Chueyee Yang

Ep. 220 – Estrella Lopez-Brea – Why it’s the Best Time to be in Consumer Insights, According to Nestlé

My guest today is Estrella Lopez-Brea, Global Head of Consumer Connections at Cereal Partners Worldwide. Established in 1991, Cereal Partners Worldwide is a joint venture between General Mills and Nestlé to produce breakfast cereals. The company is headquartered in Switzerland and markets cereals in more than 130 countries.

Prior to joining Cereal Partners Worldwide, Estrella was the Knowledge & Insights Senior Analyst for Coca-Cola where she guided the BU’s decision making processes and development of the Coke Masterbrand strategy and their innovation pipeline.

Find Estrella Online:

LinkedIn

Website: https://www.nestle-cereals.com/global/en

Find Us Online:

www.happymr.com

Social Media: @happymrxp

LinkedIn

This Episode’s Sponsor: 

This episode is brought to you by G3 Translate. The G3 Translate team offers unparalleled expertise in foreign language translations for market researchers and insight professionals across the globe. Not only do they speak hundreds of languages, they are fluent in market research. For more information, please visit them at G3Translate.com.


[00:00]

On Episode 220, I’m interviewing Estrella Lopez Brea, Global Head of Consumer Connections of Cereal Partners Worldwide. But first, a word from our sponsor.

[00:09]

We’ll take just a moment and thank G3 Translate. They have been a very valuable partner for Happy Market Research podcast, and the work that we have been doing here. I greatly appreciate it. They transcribe each one of our interviews, which range from 20 to 40 minutes, for free for us. It is a humongous benefit because it improves overall accessibility of the content that we are creating jointly with the research community. They have a unique approach. They are able to turn things around within 24 hours. I am very, very grateful for G3 Translate, and I hope that you will consider them for your next translation company project. Take the time. Go ahead and go on social media. You can find them, simply Google “G3 Translate”. That’s the number “3” and you will find the website as well as on LinkedIn. It would mean literally the world to me if you take the time to do that. Thanks so much.

[01:07]

Hi, I’m Jamie Brazil, and you’re listening to the Happy Market Research podcast. My guest today is Estrella Lopez Brea.

[01:16]

Correct.

[01:17]

Yay! Global Head of Consumer Connections at Cereal Partners Worldwide. Established in 1991, Cereal Partners Worldwide is a joint venture between General Mills and Nestle to produce breakfast cereals. The company is headquartered in Switzerland and market cereals to more than 130 countries. Prior to joining Cereal Partners Worldwide, Estrella was the Knowledge and Insights Senior Analyst at Coca-Cola, where she guided the business units, decision-making process and development of Coke’s master brand strategy and their innovation pipeline. Estrella, thank you so much for being on the Happy Market Research podcast today.

[01:54]

Thank you for having me. It’s a pleasure.

[01:59]

So tell us a little bit about your parents, where you grew up and how that has impacted your career.

[02:06]

Okay, so I am originally from Madrid, from Spain, but I live in Lausen, in Switzerland. I have two kids, in case that is interesting. I have two kids, and they are starting to approach the dangerous zone of being a teenager. Particularly about my parents, they are now retired, but they have been very, very active all their life. My father is a lawyer, and my mom, she had passion for HR so she was a HR Director; very busy people, very focused on their carriers, but at the same time very focused on their children. I have three brothers too. Well, that has influenced my career. That’s interesting because they both taught me different values. And I think it’s coming also from what they did for a living and that influenced certainly my carrier path and my choice to do consumer insights.

My dad, because he was a lawyer, his whole focus on honesty and what is right and wrong and not compromising yourself for the wrong thing was always in my mind. But since I was little, I would say: “No, that can’t be done. That’s wrong.” And that’s interesting because, that kind of objectivity is something that I always look for. And I guess now it’s very important in the research world.

And my mom, being in HR, she was very focused on empathy. She was always talking about people, and how important it was to talk to people as people, no matter who they were and where they were from. And she was always such a strong woman. She always told me: “Never give up.” You know things that you like and what you want to do in your life. So she taught me that no one is going to give me anything for free. I have to work really hard for it. And she also taught me about the importance of empathy and getting to know people deeply. And I think that’s another piece that was attached to me, and another reason why I love consumer insights and getting to know people from around the world, and getting to know who our consumers are.

So I think they influenced a lot my career. And then, in terms of my career, I started working in the research industry when I was living in the US, in Chicago. I lived in Chicago for five years, and that’s where it all started. And then I moved back to Spain, and worked for Coca-Cola for 10 years, where I held very different roles. And then my last kind of journey has been three years ago, when I was called for a job in CPW, Cereal Partners Worldwide, here in Switzerland. So here I am today, enjoying every single day.

[05:27]

Yes, congratulations. So there’s a couple things that I want to touch on. One is also having two teenagers, actually, almost three now teenagers at home is a terror. It’s a terrifying process, right?

[05:43]

I think they are still in the safe side.

[05:44]

Yes, that’s good. The role of parenting has obviously maintained the same. You’ve got to create clear boundaries for kids and help them make educated decisions. You can’t obviously control the decisions; that’s the same for me when I grew up. But the world has evolved dramatically from when we were in our teens versus the youth today, and it’s interesting to me how they have so much more information at their fingertips and the opportunity that creates for them from just an ability to be able to gain knowledge. My 15 year old last night told me that he and his friend are starting a clothing brand, which is hilarious. Something that I would have never thought would be possible as a young person. And he’s just looking up online how to accomplish those objectives and working against it.

[06:56]

Yeah, it’s an amazing age, when you see them also how they are transforming from being kids to be semi-adults. And the transition process is interesting and rewarding too as a parent, to see them grow and become this young person that you feel so proud of.

[07:22]

Yeah, absolutely, it is a rewarding, and also terrifying journey at the same time, it is both. One definitely lives in a state of tension.  So your parents have clearly impacted you from a value perspective. I liked your mechanic, the three-legged stool that you articulated: honesty, don’t compromise, and empathy. And maybe the fourth piece being a work ethic, right? You’ve got it. You’ve got to make your own way or take responsibility for where you are and where you want to get to. It’s interesting to me because, especially in context of ESOMAR and Joaquin, who introduced you and I in Amsterdam at the IIEX conference. Those tend to be the core values of the industry.

[08:19]

That’s true. That’s very interesting. I hadn’t thought about it. But now that you say that, it makes sense. Yes, they are important pillars. Because at the end of the day, our industry is about treating people right and getting to know people. And we are people. So if we’re able to see ourselves with those values, I think we’ll be able to understand our consumers. I think it’s important the knowledge of don’t treat others like you don’t want to be treated.

[08:54]

Yes, the Golden Rule.

[08:55]

Yes.

[08:59]

So I’ve done a fair amount of ethnography. I found myself in my early career thinking of the consumer as a “they”. What I mean is I didn’t personalize their specific journey. And I found as I have been now in my late 40s –I’m just a late bloomer, so for those interested, but it really is about “we”, this connection of all of us and how that needs to be involved and how we informed the brands from the consumer’s point of view. So, really, the personalization and the connection that we make with those consumers and the application of those insights into the brands on informing them on that consumer’s point of view is, I think, the core tenant or a solid way for us to be able to bring value.

[09:50]

To me, it’s the only way we can create value. If we don’t know what consumers value, it’s really hard for us to create value. So we need to get to know people and their struggles and their aspirations and their intentions in order for us is to be able to provide products and services that they can use. Otherwise, we can create the best innovation in the world but no one is going to buy it.

[10:15]

So we have all faced challenges. What is one of the biggest challenges that you have overcome either personally or professionally?

[10:21]

I’ve been lucky enough to not having any big major problem in my life, like health or things like that. I think probably my biggest challenge is something that is not very original and that a lot of other people have it too, especially women, which is kind of like that element of finding harmony between my personal and my professional life. I think that is probably not the challenge because I was literally struggling for it but because it has really been a constant element that you have to deal with when you have a career that is relatively successful, and if you have a family that you care for. I have always been lucky. I have always had some kind of support net to help me cope with both aspects of my life, whether it was my parents or a trustworthy nanny or an au-pair or a friend that you can tell: “Hi, can you pick up my kid from school?”, that kind of thing.

But an interesting challenge came to me when I moved to Switzerland with my family 3.5 years ago because on top of the implications of not speaking the language and all of that, my husband left his job to support me, and to be a stay-home dad and take care of my kids, and that has been an interesting process. And it hasn’t been challenging even to accept it for us, and even just to be proud of it and to make the most out of it because it is unusual. But it has been really great because I have been able to focus on work these last few years and advancing my career and getting to do my job the best I can, knowing that my kids were in the best hands possible while they were adapting to the new environment, and getting to know the language. And my husband is loving it. Because he is having for the first time the opportunity to spend quality time with our children, which is something that he never thought, especially now, in this kind of changing times we’re talking about, when kids transition in a little bit into being teenagers. So it is not that I recommend people to follow the same path. But what I mean is that the learning for me has been that you have to do what works for your family, and without letting conventions or other people’s opinions influence you. This has worked for us in this period of time. It might not work, later on, but it has worked and it’s working well, and it’s allowing us to find this harmony. So that’s my little story of my challenge.

[13:36]

Yeah, that is super interesting. Women, I believe, face a tremendous amount of guilt externally and then internally. This is my understanding after conversations with other people, by the way, I’m not personalizing it. But when you have children, you’re either feeling guilty if you’re not working or there’s a guilt, if you are working, and it’s a really interesting dynamic that society, I think, has set this view of what is the right way. And if you can step out of that and operate in a more truthful or self-aware perspective, then you can shake those shackles, forgive the metaphor, of guilt and create an environment that in fact you will raise a healthy, successful family.

[14:45]

That’s true.

[14:46]

But it’s hard!

[14:46]

It’s hard. Yeah, it’s hard. But if you love what you do, you just can’t compromise. As I was saying, something that my mom told me when I was starting my career once when I was pregnant: “Don’t look at the money.” In Spain, it was recession time. And a lot of people stopped working because it was even more expensive to go to work for them than staying at home with their children. It was very interesting. A lot of people were saying: “it’s not worth it for the little bit of more money that I earned. I’ll just stay home with my kids.” And the one thing my mom told me is: “It’s your decision. But if you love what you do, don’t give up. And don’t look at it from a cost-effective point of you. Look at it from the point of view of you’re doing what you love.” And I always follow that, and I think we should all follow that. And if that means breaking a little bit the norm, that’s fine.

[15:56]

Tell me about the research project that you’re most proud of.

[15:57]

Oh, I think I have a very recent one here in this company where I am right now. It has been pain and a reward at the same time. It’s a really huge project, and probably the biggest product piece of foundational learning that the company has ever done. It’s a big project in across all the regions in the world, across different markets that took me probably a couple of years from beginning to end, and taking personal time because I had a small team and it faded away, and I ended up working at it on my own. But it has really helped the organization be consumer-first and understand what the consumer is about.

It’s a huge consumer segmentation about the needs of the consumer. That’s why the consumer is always at the heart of everything. Everything that I talk about. But it’s really about knowing who consumers are, what they value, what they need, and then for us to be able to develop strategies, innovation that meets the consumer needs. So, it’s been a huge one with a lot of impacting the organization. That’s a reason why I feel very proud of this because it has really helped the organization to be more consumer-centric by deeply understanding consumers. And it has really influenced the long-term plan of the company.

And it has literally touched all the innovation pieces we have in our long-term plan. It has influenced the brand’s strategy of all of our brands. It has landed across all the markets and the regions and the functions. And every time I see an image of my project or a mention of my project, from the CEO to a person in another region, a BO  somewhere or a Marketing Director in the region, I feel really proud because it was really tough, but it is really creating an impact. It’s probably the project that I’ve worked on that has been more impactful

[18:12]

I didn’t realize that there’s a lot of confidentiality around customer segmentation in every space. But is there a part of the project that you can share, some sort of nugget that would potentially inform a different decision being made?

[18:38]

You mean sharing?

[18:42]

Businesses, the executives that are making the decisions are looking for information, and that information has to come to them in close to a real time often because they have to make a decision. The speed of decisions just continues to increase. So as you think about a multiyear segmentation, which is a heroic effort, by the way, how are they interacting with that data, the insights that you provided them so they are able to make an informed decision?

[19:19]

So for multiple fronts, on one side is just a unified long width to talk about our consumers or the different segments of consumers and the same language across the whole organization to talk about those needs that consumers have for our occasion, which is breakfast. Then, opportunity identification. Where are the white spaces? Where we’re not playing, which might be very important for consumers that we don’t have a need. We don’t have a solution for them. So it has triggered innovation on that side too. And again, brand strategy also because… and portfolio assessment. We have a pretty broad set of brands, and we need to differentiate them, and understanding who are consuming those brands but also, how do we pull them apart so that they can play in a bigger space? And when we are developing innovation, we also want to be true to the positioning of those brands and who the consumer is. So there have been really different fronts. And then again, opportunity identification, which white spaces for the largest markets are at a global level and then at a regional level.

[20:51]

So tell me about a market research challenge that you are facing today.

[20:57

Nice. I think I might have two instead of one. I think when one is pretty obvious: it’s technology. A challenge is not something negative to me. A challenge is an opportunity, right? But I think in this changing period where technology has completely disrupted the industry over the last 3 to 5 years after a pretty quiet and stable period, I would say, I think we are being good at adapting technology to increase consumer engagement, to reduce the dropout rates, to get more accurate data. I think we have evolved there, but there’s a lot of shiny objects out there that I feel that neither companies nor research agencies know exactly how to use yet and, of course, I am talking about for virtual reality, and machine learning and things like that. So we really need to look for ways to better understand how to use technology with purpose. So I hate when a vendor calls me to say: “Hey, we’re doing a lot of things in VR.” Don’t tell me this. Ask me what’s my business challenge. And I’ll tell you what it is. And then you tell me if VR is the way to solve it, but not the other way around. What do you think?

[22:30]

I 100% agree with this point. So I consult for a number of start-ups, and the biggest complaint, if you want to think of it that way, that I’ve had or that I have, is that oftentimes entrepreneurs will have a great product or service that they are trying to map to a problem. So they start with the technology, and then they’re trying to figure out “Okay, good. Where does that fit? How can I monetize it?” I always say you guys got to reverse the side of it. You know you need to focus on where’s the customer’s pain point in the market. And that represents the opportunity that then you need to apply the technology or the service or however you are banking your solution, so that it adds value to the customer.

[23:27

Absolutely.

[23:27]

So you said two things. That was one.

[23:28]

Yes, the other one, which to me, more than a challenge, is an opportunity. And we talked about it before, that is, consumer empathy. There are studies out there that prove that consumer-centric organizations who put the consumer first are the ones that are performing the market. I don’t know if you’ve read this 2019 Watermark Consulting study? Have you read that?

[23:58]

I am going to. I have not.

[23:59]

So it’s very interesting. They look what happened to the cumulative stock performance of the top Tier 10 and the bottom 10 traded companies in the past 11 or 10 years. And the result was that the leader in consumer experience or consumer empathy outperformed the S&P 500, the American stock market index, by like 45%. And the bottom companies performed way worse. It was something like 70% less than the same average. So there’s proof that consumer-centric organizations do better and because they create value for the consumer, which is what we were mentioning before. So it’s a key focus for us to ensure that basically every decision-making element is based on the consumer. We want to know the consumer better than anyone else. Are there, to the field, which is something that we have forgotten. I think like being behind the mirror is kind of like past those times. So really getting to know what’s the tension?  Who is there? And put consumer-centricity at the center? I mean, right now, we’re trying to create a consumer-centric kind of activity that we are partnering with HR to make the whole company across market regions to be more consumer-centric. So it’s not the role of CI to be consumer centric. It is not their role of our function. It is everyone’s role and responsibility to know that consumer.

[25:56]

Oh yes, this is something that I’ve seen trend in the last relatively recently, where there’s a concerted effort to create consumer empathy across the organization. So everybody inside of the company is thinking about the consumer first in the decisions that they’re making, which of you think about it from a HR perspective is a material shift from how we used to think about things. Organizational clarity is probably the number one biggest challenges of any CEO or CHRO. How do you guys actually empower that knowledge across a large organization?

[26:48]

There are many different things involved. One of them, obviously the most powerful one, is that we have a CEO that is probably the most consumer-centric person of the whole organization. And that helps. He goes to visit markets. In every market he visits, every week, or every couple of weeks, he meets with the consumer. He goes, and does in-home interviews with consumers. Every market he goes. And then he posts back to the whole company what he has learned about the consumer there.

So there is this culture of the consumer must be put at the center, which starts from the top, and obviously our function is a critical piece. We bring the consumer along the process, we use research for learning purposes, not for validation. So we are more about finding agile ways to meet with a few consumers against some intuition to move to the next level or the next step of the journey more than having everything 100% finalized, and let’s just test it and do this huge research, which we also do, and we also do validation. But then we have tools. We have an empathy tool kit that has been rolled out to all the regions on the market. So whenever there’s a project for a brand in one region, they can go down and look at activities and do empathy activities like shop-alongs, or go to the store as if you were this consumer, or meet someone of these characteristics. That kind of thing. The project that I was telling you before has also helped a lot because now we have the same language and knowledge about who these consumers are, how to pull them apart, what are the values that they have, what do they care for, what is the food that they eat. We get to know them much better.

So there’s different tools, but they all walk in the same direction. And I say that, in the organization in the last few months, and especially since the new CEO joined, that our function is a trending topic. Ha! So everyone wants to go and that’s the best position you can be at right, when you have a meeting with senior leaders, and one over the other says: “Oh, I can’t believe they haven’t been seeing the consumer”. Really? They are proud of it. They say: “Really? I saw the consumer last week.” And that’s amazing because that means that they are all preaching what they believe in. Walking to talk instead of it just being words.

[29:35]

There definitely has been a visible, measurable shift at the C-suite with the adoption of insights from a direct connection perspective. There used to be, from the organizations I was exposed to, which I feel it was a lot, a few layers between the special key executives and consumer insights. And now I’m hearing more and more about organizations, even at the CEO level, who are making direct connections on a regular basis with consumers in order just maintain their fingers on their pulse.

[30:10]

Yes, this is great. I mean, what else can we ask for, right? As people who are responsible for a function like us?

[30:20]

Honestly, it is literally the most exciting time in my career…

[30:26]

Yes, I feel the same way.

[30:27]

…for market research and consumer insights in general. Because we quite literally have a red carpet into the boardroom and direct influence. I’m actually very thankful for the Qualtrics acquisition because I believe it created, I believe it is a fact, value association with consumer insights. So thank you SAP for that. The number of calls I’m getting from financial institutes that are looking to make investments and acquisitions in this space is every day, multiple times a day. And that’s from maybe one or two a month rather prior to that acquisition. So every organization is now having to perk up and say: “Wow, that that’s an oversized valuation.” Or is it? And if it is and then they have to understand what that thesis is, and to your earlier point about the Watermark study, who doesn’t want that, to outperform the S&P 500? And the way that you do that is just profoundly obvious, to your point

[31:42]

Now the question is, and that is the reason why it is also a challenge, you have to actually prove, I’m not saying proved with numbers, but there has to be actions or actionable insights in order to maintain that traction. If we as a function are given the trust to go and be the center, let’s say, of any initiative and we do not prove that what we do is actually having an impact in the organization, then the virtual circle can stop. We do have a responsibility to perform and to ensure that, and I strongly believe that, being consumer centric results in better decision-making and therefore, growth for the company. But you have to perform. You have to have a team that is focused on actions. There’s certain elements associated to make that happen.

[32:37]

The ROI on research… We have got to really frame what we do to that point, because it is easy to start retrenching in what I will call the “traditional methodology approach,” which is more validation to your point versus learning. Of course, you have to have both in an organization.

[33:04]

Right. And if the organization invests in the function because they believe that’s how we should do it… But then the company doesn’t perform as expected. Then there is a danger of saying: “Oh, you know what? I thought you were very useful, but you’re not.” So there is also an element on us to make sure that what we learn from the consumer is actionable, is transformed, and that those insights are transformed into things that are actionable and important, and differential for the company.

[33:37]

This gets to the heart of my earlier question, which is market research used to sit as a specific function inside of the organization. And now what I am seeing is market research is giving information and empowering insights so that when the UX designer or the product owner or whoever inside the company has a question, then they immediately have a treasure trove of data that they can then make a decision. And to your point, that is the big challenge. I believe we have to see ourselves as empowerers as opposed to gatekeepers. I think that is something that I’m just seeing over and over from a theme perspective from consumer-based organizations.

[34:35]

Yes, empowerers, story-tellers…

[34:37]

Absolutely!

[334:38]

…influencers.

[34:39]

So there has been a lot of technology that is introduced outside of market research, and market research companies are always thinking about how can we apply this to our space, even though we are not on the early adopter part of the curve. How do you think the market research space is going to be different in five years?

[34:58]

Well, I think technology obviously will impact. We have only started. So I think the digital transformation of channels will happen. So more channels, more complex channels, more blurriness between the online and the offline world. I think that can only increase.

I think is the other element is mobile-only. We are now in transition time. But in a few years I don’t think we are going to be having anymore desktop surveys. I think we are probably already really late but it’s starting to move. Then virtual reality, I think, also as a way to engage with consumers and a way to be efficient, especially for big organizations that operate, for example, in different markets or are across different channels. I think it can be super-powerful, but with purpose again. And then artificial intelligence as well. I think it will become the mainstream data analysis tool. It will save time and be more accurate and will be more accessible. And I think the other element is an even higher need for agility and speed, because people’s expectations are faster every day. They are increasing faster every day. Information is expected to be available now immediately both, I think, from the consumer side but also on the company side. So consumers want things now so they cannot wait for a year until we have the pipeline ready. But companies also need the information of those changes to be available faster. So I do see this trend of less big, robust pieces of information as I was mentioning before, and more agile, do-it-yourself approaches that get you closer to the consumer along the process. I mean, if we look at things like the proliferation of the online communities nowadays, I think it’s a sign of people just bringing the consumer along the journey in a way that is not perfect but it’s going to give you some informed intuition to move to the next stage.

[37:29]

Can you elaborate a little bit on the online community’s point that you just made? I think it is really important.

[37:34]

Yes. I think there has been a broader use of online communities in the last few years, where you basically had the opportunity to have a group of consumers at your fingertips in an environment that is friendlier to them, where they move around in a nice way, and it gives you an agility to find answers or insights or a better understanding that we have never had before. Before, we had a question, and we asked it. You put the question, you take it, you analyze it, and now you can just have your consumers bring you there, bring some questions, read what they say, what they relate to, the comments that they make. And that already triggers something for you to continue working on what you’re having without having a month of stop. I don’t want the perfect report. I don’t need it. I don’t need a 50-page report with every single quote. I can just go in there, and see what they’re saying, and that will help me understand, me or the marketing manager or whoever. So I think that is one tool. But I think it’s a very powerful one that allows agility and consumer-centricity at the same time.

[39:01]

I love that. What are the three characteristics of an all-star employee?

[39:06]

Okay.

[39:10]

And by the way, there’s no pressure because your mom has been in HR a long time.

[39:16]

True, true. Well, I’m going to tell you what I look for in my team, for example, or for myself. I don’t know if it will be an all-star but I’m sure these are the things that are important to me. I don’t know if it will be three. But they are the things I have noticed.

The first one is being action-oriented. We talked about it throughout the whole conversation. We need people that are result-driven, who are having an impact in the work that they do, that look for solutions that are efficient, not from the point of view of working a lot of hours. It’s about making sure that what they produce, that the work that they do is having an impact; it is triggering an action. That is super important to me. And that’s usually related to other skills, such as the ability to influence or having initiative. Usually, those employees who are action-oriented are people who are just nominating themselves for any project that’s coming and have these skills to persuade with the information that they have or to influence with the information that they have. They are always looking for an impact. I think that will be one.

We also talked about the need for agility, and I think that makes me think about the need of being flexible and adaptable. The world is changing every day, and what is a critical skill to me is being able to pivot, to change, to be able to adapt, to be able to navigate in uncertain waters without struggling. I face unclear situations every single day. You need to be able to cope with them, and make the most of it and don’t stress. So again it ties me back to this initiative that we were mentioning before: People who have a better ability to adapt to new environments are usually asking or nominating themselves for a new challenge. Because they want to pivot, they want a change, they look for this movement and not to stay like stiff in the same role. Because that’s also what helps us grow. They see value in it too.

[42:02]

I totally agree.

[42:08]

Also, the other one to me is just having commitment, and having passion. If you don’t have passion for what you do, just go home. Passion and commitment can overcome other skills. You don’t need to be necessarily the smartest person in the world, but if you are dedicated, and you’re passionate, you will make it happen. And to me, that’s very, very important. People need to be motivated to enjoy coming to work every day. We work a lot of hours so you have to care for what you’re doing. It’s just a mindset more than a skill. You just have to enjoy what you’re doing. If you are a passionate person, you will find the way to make whatever you do exciting. I think those would be my three. If a person has all of these three skills, I think they will have also leadership qualities because they will be confident, they will be willing to take challenges, they’ll have initiative, they will be responsible and good communicators. So it all ties together.

[43:32]

I am here taking a lot of notes. I have never heard anyone connect the core values to a byproduct of leadership. I think that is super insightful. It’s funny because it completely drives the type of people that you want inside of an organization, which in an ideal world are people that are moving the needle, and see themselves as empowered, as opposed to more of the Atom rubber stamp-type of a role. And when you think about consumer-centric cultures, that has to be a characteristic of it because you need everybody, from the intern to the CEO, to ask themselves the question “Is this good for the consumer?” And as soon as they feel like “Gosh, maybe it’s not”, they have the opportunity to be able to raise their hand. You can’t do any of that unless they have that sort of mentality.

[44:38]

Agreed.

[44:39]

So I have a couple of questions that came in on LinkedIn when I posted this morning that I was having the pleasure of interviewing you. Do you mind if I ask you some of the questions?

[44:49]

Of course.

[44:50]

So the first one is from Matthew O’Mara, and he asks: “Is it true?” And he claims his daughter believes it is, that cereal can actually be dinner.

[45:02]

Well, I think any food can be eaten at any moment. What do you mean… Idon’t know if I understand what it means when he says it can be dinner.

[45:18]

I think he’s probably in a power struggle with his daughter. I assume he doesn’t want her to eat cereal for dinner.

[45:29]

Oh, for dinner, okay. What I can tell you is that we operate in the breakfast occasion for a reason because we know that we have the ingredients and the nourishment that are relevant at the breakfast occasion because we are products where the category might have some bad press. But actually cereal is a very great option at breakfast. It has all the right elements to be present in this occasion. I don’t want to advocate for anyone to go ahead and all of the sudden have cereal for any meal. I don’t want to get into that discussion, but I know that at breakfast it certainly is a good option.

[46:32]

I think he will like hearing that. That’s probably exactly the answer he wanted. The last question that I’ll ask you, and there are a few more than I’ll follow up with later through LinkedIn, but is from Ted Waz of the Opinion Economy, and he’s asking, and it’s a longer question, but the gist of it is: Do you guys have concerns around what he’s framing as click farms, where you have basically automated respondents taking surveys?

[47:01]

Oh, that’s a good point. That’s a good point. I would say it’s not a strong concern right now, but it’s probably one of the biggest concerns that we’ll have in the future. When we were talking about the digital transformation and the artificial intelligence and all the machine learning coming, I think that will be a very, very big watch-out that the industry is going to have to figure out. I think that is a great question indeed.

[47:41]

So my last question is: What is your motto?

[47:45]

I don’t have a motto but if I had to make one right now, I would say it’s just “do your best”. It seems small but and it might sound probably very cliché, but to me it means just so much. It means that you’re just putting the best effort into everything that you do. And to be honest, it’s probably the only way you can live with the feeling of self-satisfaction. Because even if things don’t turn out, there’s always going to be someone that is better than you, there’s always going to be someone who did an amazing job. But if you feel that what you’ve done is the best that you could, that you have put your soul and heart into it, that is already rewarding. It’s only yours. I think that personal satisfaction is only yours, and you deserve. And that’s a personal feeling that no matter if things don’t turn out, you’ve done your best. That would probably my motto.

[48:57]

My guest today has been Estrella Lopez Brea, Global Head of Consumer Connections at Cereal Partners Worldwide. Thank you, Estrella, very much for joining me today on the Happy Market Research podcast.

[49:10]

Thank you. It was a pleasure.

[49:11]

And everyone, if you please take a few moments, share this episode. You can screenshot it, put it on LinkedIn, Twitter. It would mean the world to me. Also, your ratings on Apple iTunes is a huge benefit in that it creates additional visibility of this podcast to other insights professionals. I hope all of you have a fantastic rest of your day!

Just want to take a moment and thank G3 Translate. They have been a very valuable partner for Happy Market Research podcasts and the work that we’ve been doing here. I greatly appreciate it. They transcribe each one of our interviews, which range from 20 to 40 minutes, for free for us. It is a humongous benefit because it improves overall accessibility of the content that we are creating jointly with the research community.

They have a unique approach. They are able to turn things around within 24 hours. I am very, very grateful for G3 Translate, and I hope that you will consider them for your next translation company project. Take the time. Go ahead, and go on social media, you can find them. Simply Google “G3 Translate”. That’s the number “3”, and you’ll find the website as well as on LinkedIn. It would mean literally the world to me if you take the time to do that. Thanks so much.

Ep. 219 – Our Official 100th Episode: Life Lessons and Market Research Trends

Welcome to the 100th episode of the Happy Market Research Podcast! In this episode, Merrill Dubrow, CEO of M/A/R/C Research, interviews Jamin Brazil, Founder and CEO of Happy Market Research. The two take a look at the benefits of producing a podcast, market research trends, and life lessons.

Find Jamin Online:

LinkedIn

Twitter

Find Merrill Online:

LinkedIn

Website: M/A/R/C Research 

Find Us Online:

www.happymr.com

Social Media: @happymrxp

LinkedIn

This Episode’s Sponsor: 

This episode is brought to you by G3 Translate. The G3 Translate team offers unparalleled expertise in foreign language translations for market researchers and insight professionals across the globe. Not only do they speak hundreds of languages, they are fluent in market research. For more information, please visit them at G3Translate.com.

NEXT 2019 Pre-Conference Series – Stuart Crane & Paul Cornwell – Voice Metrics

The 2019 NEXT pre-conference series is giving listeners an inside look into companies such as IBM, Voice Metrics, Ipsos, and Pulse Labs.. Join insight leaders on June 13 – 14 in Chicago for NEXT, where you can discover how technology and innovation are changing the market research industry. In this episode, Jamin Brazil interviews Stuart Crane, Founder and CEO of Voice Metrics; and Paul Cornwell, CTO of Voice Metrics.

Find Stuart and Paul Online:

Stuart’s LinkedIn

Paul’s Linkedin

Website: www.voicemetrics.io


[00:00]

Hi, I’m Jamin Brazil, and you’re listening to the Happy Market Research podcast. This is a special episode that’s connected to the upcoming Insights Association’s NEXT conference. It is located in Chicago on June 13th and 14th. I do a lot of these conferences both inside and adjacent to the market research industry. I think this particular NEXT conference is a must attend if you’re interested in learning about what’s coming up “next”. Maybe that’s how they came up with the name. My guests today are Stuart Crane, the founder and CEO of Voice Metrics, which helps companies leverage voice, as well as Paul Cornwell. Did I say your last name right, Paul?

[00:48]

Yeah, you got it.

[00:49]

Voice metrics CTO. Guys, thanks very much for joining me on the Happy Market Research podcast today!

[00:53]

–Glad to be here.

–Yes, thanks for having us, Jamin!

[00:56]

You guys are speaking at the NEXT conference on how to integrate voice into the total customer experience. I’m really curious, given your backgrounds, when did you first recognize the voice was important?

[01:10]

Voice, I’ve been interested in for quite some time back in the day when I would listen to cassettes in the car and CDs in the car. I was really interesting in voice recognition:  recognizing voice with Dragon dictate, and that sort of thing. But when I realized it was really going to be big is actually when I got an Amazon Echo, I think was for Christmas in 2015, I believe, and just being able to talk to this cylinder, and have it talk back to you and start songs, and you could still talk to it while music is playing. And obviously Siri was out there. But now, it’s basically an ambient voice conversation. It just blew my mind! And then I found out that you can actually write software for it. You can write programs for the Amazon Echo. Back then, it was just called Echo. Now it’s obviously “Alexa”, and it’s a big ecosystem and everything. So I just really recognized that being able to talk to devices and have the full features of computers behind it really is going to transform things. Not that it’s going to take away the capabilities of mobile or anything like that, but supplement it in such a great way. I started looking at ways that we could program voice and got involved very early in the Alexa’s software development ecosystem and just took it from there.

[02:29]

All right, great. So Paul?

[02:31]

Yeah. So I came from an AI machine learning background prior to getting into voice, and that was sort of my segue-way into voice and where the interest came from. So actually, before I met Stuart, I was pretty hot and heavy for Alexa and the idea of building these interactive experiences. So I was looking a lot at Lex and Alexa on the Amazon side, and it just seems like a natural segue-way coming from that AI background and thinking about how these devices and experiences can be more conversational and just the technology caught up to where my head was. With the opportunity with Stuart, who had this vision, at the very beginning of what we’ve built, everything just seemed to align.

[03:23]

So I’m going to go ahead and share, and I apologize, I don’t mean to hijack the point, but for me I recognize it was really important with my daughter and the iPhone I got her when she was 11 years old. We were driving in the car for a three hour drive, so I just started making small talk. And I talked to her about her best friends, and her top three surprised me. It was Siri. So I wasn’t sure if she was making a joke. But we dived into that. And she goes: “Oh, you know, Siri, she’s always there. She’s talking to me.” In the context of an 11-year-old world perception, she really did not understand this concept of AI or bot. For her, it’s a voice that’s got a name, and is communicating to her. Sometimes it doesn’t make any sense. In fact, maybe that’s a lot of the times, especially in the early days, but now you can fast forward with where we are. I also have younger kids, a 2- and a 3-year old, and one of their favorite things to do is interact with Alexa, playing the hide and seek game. I don’t know if you guys have done that or not.

[04:30]

–Yeah.

–Yeah.

[04:33]

It’s just this construct where you can’t have a tangible game or UX –we are thinking about what that looks like, but in a voice context. For me, as I fast-forward to two or three years from now, I don’t exactly know how voice is going to look like but it feels like the opportunities for us are significant.

[05:06]

Yeah, absolutely. We were out in San Francisco, speaking a couple of weeks ago, and what we noticed just walking around the streets of San Francisco is half the people, probably more than half, maybe 80% of the people have their AirPods or headphones on. So once those have the capabilities, the voice assistants, built right into them, which they’re starting to do, obviously Siri is built in the AirPods, it’s going to be huge. It is just all over. It is everywhere.

[05:35]

So you’ve worked with a couple of market research agencies on voice surveys. What do you see as really exciting in that space? And what do you see as a material challenge at this?

[05:49]

Yes, that’s a good question.

The companies that we are starting to work with is in a really very exploratory way, which I’m sure we’re going to find out at the NEXT conferences. People want to see how can we utilize the voice’s system, whether it’s Alexa, Google Assistant, and Siri at some point to get data, get information, get feedback, get surveys and take them. So the agencies we’re working on right now are taking our survey platform, which is called Survey Line, and they’re basically building surveys similar in the way you would build a SurveyMonkey survey in the web app, and they’re showing them to their clients that are maybe big consumer product manufacturers or just product companies that have panels of testers out there. And they’re basically helping them to say: “Some of the things you’re doing to collect data and do market research in consumer research can now be potentially done by voice.” So they’re looking at things where they may have people coming into the homes and doing surveys by hand. And they want to lower the cost of doing a survey and consider also the convenience factor for the panelist. One thing we’re finding right now is the agency is looking at doing very interactive surveys that have a real voice behind it. So you actually have a voice actor, a voice talking the person through a product. “Pick up the product”, “Hold it in your hand”, “How does it feel in your hand?” And it’s basically through the voice assistant that way. They’re building some of the longer interactions. Some of the challenges we are working on right now is just the cadence, the pausing and stages because sometimes you might want to pause and say: “Well, you do this for a little while, and then come back and tell us what you thought about that.” And so those things aren’t as intuitive on a voice assistant because it wants to work just back and forth, back and forth. We have got some things that we are modifying to make it work in an environment where essentially the market research agencies want a hands-free experience. They do not want to have the person go to a phone or go to a laptop or any kind of tactile interface at all. They want it hands-free. And that’s what’s perfect for surveys by voice or a voice survey. But in some situations when they do something with a product and then they come back and say that. So some of the challenges, like I said, are related to cadence, pauses and delays and just getting that interaction as natural as possible, knowing that you’re still dealing with essentially a computer. As you know, IVR has been around since the 80s. So we’re taking what that had done, and saying: “Hey, this could be done on a voice assistant” and be done even better because you have full programming capabilities, you have really voice behind it, and so forth.

[08:54]

Stuart, I want to get to an example, if you guys have one, of a voice based survey. But before we do, Paul, I have a question in context of AI. It’s a term that we have heard a lot in market research over the last years. And the actual nailing it down in terms of how it applies and improves an outcome has been a little bit squishy in our space. Can you talk to us a little bit how the role of AI in a voice context?

[09:21]

Yes, absolutely. So I think, out of the box, Alexa and Google Assistant do a lot of things very well. A lot of the reasons that it’s improving over time are due to the machine learning and artificial intelligence that Amazon and Google are leveraging themselves. But we have found that there is still a gap. What we have tried to build, and I think what is successful, and what developers of voice solutions are doing, is they’re building their own sort of contextual AI. Using surveys as an example, we have actually created sort of our secret sauce to make the survey experience much smoother for the user because out of the box you run into a lot of things with Alexa skills and Google actions, where she doesn’t understand exactly what you’re trying to do. And if what you say or what she heard doesn’t match exactly what’s been predefined in those voice solutions, those skills and actions, then it can fall down. So coming at it from a pure voice developer standpoint, to me artificial intelligence, which can be a buzzy sort of word –we hear that term all the time – it just means basically having a layer of algorithms and logic that can make sense of what the user is actually trying to do with the intended action is and giving them that results. So that’s how we approach it. And I hope that answers it.

[11:00]

Got it. Yeah, that makes less sense. Again, going back to the simplistic example of the hide and seek game on Alexa. In that framework, it doesn’t feel 100% human, but it also doesn’t feel like going back to Stuart’s point about IVR in the 80s. It’s definitely a lot closer to the human interaction experience. All right, Stuart. Do we have an example?

[11:25]

Yeah, yeah, So what I’m going to show now is an example we put together at the Voice Of The Car Summit, which was a few weeks ago, that brought together people who are involved in bringing voice assistance into the car. Obviously, there’s a lot of companies involved in that, and the car companies themselves, the voice assistants, and so forth. So this example that I’m going to show is related to a survey that would be done after you go to a retailer, a restaurant or, in this case, a fast food restaurant. So everybody’s familiar with the receipt you would get at a movie theater or retailer, a restaurant, which says: “Oh, thanks for coming. Please take our survey.” And it has a long web URL that you have to type into your phone, or what have you. Who does that? Who is going to go, and take the survey, and type all that in from a printed receipt? So the idea is that we can just ask our voice assistant to take it. So the receipt would say: “Just start the McDonald survey” or what happens to be. And in this case, we did a demo for a McDonald’s fast food survey. So what I am going to do is I am going to say the wake word, and it is going to start the survey, and it would be what someone would do in the car as they are pulling out of the drive-through. So let’s give it a shot!

–Alexa, start the McDonald Survey.

–Hello, thanks for visiting McDonald’s today. We want to hear about your experience. This survey should take less than a minute, so let’s get started!

How often do you visit this McDonald’s location?

–About once a week.

–For the next few questions, rate your satisfaction on a scale of 1 to 5, where five is excellent.

Rate the speed of your food delivery.

–Four.

–Rate the quality of the food.

–Three.

–Rate the friendliness of the McDonald’s staff.

–Five.

–Finally, yes or no. Would you recommend this McDonald’s to your friends and family? –Yes.

–That’s great. We’re happy that you’ll recommend us! Thanks again for stopping at McDonald’s and taking our survey. Next time, try our new Mushroom and Swiss signature burger.

[13:58]

You had to throw in the advertisement at the end, of course. But I really like this. So there’s a couple things that popped for me. I will start at the beginning. First of all, thinking about programming that survey, is that hard? I know that creating Alexa skills in general at a basic level is relatively…

[14:19]

-I will let Paul hit that question.

-Yeah, it’s hard to make it extremely flexible. So we built a platform to do that. I think anyone could probably build an Alexa skill or a Google action that is built around a very specific set of questions and get responses. To sort of take it to the next level, we really wanted to build something that was really self-service and something that we call a platform. But I would say the challenges were probably with supporting those different question types and collecting responses in a way that match up with what the survey creator was trying to get. So if they are looking for a rating, we have a lot of validation around. So if instead of 1 through 5, the person said “6”, we got to make sure we come back and tell that person gently: “Okay, that’s not the right answer.” And then maybe play the question again, things like that. So it’s really just having the experience of as a conversation it could be. Then, from a programming side, it was just really building the platform to support basically any type of question and answer back and forth that someone wants. And we tried to make as conversational as possible.

[15:36]

I do think it be really funny if you did an out take version where the correction was something like: “Hey, jackass, it is only five.”

[15:46]

Yes, that would be good.

[15:47]

That’s really feeding the point of the impact of user experience in context of feedback. You really have an opportunity to help enforce brand inside of consumer feedback nowadays. In truth, we always did. I think we are just actually starting to pay attention to it more as an industry now. But having that friendly voice is such a better experience, to your earlier example, than just having to go manually and put a URL into a web browser, which is just like filing taxes.

[16:27]

Yes, for sure. We think there’s multiple benefits to it. We just think it’s another way. I mean, obviously there’s other ways to take surveys. But one of the things we really like is just how we have seen some creativity with some of our customers, who are doing things like having a user do a feedback session while they are experiencing the product, which is difficult to do any other way. But voice lets you do that. So maybe while you’re trying shampoo, or whatever, and you got an Echo in the bathroom, you could actually be answering questions on how does it feel?, how does it lather?, and things like that.

We are seeing some creative stuff, and we just love that. That’s why we try to build it as just as open as possible.

[17:10]

In context feedback, I think it is the part that is going to be interesting for market researchers, and I don’t mean that in a narrow way but in a broad way, anybody that’s interested in consumer feedback is going to find to be tremendously valuable because the in-moment experience comment is the most valuable feedback versus the degradation of feedback because of the delay in that Q&A.

[17:38]

Yeah.

[17:42]

What kinds of content or insights are you actually capturing beyond the obvious answers to the questions?

[17:46]

It is all centered on that: the responses, as you probably are aware. So Alexa and Google don’t give anyone like raw access to the audio itself. You can’t set up a skill and then get the audio file for what exactly that user says. I want to hear their voice. It doesn’t work like that. That’s for privacy and good reasons. So they do a great job with the Speech-to-Text. So it relies heavily on Alexa and Google’s natural language processing and Speech-to-Text capabilities. So we have different question types that we support. So we support asking a user for a rating from 1 to 10 or 1 to 5, whatever they want to set up, “yes/no”, and then multiple choice, of course, and then free form, which is really wide open. So if you just want to ask for the user for some comments, things like that, we have that capability. And we have just added a new question side. We just call it “mobile phone” but it’s basically the ability to collect contact information from the user. And the way we’re implementing it right now is if the user wants to supply that, they get a text, and you need to lead to that phone, and it sort of makes that connection with the brand or whoever is conducting the survey. So we’re looking at different ways to provide value there. But as far as the actual insights, we are just looking at providing as accurate a set of data as we can per survey and then our customers will gleam the insights they want from that data.

[19:21]

Is the data set like a CSP file?

[19:27]

Not exactly. So right now that’s how it happens.

[19:32]

So really easy to integrate into whatever platform they’re using for their analytics. Is there any additional metadata that you are gathering, in a traditional web or web-based platform? You know, you’ve got a host of stuff like time stamps and a browser version, maybe even location?

[19:54]

Yes. Well, we could get what device they are using, whether it’s Google Home or Alexa on them, and then within that which type of device they get. We can only basically get whatever we are given by the platform, the voice platform, and the Google Assistant. But there is some metadata and Paul and I work with that and we provide that to some of the clients.

[20:13]

Got it. I’m going through the site, I literally just purchased my breakfast this morning from McDonald’s. That is maybe not an endorsement of my health, but I do like McDonald’s a lot. So I finished going through the check out. How do I get that? What’s the trigger event? Is it in cars? Is it later? How does that survey get served up to me, so to speak?

[20:45]

Yeah. That’s basically going to be the challenge. I think going forward, Jamin, it is basically what we call the “voice call to action”. And the “call to action” could be in so many different forms. It could be like in this example that we gave, it could be on the receipt, and it just says: “Launch the McDonald survey”, or whatever engagement or voice action they want to start. It could be printed on a product and say: “Tell us what you think. Just say to your voice assistant XYZ”, and we would obviously rebrand it to that product or to that company or whatever they want it to say. So that’s going to be going forward. That challenge is how do you implement that call to action? We are working with a company now that does direct marketing. And they have huge brands like Wells Fargo and these companies that do massive amounts of direct marketing. And they’re adding voice response into it because they get somebody who could get something in the mail and it would be “Go to our website” or “Call 1-800 number”. Well, now you just interact with us through voice, and it would launch essentially a voice interaction, which could be a survey asking them a few questions and based on how they answered those questions, it could do different things and contact them that way.

But I think it is going to be tricky because it is going to take time for companies to say:  “Where do we want to put this call to action and what should it say?” And that’s something that we can help with to a certain degree. But we’re not the experts on that so much as they are.

[22:18]

It seems like that’s a big partnership opportunity that you’re talking about.

I am thinking about in the market research space, we have got a host, whether it’s Dynata or others, very large market research sample providers, and I don’t know how big the industry is between $2 billion and $4 billion, if they have a voice enabled device as a variable inside of their profiles, then maybe there is that trigger event that could happen. There’s a lot of bubbles in this scenario, but assuming that there was an app that was tracking geo.

[22:56]

So just think of emails and how many people do SurveyMonkey or Qualtrics surveys or Zoho or whatever. Most of the time they are asking people to take their survey because they are sending out an e-mail or it’s on social media or somewhere. That could be supplemented, maybe not replaced, but supplemented with “Do you want to do it with your voice assistant? Just say launch bla-bla or “Start the XYZ survey” or whatever it is. Now, obviously, surveys by voice need to be friendlier in a voice contact so you can’t take every SurveyMonkey survey or web-based survey and just copy and paste it into a voice survey because there’s just nuances, and cadence like we talked about before, that are necessary. It’s better sometimes on a screen to sort things or see a lot of multiple choice answers, and that doesn’t lend itself to voice. But the call to action could be in similar way to the way SurveyMonkey’s and online surveys are done.

[23:57

So in 2023, it’s projected that there’s going to be about $80 billion that are going to be purchased through voice. This is for me a massive number, and I’m seeing in my own user behavior that I procure or buy stuff through my Alexa device, more of the CPG type of stuff is what we’re doing. Google and Amazon of both very aggressive and gobbling up the generic brands. I know that has been well documented. So, like generic paper towels I believe is now owned by Amazon.

[24:36]

Yes, Amazon Basics.

[24:37]

So, in a voice-based, consumer journey, which is invisible, I don’t have any opportunity to intercept the consumer if I’m Scotts, for example. Why isn’t voice a bigger deal right now for the CPG spaces? Or if it is, are they just operating in secret? As a consumer, I’m just not seeing a lot of investment, and as a practitioner, a lot of research. There is not a lot of noise in the space about investment that’s being made in this invisible consumer journey.

[25:20]

It is a good question, and because we’re in the voice industry, we do see a lot of internal investments of companies that are building things now, but they don’t want to just rush them out to market. I was in the healthcare space for a long time, and they’re actually wanting to get voice capabilities for patients and for doctors and so forth. But the brands, like you said, they’re taking a slower approach, and they’re doing a lot of internal testing and building things. But they’re also looking at “How do we get on there?” Because Amazon and Google have basically a native interface. And as soon as you start talking, Google and Amazon know who you are. But until you open a skill or an action or some interface with that brand, they still don’t know who you are until you somehow give them permission. So it’s much more difficult beyond Amazon and Google to get that.

So that’s why we’re building in things like getting contact information right through it, and doing look-ups with codes and so forth so you could just put a code in. But there is a lot of investment going on by brands and also ad agencies. The agencies are basically thinking: “How can we get into voice?” And it’s slow for a couple of reasons, mainly because they are just trying to figure out how it all works. But also they want to be careful not to roll something out that’s half baked.

[26:45]

I did some analysis earlier this year on voice ratings. I was using it as a surrogate for app utilization in voice. Unfortunately, there is not a corollary. The number of rate ratings, for example, does not mean that’s the utilization of the app. But having said that, it still is really interesting to see what products are apps that are being used in a voice-based context on just frequency. And so one of the things I thought was really cool was that, I believe it was GM, that has an auto-start, voice skill to the vehicle. Again, I am intuiting. I live in California, but it’s cold outside so I’d like to start my vehicle ahead of time so it can warm up. And that’s the extent of the skill, which is very highly rated. But they were the only automobile manufacturer, even including Tesla, that had any voice-based app that was in the top 100, I think is what I pulled. So it feels like just transparency in terms of what apps are being used and by whom could be a big opportunity for whether it’s a company like yours or even a company like Nielsen for communicating to the industry what is trending from a user experience perspective.

[28:15]

Yes, exactly. I think it all gets back to that “voice call to action” until people know what to say to their voice assistants, what to ask of their voice assistants, and have a prompt.

It is going to take time because people know how to say: “What’s the weather like outside?” or “What’s the sports score?” They can turn their lights on and off; I have all that up in my smart home, and it’s a great way to play songs. That’s the biggest use case of all for the smart speaker. But I think once brands and companies and different entities start doing a voice call the action where they say: “Well, here’s our website. But then, if you want us by voice, say this”, you will just see that take effect. And then, it’s going to take some time, like you said: 2023, $80 billion. I think in 2023, you will just see a lot more calls to action “Hey, engage us by voice!”

[29:09]

Yeah, that’s right. It is the whole user journey that has to trickle down to just the knowledge of how to interact because it’s invisible. You don’t have those user prompts that you would have. I go to the Star Trek example, right, where you know you had the computer, and then there was a constant interaction with it, and then they would give commands to the computer to transfer controls to whatever. Are you seeing that as one of the maturing use cases or potential use cases where there is a voice-based Instagram feed and then the person asks to transfer that to his/her phone or something along those lines?

[29:53]

Not yet. It’s just kind of too much of a reach for somebody to know to do that. But I think once there is a good use case that it actually gets habitual… It’s our about habit! Turning on lights and doing things that are IoT, and if they do them often they get that habit, and then you get that. But if somebody doesn’t know to do something, to your point before, there is really no, no visual interface. In most cases, you have Echo show and you have some visual. Actually, that brings up a good point, Jamin, I do actually give it commands when I see things on my Echo show that they prompt me with an article or to do something. Right now it needs that prompting or call to action. As more companies put them out there, you’ll see more use cases, and then people won’t even need to be prompted. They will just use them. But we are still in pretty early stages on people doing things like transferring things. It will come but it’s going to take some time.

[30:53]

So what is one practical take-away that our listeners can gleam right now from your upcoming talk at NEXT?

[31:03]

I think the biggest thing is that feedback and surveys or just getting anything from a consumer or an end user, an audience is doable by voice with your own branding, and it’s just now becoming possible. So what we are going to show at the NEXT conference is basically a platform that allows you to create a survey like SurveyMonkey, but it could be branded for yourself so that it’s your own voice. It’s not the Alexa voice or Google Home voice. It’s your own voice throughout the whole thing, like I showed, and you get the data, you get to ask what you want to ask, and that the user is happy with the experience. So that’s what we’re going to show, and it’s evolving. It is still very early stages in this. But as we improve our platform, we are leveraging the capabilities that are being improved by Amazon Alexa. And then there’s also obviously Cortana and Bixby and some others, and Siri. Once Siri has the capability of program, Siri will have that as well.

[32:06]

If somebody wants to get in contact with you, how would they do that?

[32:09]

Yes, the best way is just go to our site, which is www.surveysbyvoice.com.

[32:19]

Got it. My guests today have been Stuart Crane and Paul Cornwell of Voice Metrics. Thank you both for joining me on the Happy Market Research podcast today.

[32:28]

–Thanks a lot. We enjoyed it.

–Great. Thanks for having us, Jamin.

[32:30]

Everyone else, for more information on the Insights Association’s NEXT conference, to hear speakers like these fantastic gentleman and others, please join us in Chicago June 13th and 14th. You can also find more information on our website http://happymr.com/next2019. Have a great rest of your day, and I hope to see you there!

NEXT 2019 Pre-Conference Series – Frank Kelly – Ipsos

The 2019 NEXT pre-conference series is giving listeners an inside look into companies such as IBM, Voice Metrics, Ipsos, and Pulse Labs.. Join insight leaders on June 13 – 14 in Chicago for NEXT, where you can discover how technology and innovation are changing the market research industry. In this episode, Jamin Brazil interviews Frank Kelly, Global Head of Operational Product at Ipsos.

Find Frank Online:

LinkedIn

Website: www.ipsos.com/en


[00:01]

Hi, I’m Jamie Brazil, and you’re listening to the Happy Market Research podcast. This is a special episode connected to the Insights Association’s NEXT conference, which is being held in Chicago on June 13th and 14th.

My guest today is Frank Kelly, head of Innovation and NPD at Ipsos. Now, Frank, I do have a question. I have always said Ipsos. I think it’s pronounced “Ipso”, is that correct?

[00:27]

If you are French.

[00:29]

Okay.

[00:32]

For everybody else, “Ipsos” works fine.

[00:33]

Perfect. So Ipsos is a global market research and consulting firm headquartered in Paris. Founded in 1975, Ipsos is publicly traded and ranked in the world’s largest market research agencies, actually number three, I believe, with offices in 88 countries and employing over 16,000 people. Prior to joining Ipsos, Frank has held senior leadership roles at Nielsen, Greenfield Online, TNS and Lightspeed/GMI. Frank, thanks so much for joining me on the Happy Market Research podcast.

[01:01]

Ah, thank you very much.

[01:04]

You’re speaking at this year’s NEXT event on how to integrate voice in your total customer experience. My second episode on this particular podcast was centric to voice. I am so excited to see a conference, the first conference that I know of in our space, that is really kind of centralizing the communication around this particular medium. How did you first come to realize that voice was important?

[01:29]

If I go back maybe 8 or 10 years ago, when I started seeing people use voice to text, it dawned on me. As soon as people started using features like that, there’s this bound to be an application and research, because they’re just showing preference for a way to communicate. And we have to accommodate those preferences in the way that we capture data. But I guess the real big thing was certainly when Siri was introduced by Apple –I think it was 2011. That really seemed to show the promise of what you can do with voice communication. And it showed that with work eventually that could become a major component of how we collect research data.

[02:11]

Yes, for sure. You know, it’s interesting 2011. I think it’s September 2016 that Alexa launched. I think I have the year right. Does that sound right to you?

[02:22]

That sounds right. Yes.

[02:23]

So the big head start that Apple had inside of this space, and yet they certainly have taken a back seat from a growth perspective with Google Home now being the fastest growing voice-based platform. And obviously, Alexa. I think Alexa is still dominant.

[02:42]

Yes, well, again, a lot of people are using the Apple, the Siri on their other devices. So it’s not just the voice assistant devices that we should think about because research could be captured probably more commonly through the voice assistants on the phone.

[02:59]

Right. Yes, yes, for sure. I was talking to my kids. I have a bunch of kids, some older ones and some younger ones. So the younger ones are utilizing, and this is all just organic, Alexa right now to play hide and seek. It’s just really funny. Oh, Alexa, stop! Sorry. She’s now going to be called “A”. No, no, stop!

So the other side of it is, my older kids were talking about how it would be really cool if they could get an audio feed that highlighted stuff coming out of their Instagram account that they could then somehow magically connect right to their phones, to get in the visual pieces there as well. It is almost like a morning notification or update or what have you. So it’s funny how you think of them and “hide and go seek”, which is very much a tangible, visual-based game can be and has been created in a voice-only context. The other piece that I think is interesting… You mentioned Siri in 2011. I got my daughter an iPhone. She was 10 years old at the time, which I know it’s early, but don’t judge, and we’re driving, and I asked her: “Let’s talk about your best friends.” That sort of dad conversation, right? She said it was Hannah, another girl named Emma and Siri. She is actually pretty clever, my daughter. At least, I’d like to think so. But anyways, she actually told me in the car that, she was all in, that Siri was a real human being and just happens to be constantly available to answer questions that she has. And of the top people in her life, one was an AI.

[05:06]

Wow, that’s an interesting story. It is true, there’s people that are interacting with these devices constantly, many times during the day and they’ve customized the voice to their particular accent, to their gender, to their favorite sports player, whatever might be.

[05:28]

Right.

[05:29]

And it becomes a pretty indispensable component of their day-to-day life.

[05:33]

Yeah, for sure. And I think that as we pull back the user experience, and I’m not asserting your age on the podcast, but I didn’t grow up with social media by any stretch of the imagination. Libraries were the source of information for me, not the Internet growing up, and so my context is completely different from my kids. My teens, who have grown up with access to social media during pretty much their whole awake life. And then now my youngest ones, my two and three year old, who are interacting yet a whole different way with technology and access to entertainment and information. As leaders, we need to make sure that we have, that at the industry level we create the humility to understand that here’s a massive evolution that’s happening in these other two generations that we just don’t exactly connect with.

[06:27]

Yes, that concept came out a while back about the digital natives and so forth and much what we call the youngest generation because they are even more native. But it does also suggest that across the other generations, there are some that maybe are much less amenable to these technologies. And so it means that when we create research services, we have to really cater to quite a range of capabilities in the technology space.

In many cases we have to use multiple modes of data collection, which each have their challenges, and they may be well suited for a certain generation and not so well suited for another generation. So you have to have a secondary methodology that you have to try, and make the two methodologies fit together somehow in order to capture the representative data.

[07:24]

It’s kind of like an analogy: being we went from paper to Internet, this whole transition in market research. Obviously, there’s still some surveys that are paper-based but predominantly Internet is taking that space over. And then, later on, in 2006, the release of the iPhone smartphone. So now you’ve seen, from 2006 to 2010 again a migration. I think the majority of surveys now, over 50%, are taken on smart devices. Are you seeing voice is part of that narrative?

[07:57]

I could talk about several different waves of innovation, and how researchers have followed the adoption, which was curved from… I worked in postal. To go back to those era. I worked in postal and CATI and face-to-face. And so most of those have transitioned to the online world, and then with mobile coming in, moving from computers to other devices, tablets for a while as well. But they seemed to be phasing out, but now the majority of collection is now on mobile, indeed. And within these devices, such as with mobile, with new technologies being available to move to voice, this will be an equal challenge and an equal opportunity, shall we say, to capture data in a new way. And like the other challenges, we made some big mistakes. When we first moved to the online, everybody’s heard the story about you just took CATI surveys and telephone surveys, and adapted them to the online, but didn’t really make use of the unique characteristics available online to the extent we could have. And then the same story was really true, it took a very long time to rethink how our surveys could best fit in the mobile environment. And it’s really just getting to that point now. And I’d like to think that at some point we learned from all these lessons and say:  “All right, well, you know, there’s going to be a sizable portion of data collection in the future, which will be voice-based. And let’s plan for that. Let’s figure out how to leverage that new methodology to its fullest from the very beginning and not kind of drag our feet”, and so forth.

I am definitely seeing enough of these transitions to see that this is going to be a big one. And it’s going to be an important one that’s going to provide a lot of great opportunities. And ultimately, there are going to be companies that do a good job of figuring out how to work in that new space and how to leverage the new capabilities of voice for data collection and there will be others that don’t, and suffer as a result of it.

[10:15]

Yeah, gosh, your point about mobile is really interesting to me. I hadn’t actually considered that, but, 2006, it is about 13 years later, and what you just said is actually very accurate. Actually, I don’t even know if we, as an industry, have completely adopted it. We just fielded a survey that was not mobile compatible, hilariously enough, we helped to fulfill sample in a survey I should say, and we saw a massive dropout rate. We wondered: “Why in hell is the incidence so bad?” It turns out we checked it on our smartphones, and sure enough, we couldn’t take the survey on a smartphone.

[10:49]

There’s still probably about 25% of surveys that can’t be taken on a mobile device. Something like that. It’s still a problem, you know?

[11:03]

Yeah, only if you want representation.

[11:04]

Now, the problem is that the people that are only doing it on a computer are not necessarily representative because there are whole groups of people that almost never worked on a computer.

[11:15]

Ha! That is exactly right. Such a great point. You know, that’s another interesting point there too, and I know we’re a little bit off topic, but is Rogier Verhulst, Head of Insights for LinkedIn, told me the day of the email solicitations is dead, which he’s making more of a point, not like a state of truth. His point is that there’s entire working parts of the organization that literally don’t check e-mail anymore right. They are using Skype, or sorry, well they are using Skype, but they are also using Slack and other platforms.

[11:54]

Yes, Slack.

[11:55]

Exactly. Right. Exactly. So if you’re exclusively soliciting feedback through email, which worked great prior, then you may be missing access to a subset of the population.

[12:12]

Yeah, well, on that point, we see ourselves soliciting responses from respondents through at least a handful of different ways. This in-stream, which is sort of in social media or in-Linked stream there, where you are recruiting people in real time to a survey.  In reality, in augmented reality. And there’s quite a bit of this being done there in social media, in voice, as well as the typical email and other communications methods.

[12:52]

So what is the biggest challenge for market researchers to get consumer opinions in a voice context?

[12:57]

Well, I would say that we can’t underplay the technology challenge of the AI component. What we really need to have is a conversation with respondents and conversation between a computer and a person. And to do that, the computer has to understand what the person is saying and use that understanding to then ask further probing questions. It’s one thing to just say: “Okay, can we take these basic closed-end questions, and get a computer voice assistant to understand them?” And I’d say: “Yes, We are pretty well there on that part.” But that is back to the point earlier. That’s just taking mistakes of, using what worked online and trying it on the next mode when there’s an opportunity to do better than that, and that’s through really moving to a more conversational mode in the voice context. And to do that, you really have to be able to understand what people are saying. And I think there’s this great progress being made in this area, that you can train a database at a category level, you can take social media data, for example, and use that to train a research database, which is much smaller, not adequate for training a database on the terminology used and so forth. But we’re not really there yet for large scale conversations, shall we say. But that’s where the ultimate goal is to me. As we progress with AI and with the natural language processing, we’ll get better and better over time at being able to make sense of what people are telling us. And based on that, asking the right questions to follow up on that.

[14:14]

So in 2023 it is projected that about $80 billion dollar will be done on voice, which is obviously a material channel, for whether it’s Walmart or Amazon or whatever, Google, etc. And that’s around the corner, so to speak, when you’re 48 like I am, it feels like it is pretty close. Why do you think voice isn’t a bigger deal in context of insights right now?

[15:13]

Well, it is getting a lot of voice, a lot of mentions at the moment. It’s got even more buzz. And, like I say, augmented reality that I just mentioned earlier is probably an even bigger industry than voice is today. And yet it’s not that important in a research perspective. Part of it is that I think research companies are pretty good at adopting, and using new technologies, but we’re not that great at developing them. So we need other industries that come up with these new technologies to come around and come into our industry, and help us figure out how to best deploy those technologies. The big industries for voice are things like automotive, or security, or financial, or retail. They are the early movers. I think research is a bit smaller, and the technology companies will be focusing on research as an opportunity in the near future. But the challenge is here. Technology is a bit more too complex for most research technology companies to try and tackle and optimize for research purposes.

[16:25]

To your point, do you see that as more of a partnership opportunity for a company like Ipsos? Or is it a hybrid where you’re going to be developing your own suite of solutions?

[16:40]

Well, the industry tools are going to be pretty good. I don’t know that many research companies are going to be able to tackle, to partner with the likes of Apple and Google and such realistically. But they’re making good tools available to be used. We have already been doing stuff within Amazon and so forth where you could get a skill picked up by those applications so that you can get surveys in there. And we’re going to have at the NEXT conference some good demonstrations. Myself and my co-presenters will be showing several examples of real projects that we’ve run this way. I think there are tools that we can leverage. I think that they will be building blocks that people will build upon because again, we need wide availability of these tools within whether it’s Siri, or the Google voice Assistant, and so forth. We need these things technology to be deployed out there and then we just have to make use of it.

[17:50]

Yeah, right. The analogy being for me, if you look at whether it’s Facebook Ads that have A/B testing baked in or Google Analytics, obviously, which is to show you a nice point of view of what’s happening in your website or apps, one of the things that market research is doing a good job of right now at the brand level is tethering that data to state consumer opinion data, and then creating more context for the business insight. It sounds like what you’re saying is voice is going to follow a similar suit where you’ve got these building blocks, whether it’s AWS or what have you, that will empower the bulk of the platforms, and then specialty pieces whether it’s an injection of the lady whose name starts with “A”, who I don’t want to be in on the interview, she could follow up with the: “What do you think about that last purchase?” That sort of structure.

[18:57]

Yes. I would say that we don’t need to create everything from scratch. We just need these tools. Everybody has a mobile phone. Many people have voice assistants. We just need to leverage the technology that already exists within them. And then, we can layer on other technology. In the case of the voice assistant, you’re not getting actual voice, you are getting the transcription of the voice, but I think Video Analytics is on the rise. And I think that’s going to be a big type of voice data capture that will be very important to the industry. Because I do think that the sentiment, emotion and voice tonality and all those different things that you can layer on there can further help you understand your research participants. So I think that down the road, I could see us doing segmentations based on voice, based on what we teased out of a voice in terms of the personality types, and they would be equally as valid as an answer in a questionnaire.

[20:14]

I think you actually already answered this in a number of different ways, but I’m going to really try to kind of hone in on this practical point. What is one practical take-away that participants can get out of your talk at NEXT?

[20:29]

I’m sort of a field work expert, if you will, I have been doing it for a long time. And so what I tend to look at is… And I know that researchers are going to ask a lot of questions about representivity, and how you blend sample, how you adjust the data for different collection modes and those types of things. So I am going to try and at least get some initial answers to some of those researcher-type questions in addition to the use cases that we hope to have several, like I said, good use cases that will illustrate the best ways to leverage functionality.

One thing I didn’t really explain is that like in a diary situation, there is a lot of repetitiveness in the data collection. You don’t want to be asked the same question again, and again, and again. If you have a series of five questions, you need to answer in a diary several times a day every time you do something like the laundry or something, using the AI techniques you can just give an answer for all four questions at once. And the voice assistant will listen to it, think about it, and recognize that you have answered all the questions and just say: “Thank you”. So there are some practical uses like that, that do make the research experience better for the participants, and that’s really what we’re focusing on the near term.

[22:00]

Yeah, I think so. I’m really excited about the point you just made, which is we care about the respondent experience. Research is right now being done at a scale that is unprecedented. Even if you look back 3 years ago, it’s crazy, but even if you look back 10 years ago, or 20, it is mind boggling that we’re doing as many surveys as we are right now. Everybody is doing surveys, it feels like. I got my tires changed the other day. And guess what? The local tire shop, which is not like a national chain, sent me a follow-up NPS survey, which was hilarious. So they are really starting to care. Seeing market research as an extension of the brand is important. And so we need to be better stewards of the respondent. I go back to the eHarmony example. I don’t know if you are familiar with that product.

[23:00]

Yes, not directly but yes.

[23:01]

Right. Prior to when I got married I did use them, by the way, but it was.. it was arduous because it was right when they were relatively new, and it was about a 400 question survey. It was really, really tough, like a multi-day thing. And they were very early in the space. They were able to reduce it to a subset of open ends with just a few closed-end questions and then, from the open-ends did populate the 400 variables that they needed in order to optimize matches. So the interesting part there for me is that they did this in a text-based environment, early leaders in sentiment and such but now you think about a 30-minute survey, and it is really hard to do that. I would argue, nobody could actually do that, maybe 0.25%. But you could actually have a conversation and have that be meaningful and then ultimately populate the data set in a way that can be analyzed for researchers.

[24:11]

Yeah, that’s very much my point of view. I think about qualitative and quant. They are coming together, and I think it’s a good thing because quant people are good at listening. And quant people are really experts at asking questions. But they tend to ask questions with a set of closed-end responses. And what we really need is good questions with open-ended responses where people can say whatever they want, and people that say some things that if we find particularly interesting, maybe we go back and do a return to sample through a voice survey or some other method. It might make it tougher for Data Analytics because it’s less structure data but ultimately, again, it’s getting more towards a conversation, person to computer, where each conversation eventually becomes unique. That is driven by the participant, not by the researcher. That is when we really know we have come full circle from the original days of face-to-face and CATI where it was a conversation as well. But then we put a lot of technology in between and methodologies that, in some cases, made it easier and more efficient for us, but didn’t necessarily preserve the deep insights that we were trying to get. So ultimately, if we can find a way to do things fast and at scale with deep insights, then we have really succeeded. And I think voice is going to be one of those ways that is going to help us get there.

[25:40]

Oh my God. Yeah, for sure. I’ve been seeing this is a growing trend. I was just at IIeX in Austin. There’s a lot of qualitative technology companies that have been entering our world over the last couple of years and really, if you think about it, a survey is just a surrogate for a conversation, it just enables a conversation at scale. And the reason that we have closed-ended questions is because I’m lazy to analyze the data… Through AI what we’re able to do in the sense of analysis, etc., natural language processing, is really, for the first time, be able to have that conversation at scale so that we can get qualitative and quantitative or qualitative insights at quantitative numbers.

[26:26]

Yes. And so what you can do is when you ask that question, you can get a set of responses, and then you can do probing, you can teach the AI to know what to ask.

If they say this, then ask that. It gets smarter and smarter when you train the database at asking what is the next question to ask to get deep behind the meaning of what they have in mind when they answer a question a certain way. And that’s just very hard to do in a quant survey today with the typical survey technology.

[27:03]

So looking forward, not too far, but relatively near term, what do you think is next for voice powered surveys?

[27:14]

Well, let’s see. The real challenge is, of course, that surveys are too long. You really can’t do a 20-minute voice survey. It’s just not going to work. It really has to be more like 3 or 5 minute survey because people just don’t want to talk to the voice assistants in these long dialogues. So I do believe that there is more and more opportunities to break up those long surveys, and to look at them, like you were sort of suggesting, into pieces and ask different people different parts of the questions, infer some of the questions, and so forth. We have to be much more creative in how we approach surveys, asking people questions. Voice could be a very good component of that. But it has to be changed down to, using them for specific situations where you’re hoping to get their deep thinking involved, and then open it in that kind of environment to answer a tough question, not just something that is a simple tick box.  I think that there will be a place found for voice surveys very soon that’ll be just one of the tools in the box to capture research insights. And then over time, I think that we will just find more uses. But I think the initial uses will be returned to sample, like I mentioned, or diaries that every repetitive nature or very short surveys, which could go out for a very large portion of the population. And from that, you call out a smaller group that you want to do in more depth and maybe move them back to an online survey. So I think there’s going to be a lot more switch mode-type things and broken-up surveys into pieces, and a much wider range of interviewing techniques. Back to your IIeX example, certainly the tools around big qual have been coming out at a rapid pace over the last few years. There’s a lot of great stuff there to do more and more survey interviewing. And I think that we will be leveraging them in a voice environment fairly soon.

[29:47]

My guest today has been Frank Kelly, Head of Innovation and NPD at Ipsos. Frank, thanks so much for joining me on the Happy Market Research podcast.

[29:55]

Hey, thanks very much.

[29:56]

All of you, for more information on the Insights Association’s NEXT conference, again that’s June 13th and 14th of this year. Please visit http://happymr.com/next2019. That is http://happymr.com/next2019.  I hope to see there. Have a great rest of your day!

NEXT 2019 Pre-Conference Series – Ellen Kolstø – IBM

The 2019 NEXT pre-conference series is giving listeners an inside look into companies such as IBM, Voice Metrics, Ipsos, and Pulse Labs.. Join insight leaders on June 13 – 14 in Chicago for NEXT, where you can discover how technology and innovation are changing the market research industry. In this episode, Jamin Brazil interviews Ellen Kolstø, Design Principal at IBM.

Find Ellen Online:

LinkedIn

Website: www.ibm.com/us-en


[00:01]

Hi, I’m Jamie Brazil, and you’re listening to the Happy Market Research podcast. My guest today is Ellen Kolstø, Design Principle at IBM Q. International Business Machines Corporation, or IBM, is an American multinational information technology company that is headquartered in New York, with operations in over 170 countries. In 2016, IBM launched the IBM Q Experience, which is an online platform that gives the general public access to a set of IBM’s cloud based quantum computing. Ellen has hosted lectures at the University of Texas on design for artificial intelligence and has served in senior roles on both the agency and services side for companies including JWT, Young & Rubicam, Leo Burnett and BrainJuicer. Ellen, thanks for being on the Happy Market Research podcast today!

[00:49]

Happy to be here! Thank you.

[00:51]

Tell me a little bit about your background. This is kind of helpful for us because it level sets, and gives us a little bit of context of who you are.

[01:02]

Yeah, always a great question. So I started life in the agency environment as a strategic planner and so it came up through that world of account planning. I’d like to say it came over from the Mayflower, sometime in the 80s, from the British, and I grew up in that culture where it was very much about understanding customers and working with them and doing the research yourself so that you could translate that into creative strategy for communications. So I started in that world, and did that for quite a while. Then I felt that over time, the balance of the amount of research that was getting conducted shifted over to clients themselves, and they were taking on more of that in their own realms, and agencies were doing a little bit less of that. And so I found it very attractive to move into the realm of market research, where I could spend all my time conducting research, which is my favorite thing. And that is when I moved into that world and into BrainJuicer, now known as System1. I liked that environment as well because we did a lot of really innovative types of research using technology, so it combined these two worlds that I’ve been playing in, especially most recently. We did a lot of online ethnography and also online community. So you had a lot of tools to use and have consumers come with you for weeks and months in some cases as they work through different experiences with you, so that you could maximize products. And it was really fun, whether it was a long-term engagement, working with them on their relationship to cookies and unboxing experiences or how they selected their phone service and all that kind of fun that went along with that. So I did that for a few years, and then, I had this interesting opportunity where someone said: “Hey, IBM is looking for people with deeper search experience in what we call ‘user research and technology’”. Looking for that for Watson, specifically in the realm of AI, specifically they built up that team because Watson was new three years ago, it was just getting started, especially with the design team, and that is the group that creates the user interface and all of the tooling that our customers use to create AI themselves. I decided to go talk to them, and it was a really great experience. And I ended up there in a completely different realm: total technology, business to business, enterprise environment, but in a completely new and exciting space. And I was very energized by that. And that is how I ended up making my way to IBM through some of the other areas.

[03:45]

Where did you grow up as a kid?

[03:47]

I grew up in Houston, Texas, of all places. So I had actually spent my career moving around and worked in San Francisco and Chicago and Boston, and all these other places. Then I decided to come back to Texas and work in Austin at an agency, and came back to my roots here. And I really love Texas because it’s an amalgamation of a lot of things in this one giant state. You’ve got big corporations. You’ve got rural areas. You’ve got tech corridors and Austin, agencies in Dallas. So it’s just a lot offered here, but yes, I grew up in Texas and decided to come back to the Wild West, if you will.

[04:30]

So I did some digging and preparation for this episode. In 2015, on LinkedIn, you published a long form blog titled “Customers as Mentors”. And you opened with what is probably one of the best quotes I’ve ever heard, and I’ve never heard before, which is pretty unusual. And that was: “The purpose of business is to create a customer who creates customers.” And I thought:  “That is exactly right!” So I know you recently spoke in Austin at IIeX, and then you’re going to be speaking at the NEXT conference coming up in Chicago on June 12th and 13th. What are some of your favorite examples of how AI is helping us better create customer advocates?

[05:14]

Well, that’s an interesting question, and part of my point in that blog was that it’s really great when companies or good companies start to look at their own customers as potential mentors for new customers as in you’ve got all these customers you have a relationship with who’ve been through the journey of adopting your product, especially in categories where those products where there can be a lot of work to adopting them —and technology being a space very much like that. So if you pair them up with brand new customers, and get them started together, and wouldn’t that be a great thing to do? And I think some companies have looked into that, but I think it’s still right for growth. So it’s interesting that when you bring AI into that because AI obviously as a machine has a different perspective. It’s a human-generated perspective because we make these machines right now. But the rule that I think AI can play in that it’s almost becoming that mentor itself because you’re seeing that in a lot of the spaces where AI comes in the chat bot space for the conversational system space where let’s say, it’s midnight, and for whatever reason, you decided to download that new piece of software, and you’re not sure how to do it. And you need help. That’s the time when you may turn to a machine, and AI can help you get through that process, go through that journey of downloading that software correctly. So it ends up creating machine mentors where what I was talking about were human mentors. But you end up having these machine mentors, and they can be as useful and helpful because they’re available 24/7. They ideally, if it’s done well, know the questions you’re going to ask. That doesn’t always happen right now, but it is the vision. The vision is to be able to get the help when you need it, how you need it.

[07:04]

I know you’re going to be a little bit biased here, but who do you see in the space leveraging AI for driving customer experience particularly well?

[07:14]

Well, that’s a great question. I am biased, and it’s some of the folks that we’ve worked with, I will say —I was using that example of downloading software, I would say Autodesk, which is the company that makes AutoCAD and all of that software that helps architects and a lot of people that are doing a lot of rendering. They have a very advanced system that allows you to do a lot of things and get a lot of answers directly through that system. And they have worked long and hard to get a system that’s very thoughtful, that’s very focused on the key questions that customers need and is able to really help them. Now, it’s a different focus in market research. In many cases, we are not always looking at AI right now as being a direct interface to us. It’s more than, it’s a tool to help us in active analytics or insights in your engines to understand a lot of large scale data if you’re a market researcher. At this point, we are not using bots to field for us. Ha! Maybe somebody is. Maybe somebody is trying, but I think we still want to be the one asking the questions. Obviously, you could argue that surveys are an automated form of that, but it’s a different type of research data collection. But at this point, I think AI is in the realm of being a tool in market research, and I would say that it is definitely the best place for it to be right now.

[8:39]

I have spent about maybe a third of my career doing qual and the balance quant. Research is really just a conversation at scale. You don’t need to do research when we only have one customer because you’re talking to that customer, hopefully. But as soon as you are IBM, then we have got a lot of customers, and we can’t actually understand the customer sentiment or put the customer in the center of the conversation unless we actually conduct research and facilitate that conversation. What’s interesting about AI to me is, and you probably saw this at IIeX, that there’s a lot more companies that are entering into market research that are leveraging AI for qual, which is allowing bigger base sizes to be done and historically possible. And when you think about my career, this is way in the 90s, late 90s, mid 90s, we would do things like collages. You have probably these kinds of projects.

[09:41]

Yes!

[09:42]

And then, we would basically try to put together the respondent collages in a master collage, which is really funny if you knew my art. I never got a repeat customer on that one. I don’t think I delighted customers there. My point is that we were able to actually conduct these kinds of exercises, and then the machine put them together. The AI put them together in a way that is actually meaningful and connects to the audience. Are you seeing that sort of application in market research looking forward? Is that one of the growth areas?

[10:15]

Well, it is. It’s funny that the presentation I made at IIeX was actually around caution with AI.

[10:25]

Oh, interesting!

[10:26]

Understanding where the models are at this stage of the game is not to say that, as I said, you can’t use them or have them be a part of products and services; that can be very helpful. But I’ve spent the last three years watching our customers build AI in their own systems, and seeing the tremendous amount of work it takes to build a really solid, stable model that is reliable, that is as balanced as possible. I mean, bias is what it is, so it’s going to exist but you can get as close as you can. It’s a tremendous amount of effort and work. It’s not something you stand up quickly. It also requires, in some cases, hundreds of thousands to millions of data points for something to be really reliable. Think about if you start as a child and you don’t really know the difference between a cupcake and your dog. You’re not really familiar as a little kid but you start to see that thing over and over and over and over, all these elements, and that’s how you learn. AI is the same way. So you can’t expect after, in some cases, five times an image comes up that AI can correctly identify every time that it’s a Porsche. There are so many elements to a Porsche to get it right, from the shape of it to the texture to the colors to the different elements that are on the vehicle to the logo. It’s got to pick apart all those things, put it back together and identify that as a Porsche. And that’s kind of the value or the promise of neural networks, right? But it takes a lot of work for a model to get that right. And so I was illuminating at that conference, under the hood, how the sausage is made, which is what I will be doing partly at NEXT too just to arm market researchers with an understanding that I think the smart move right now is to use AI but use it with caution, and double check what you’re getting! Don’t expect that it’s a black box that magically spits out the right answer, or that its first passive data is going to be better than what you could do. It may not be, and it takes a while for it to learn from other people, to run enough times, to get things right. And we are at the point where you just have to make sure that your own human intelligence is a part of the mix. It’s not magic. It is very much augmented intelligence, which is what we like to say at IBM. It’s going to add to what you’re doing, but it’s not at this stage going to replace you or what you are able to do.

[12:57]

Yes, I just had a conversation yesterday with Aggie Kush, the Head of Insights he had a lot of titles, he was the Head of Insights for BSkyB. He finished his PhD talking about machine learning. One of the things that he identified going through his thesis, and I think was actually core to it, is that AI in and of itself can reinforce biases that we have, maybe even a gender bias, because it’s recognizing these patterns and then basically playing of the pattern recognition so gone unfettered, it actually could not have the outcome, whether it is social or otherwise, that we might want, meaning that we really got to pay attention to the models and the actual implications of the of what the machines are telling us.

[13:55]

Yes, you play in right into an example I gave at that presentation, which was a study that was done in 2015 around Google Search. Google Search is a great example of AI in use and with a large trained model. All of us when we do search or training that model, right? And this isn’t a dig on Google because, in fact, the way this worked out made perfect sense with what you’re saying. But within their search, university looked to see that whenever someone searched on CEO, they focused on this one instance. When you searched on CEO in 2015, 27% of the CEOs globally were female. But yet when you searched on CEO and Google, female CEOs only came up 11% of the time, which would tell you: “Oh, hey, my model is biased”. Now, Google rightfully came back and said: “Hey, this is based on what people are putting out, whether it is ads, whether it is articles, whatever images they are using, that’s where this is pulling from.” And the university came back, I believe it was Washington University, that came back and said: “Well, that may be true, but we also believe that whatever people are clicking on is training your model.” So if only 11% of the time are clicking on female images, then the model things that that’s the amount of time people want to see female CEO images. And it will continue to under-represent. So it’s exactly the point you made. And it is unintentional bias because that’s the other thing I’ve heard a lot of discussion around: this idea that machines will be able to be unbiased because they’re machines, and they will avoid the unconscious bias that humans have. Well, no, actually, humans are part of the training process. And so that unconscious bias was absolutely present in that example. Nobody was consciously, I believe, trying to say: “I’m going to search every time until it changes its model.” No, it just happened to be that that’s the way it went. And now you have got bias in that model. And that is the other reason I say to always double check what kind of models companies are working with because how much work are they doing to troubleshoot these kind of issues? Are they really looking back at their models and saying: “Oh, we know the types of people that are using our software, whatever we are offering that has AI in it, and we’re going to go back and double check and see how that’s augmenting our model.” Because AI models are never done. You don’t create one and walk away. You are constantly working on it and seeing how it changes because it’s a very constantly changing amorphous thing. So that is where I get on my soapbox about. How do you use it? I still believe it has tremendous promise, and it will always have tremendous promise. But you want to make sure and use your own intelligence in all of this as well. And don’t underestimate your own intuition at certain points.

[16:46]

Do you think there’s some overlap? Because we moved away from the institutional tracker. I mean, not like whole sale, but it’s become a smaller and smaller piece of the corporate budget. You know what I’m talking about, right? The quarter million dollar or million dollar…

[17:01]

Okay. Yes, I worked for a lot of them.

[17:04]

Yes. So those are going away, but at the same time, as to what you’re talking about, I have never heard it cast exactly like that. But these machine learning AI systems are in a lot of ways uncovering the direction of the consumer, which is really one of the big intends of measurement from the trackers. Do you think there is an analogy there?

[17:30]

Potentially? Depending on how people are interacting with AI in the tracker and who is answering the questions, I think there will always be an opportunity to double check what you are getting back as a result of that. Different from a survey, without AI in it, where there is an answer, you click on it and it’s done, AI is always training and because it’s always training, yes, things can change. And so you are just going to want to know how that might change. So, sure, it’s certainly something to keep an eye on for sure.

[18:08]

I think it’s a bad idea now that I hear you answer that question. Okay, so how can modern insight pros use AI?

[18:13]

With caution. Ha! I say that because, again, I believe there’s a lot of value. Like I said, where I get most excited in market research is with Predictive Analytics. I think there’s just a tremendous amount of opportunity. We always struggled with market media modeling. We are always trying to model things to understand what people were going to be doing. And we never had a really great way to at least get an idea of where people were headed. And predictive analytics, especially where AI can aggregate a ton of data, look across many things and start to make connections, will be invaluable. And I think we will get a much more accurate understanding of what could be happening if we were to run certain media mixes, what do we think the outcomes could be. I think that that’s where it’s got a tremendous amount of promise, and I’d be very excited to see how that moves forward.

[19:12]

Yes, I did a fair amount of modeling in my early career. The way that I was taught to do it, which is to say, there’s lots of ways to do it, is you find it, you asked a question in your survey, which is something like “probability of purchasing a TV”, and then that level sets against actual TV purchases over that period of time and so it gives you a baseline. And then you ask another question similar to that but about a new product that your customers are interested in measuring and then, perform a regression. And then all of a sudden you’ve got that or a Van Westendorp or some other kind of methodology that is leverage in order to come up with the predictive… well, Van Westendorp is a little bit different. My broader point is do you see marketing research as a discipline starting to use and leverage AI in order to do these market predictive models versus the traditional, old school stats point of view?

[20:17]

I would say it is probably being more valuable in that space, for sure. We worked on so many regression models, and I still couldn’t tell you if I really knew if any of that was going to play out. It was hard. There is a famous quote… Oh, gosh, I’m not going to get this right. Something about “I know half my advertising works. I just don’t know which half.”

[20:53]

And then we categorize that half we don’t know under branding.

[20:55]

Right! Exactly! And it’s never going to be a completely exact science. I think predicting behaviors is very hard. But statistically, it still was not quite enough of an indicator of what was really happening out there. AI has the ability to look at a lot of things and because it can also look at unstructured data, you have this unique opportunity where it could look across more than just the statistics. Now, it can look across conversations and different things that can be fed into the whole pie and tried to get a better understanding of what could potentially happen. That’s where AI’s promise has always been and that it has now so much more data to draw from to try and find these answers to very complicated questions.

[21:46]

AI is part of the tool kit, right? And let’s say that you’re entering into the insights role inside of an organization, marketing research or some other some other way. Well, actually, let’s focus on market research, what skills do you think the person should be cultivating in order to successfully drive inside of the firm, basically informing the executive level business decisions?

[22:14]

Yes. There’s a lot of different things. So the first one that came to mind because it is the one that I constantly run up against is flexibility. You have to be willing to roll with what comes along, not only with all of the changing technology and the different things that come up, but it can be very difficult to leave sometimes your opinions at the door and say: “OK, well, let me look at this a little bit differently”. Insights? When you get to the executive level too, they need to be pretty battle tested, right? You want to make sure that you feel pretty good about them, which means you have to at some point vet them in various different ways to know that you have something collectively that you feel is going to stand the test of time, especially the enterprise, where big, big, big decisions get made, right? And so you have to be flexible, the tools you use in the kind of data you’re looking at. You have to be willing to look across a whole bunch of different types of data, trying different methods. I don’t think you can do “plug and play” anymore. I mean, I think I i’s back to your point about all of those longitudinal studies, and all these tracking studies of “there was one way to do it”. You did that every time and you reported that number at the end of the year. And now, there’s so much innovation and change. I think staying on top of it is challenging. But I think also being willing to be flexible and reinvent at various times is going to be a really important skill set.

I am also going to go back to, and this feeds into flexibility a bit, creativity, which is also super important. And it’s a funny thing because I think what really helps that is to be able to draw from things that aren’t all related to what you’re doing or even in some cases, your domain, right? It’s looking out what completely different companies or different competitors are doing or even people completely outside of the industry that you are in, and trying to see how you can maybe utilize some of those elements in what you are doing to try and come up with new ways to think about things. Every industry is getting so incredibly competitive, certainly saturated with a lot of known insights. Getting something new and different is just requiring a whole other level of flexibility and creativity and inventiveness that you are just constantly having to hone, and it’s not easy to do because you’ll get in myopic into your workflow and then go: “When was the last time I even read anything on a new technique in this area?”, but it’s something to keep in mind.

[24:48]

This is such an interesting point to me. When I started my career, it used be the case that it was adequate to conduct a consumer survey and then analyze, PowerPoint, and then story-tell, right? But it was all in the context of that study. Now it feels like that’s wildly inadequate, right? You need to really hone in on providing the context, market, business, social, whatever, of that particular insight because the context informs so much of the implication of the data. And so one of the things that I’m seeing more and more in research reports is that maybe 25% is spent on both the setup, the context, and the implications at the business level. So it’s almost like we’re moving a little bit broader, and then also going deeper with the insights.

[25:45]

Wow! It’s so funny that you mentioned that because context is a big, big thing with me. I completely agree. It is telling stories, and it’s telling stories with the details where you can really start to see what’s happening. And I think in on the side of technology, especially with usability, there has been a tendency towards scores and just very almost quant-like representation of the learning. And I have pushed to put a lot more context even around that kind of thing. Just because somebody is navigating through a website does not mean there is not a lot of interesting things, especially if you are sitting there watching them, that can tell you about their thought process or why on that day, they ended up in certain parts of the experience. And that is where it gets interesting. It’s also true that your insights are better remembered with context. Without context, they are “somebody wants that”. But when you can go back and replay a story to somebody else about the context of why they want it, it gets institutionalized, it gets internalized, it gets retold and it’s that whole fireside chat kind of phenomenon. I’m a big believer in context. I would almost say that the context is 90% of it. And I completely agree with your point.

[27:11]

What I described is actually incorporating a lot more data really into the narrative that you build out. But the master, storyteller, they’re doing that. But now they’re actually the content on the slides, and the actual story that they tell is re-tellable. So it’s actually a hell of a lot less content that winds up getting displayed, and the story is profoundly simplified to its core essence. So it’s really interesting; it’s a much harder job today than it was before, I think. It is one of the reasons we have to leverage any tools that we can in order to help us.

[27:43]

Yes, and that’s where again unstructured data comes in, right? It is all of that kind of conversation. It’s interesting how AI will be able to help us with that. I think insights engines will get a lot better, and they will start to be able to serve up that context in ways that we can’t possibly get through all that data, and that will be super exciting when that happens, and that all of that context is that we want to hang on to.

[28:16]

Yes, insights and context, that would be interesting business to start, I think.

[28:17]

No kidding! That would be great, right?

[28:23]

I think I am doing about 1,000 interviews, and I’ve said the story before on the show. So I apologize to the listeners about the redundancy, but it’s rare. It’s worth mentioning. I did a quant study, relatively short, and then at the end, I asked: “Please do me a favor, and take a 15-second video or some period of time video of your environment”. And one lady, I’ll never forget it, took a video of a number of kids where they were running around like chickens with their heads cut off, as my mother would say. And I was thinking to myself: “All of a sudden it drew everything into question about the insights that she was providing in that survey for me.” You know what I mean? It feels like… totally. That was really important, the context of her providing that insight, which in that case was potentially moving a multimillion dollar ad buy. So it seems like maybe they’d want to know that? I don’t know. Anyway.

[29:21]

Absolutely! I did mobile ethnography, like I mentioned in BrainJuicer, where we had customers videoing various things, unboxing experiences, as I mentioned, in all sorts of things. And you saw the context there of their world. Right? There was one really funny when I was doing on a cookie that was being introduced. The husband was more excited about the cookie than the wife. And the wife was the one in the study, and he kept creeping into the video and taking it, and she eventually had to hide the box from him. But it was an interesting dynamic that you want to say. And the cookie was targeted to women, as they can be because it had a certain dietary benefit. But it was like “Who cares? See, this guy loves it.” So, yes, there’s so many stories that could be told by being in that environment, obviously the power of ethnography and the power of storytelling.

[30:13]

Yeah, which links to where you started, that is, the power of AI because it’s so hard to do that at scale.

[30:24]

Yes. It is hard to do that, yes. Yeah, it is the promise of it, and it will get there for sure, and it will change everything. I still firmly believe that even as it starts to be able to go through a lot more of that data and comb through it and give insights, I think humans are still going to be very, very much in the mix with it in terms of building off of it. You know how you probably collaborated with another researcher before, and you have kind of rift off each other to come up with the ultimate viewpoint on something or the ultimate insight. I believe that is how the relationship will move forward with AI.

[31:03]

Oh, I completely agree. This whole fear around AI removing jobs in the least, in the next 50 years, maybe 50 years, but not in 20 years, at least not from my vantage point, it’s all about partnership. I liked your augmented intelligence point of view.

[31:18]

Yeah, I agree. I just don’t see that happening.

[31:24]

So on a future look, how are we going to be different as an industry in five years?

[31:29]

Oh man. Well, let me get my AI together, and I will tell you. Ha! Where’s my predictive analytics? I will give you one viewpoint I’ve been thinking a lot about. And this is because I am in technology now and more so, in this space. But I think your UX research and market research are going to morph because I am already seeing in the realm of usability and user experience, all of that research, a lot of researchers in that space saying: “God, we need to understand more about the market. We need to do more up-front qual”. And then, when I was at IIeX, they had several sessions on usability, which was pretty funny, because some of us from the team went to that conference and they said: “Wow, they introduced usability like it was a new technique.”  I think it’s pushing into the realm of market research to say: “Hey, nothing is stopping you from wanting to dig deeper into the online experiences of your customers even though you might be at the brand level, right?” So I think we’re going to see all of this come together as one big realm of customer research, and I think it should because customers will engage with you all over the place. And why wouldn’t you have one researcher, a team of researchers looking across all of it, from the market to the online experiences to everything else in a meaningful way that doesn’t separate out user experience from market research.

[32:59]

We have addressed this next question, but I’m gonna ask it anyway, just to see: If you were going to create a company today servicing the industry, the insights industry specifically, what problem would you address?

[33:13]

Yeah, I like your context one a lot. So this is what I’ve been thinking about for a while, and I don’t know if it’s controversial or not, but it’s this whole idea of “is bias really a bad thing?” The reason I say that is that in research we are constantly saying you can’t be biased, we got to be unbiased, and we all know that’s impossible. You want an unbiased sample, and this and the other will. The panel probably already has biased from a million different angles right that you have drawn from. We know as humans, bias is inherent, certainly there is bias you absolutely want to be careful of, anything that harms anyone. But in some cases, bias is to be learned from. And if it exists, how might we learn from it and gain insights from the bias itself rather than treat it is something we just should either ignore or pretend, we have maximized it out of the equation. So for a business to understand how we can work with bias rather than avoid or against it, I think could be really interesting to figure out. Even with that Google example, there’s more going on there, with how people are clicking on those CEO images. What is it? Is it purely gender bias? Are there other things at play? What can be learned to unpack some of those elements that will help us better understand the role of bias? I would also argue, in some cases, bias is not any different from having a hypothesis. Having a hypothesis means I have a point of view on something without all the data. And I am biased in a certain direction because I think this might be what is going to happen. And then I will go into a study with that hypothesis, and I will obviously look to see that plays out. But we all know you are looking more for that particular other things because that is where your mindset is. It’s not a bad thing. It is something we all do. But how might we think about how to reframe the use of bias in a way that we can learn from it, that we can improve the outcomes and treat it as something that is a part of the mix, not something that we just should avoid.

[35:19]

Yes, it would be fun from a start perspective, it would be really fun, and it’s useful to think about… You are familiar with Myers-Briggs, of course, or whatever personality profile thing?

[35:29]

Yes, yes.

[35:30]

So, like, for Jamin Brazil, what biases do I have in my life that I probably honestly just don’t know about, that are just a function of culture and context?

[35:48]

Absolutely. Yeah.

[35:49]

That would be a really interesting… I don’t know how we would do that, but it that does seem like something AI could address.

[35:53]

That would be a great Myers-Briggs. You are right. Because then that’s something you would know going into any future work. Okay, this is a mindset I’m coming in with, and now what do I do to either to mitigate it or to in some ways celebrate it. Because it’s a funny thing too: I was reading a Harvard Business Review article recently that talked about how employees get reviews, and so many times, reviews are a negative experience because it focuses a lot on your weakness. “You should be doing this.” “You should be doing more of that” instead of “Okay, let’s celebrate what you are good at and find other things for you to do that celebrate this thing that you are good at.” So it’s kind of that same idea. How could you take what might seem like a negative and say: “Well, there may be ways in which this could be extremely helpful with certain studies”, “Having this viewpoint could really make me the best researcher for this type of research” as opposed to “Oh, you are biased in a certain direction, and now you’re not good for certain things.”

[36;54]

Yes, totally. It is such an interesting point of view. I can pick on my grandfather here, my late grandfather so, I will tread lightly. But my point is that he grew up in a World War II generation. And there was just a completely incorrect set of biases that were ingrained there, not in a positive way. I am not saying he was part of some terrible group or anything like that, but it was just different, really different. He didn’t fit into a millennial culture, how is that? And yet, with no malicious intent or anything along those lines, it was just the framework that he understood and agree in incorrectly. So the opportunity for him to get informed on that, to hear: “Hey, these are the things that you know you have inherent biases” because you can often find see them in other people, but they don’t really not be able to see them themselves. And that’s the point. It’s hard to see the blind spots in ourselves. Something like that could be really interesting.

[37:59]

Absolutely!

[38:00]

Sorry about this. I totally went away with the conversation.

[38:04]

No, what is interesting about your grandfather, too, is that, who knows? His perspective might be getting smaller and smaller and smaller as millennials grow. So that maybe a perspective that’s also interesting to understand or potentially having a certain study, where there is another angle to things, you know what I mean?

[38:24]

Totally. Out of micro level in and a man macro level, start seeing how that plays out. That’s so interesting. All right, my last question: What is your personal motto?

[38:32]

Ha! I guess the one that comes closest to encapsulating me is: “Always be prepared.”

I learned that a long time ago for my father, who approached everything with a lot of preparation, thoughtfulness. He had he had a plan for everything, and it really served me well of just having some level of preparation is, I think, sometimes 90% of the job, 90% of the battle, whether you’re reading secondary research ahead of a study or you are just getting smart about an industry or you are having a conversation with some stakeholders. Before you get started with something, you have got a good jumping off point that means you are not just going in shooting from the hip in many cases. I’m someone who likes to have a level of preparation. So it’s ironic because in some ways AI is very much about that. Building models is very much about a tremendous amount of preparation going into any kind of work that you are then going to do with it. But yes, that’s my thing. I like to be prepared.

[39:37]

I love that. I got to end on two stories to that point: A good friend of mine, Jennifer Crawford, she took a bet on me when we were at Decipher in the early days. She is the owner of a New York-based research company called Research Solutions. And I remember I co-pitched with her to Meredith about an online diary, something you’re really familiar with, and in that pitch she came in with a folder that was about 0.25-inch thick of preparation. There was a bunch of stuff in it about the meeting. And so we left after 45 minutes. I don’t know if we actually opened it. Maybe we got through two or three pages in the binder, or the folder. And this is the only time I have ever heard a customer say: “I want to thank you so much for being so well prepared for this meeting.” And we won the business. It was a windfall for both of us, the firms. It was spectacular. Anyway, sorry about my reminiscing. But preparation, as it turns out, I think it’s really important. Oh, and the second one I want to mention is Voss Media. Voss Media, which is a big company, is inundated with papers about states of industries, etc. And they actually subscribed to an AI-based system, which does the processing so that they can reduce all this vats of information into a quarry string and pull out the pieces that are relevant and say that they have 99% coverage on their content. So anyway, yeah, I like the preparation point. Thanks so much for sharing that.

My guest today has been Ellen Kolstø. Sorry about that hick-up. Ellen Kolstø, Design Principle at IBM Q. Thank you, Ellen, for joining me on the Happy Market Research podcast today.

[41:20]

Thank you. It was lovely being here.

[41:22]

Everyone else, this is in conjunction with the upcoming NEXT conference. You have a couple weeks still to register. You can find out information online, of course, at https://happymr.com/next2019 as well as Google Next, and it is located in Chicago, on June 12th and 13th, I believe. It is going to be a wonderful event. I hope to see you there as always. I love your screenshots, feedback. Share this. It’s appreciated. Have a great rest of your day.

Ep. 218 – NEXT 2019 Pre-Conference Series – Dylan Zwick – Pulse Labs

The 2019 NEXT pre-conference series is giving listeners an inside look into companies such as IBM, Voice Metrics, Ipsos, and Pulse Labs.. Join insight leaders on June 13 – 14 in Chicago for NEXT, where you can discover how technology and innovation are changing the market research industry. In this episode, Jamin Brazil interviews Dylan Zwick, Chief Product Officer at Pulse Labs.

Find Dylan Online:

LinkedIn

Website: www.pulselabs.ai


[00:01]

Hi, I’m Jamie Brazil, and you’re listening to the Happy Market Research podcast. This is a special episode that’s connected to the Insights Association’s NEXT conference in Chicago, that is, this June 13th and 14th. My guest today is Dylan Zwick. Dylan. I said your last name, right?

[00:22]

That was correct. Yeah, Dylan Zwick. I’m always dead last in the alphabetical order.

[00:27]

That’s funny. I was always first in photos because I am 5’8’’ so we have that objective position. Dylan is the co-founder and Chief Product Officer of Pulse Labs. Pulse Labs is a solution that enables users to launch and gather consumer opinions via voice devices such as Alexa and Google Home. Dylan, thanks for being on the Happy Market Research podcast today!

[00:49]

A pleasure to be here. Thank you so much for having me.

[00:53]

You are speaking at this year’s NEXT event on voice. When did you first realize that voice was important?

[00:57]

So I first realized that voice was going to be big back in 2016 when I bought my first Echo. So I started playing around with Alexa, and realized that what had been the dream of science fiction now for decades, you know, the ability to speak and actually have a conversation with a computer was actually becoming science fact, you know, it was it was becoming reality. And so, I played around with building my own Alexa applications and started exploring the tools that were out there for developers and designers for Alexa application, and for voice applications more generally, and realized that this was going to be a huge space and also that I really wanted to be a part of it. So that’s what got me initially involved.

[01:54]

Yeah, I mean, Alexa in and of itself is really interesting. One of the things that I think is… If you pull back, YouTube right now, I forget what the data is, something like 60% of the Internet is there. It’s a massive amount. And if you look at the bet that Google placed when they did that acquisition, it was, they consolidated the different product lines into a single thing, and then they centralized the KPI to one centralized point of focus, which was the number of daily videos unloaded. And that created so much focus from an R&D perspective that that was all anybody cared about. It wasn’t predicated on revenue or eyeballs or anything like that. That was it. And then subsequently, of course, that was the tail that wagged the dog. Amazon is actually doing the exact same thing with respect to Alexa. I mean, my kids… My 12-year-old can create an Alexa skill. It is crazy easy how they have made the development side of this accessible.

[02:52]

Yeah, that’s been a huge focus for Amazon. And the Alexa team is to open up as many tools for developing essentially applications or, as they call them, skills, on Alexa and then, trying to provide these and encourage as many independent developers to build skills there as they can. So you have a ton of skills, actually, that have just been built by independent developers, and then also a bunch of skills that have been built by brands or professional agencies. And there are even companies out there that are focused exclusively on the building of Alexa skills. And then yeah, you’ve mentioned, you know, they’re also very interested in providing tools that makes this as easy as possible. So you even have a blueprint tool that essentially lets you quickly create a standard but personalized skill without the need to have any programming background at all. And I focused on Alexa and what I just said but Google is also pursuing a similar strategy, and that you can also build applications on Google’s Assistant. They’re called actions, and they’re really trying to build out, and expand, and encourage that ecosystem as well. So all the major voice players and, to be honest, Bixby and Cortana are also very interested in that. So all the major voice players are really trying to provide a platform for as many content creators to participate on as they can.

[04:30]

So the Bixby thing was interesting, right? They launched… I think it was last year. It was Samsung’s voice device. And Cortana. It is interesting to me that Cortana and Siri haven’t had a more dominant role in voice so far, especially considering the head-start that Siri had. Do think that developers are going to need, or should I say, brands are going to need to deploy across all of the major players? Or is it… I may even roll it back a little bit further. I don’t know how old you are, but I was in the Silicon Valley during the whole rise of the dot-com, and there were probably 12 searching engines.

[05:13]

I remember.

[05:14]

…like Infoseek and Go.com. You had this… exactly! So you had to really pay attention if you wanted to get visibility on the Web in terms of where, what the users… do you think ultimately it is going to be one ring to rule them all?

[05:29]

So right now, it’s certainly a duopoly. So right now, most of the market share there is being taken by Amazon and Google. And so if you are a brand and you are building an application for voice, most of the time you’re going to want to… Brands are interested in actually just building on both of the platforms, and it tends to be pretty easy to port applications built on one from the other. Once you’ve built, for example, a Google action or Alexa skill, translating that over to the other platform —as I said, it’s not trivial, is a whole bunch easier than building a new one from scratch. So because of the market share that both of the major smart speaker players have, most brands when they build a voice application are interested in building on both – and it’s becoming easier to port that so it’s becoming less expensive to do both, kind of at the same time, so most are interested in doing that.

In terms of the other voice assistants, that is, Cortana, Siri and Bixby, they’re all making interesting plays, but they are mostly not competing directly with Amazon and Google on the smart speaker market. So Cortana is actually positioning themselves as much more of an enterprise voice offering. So the idea would be that Cortana would be kind of your voice assistant in the office and sort of the business aspect of voices system. And then, Bixby has an offering that is very tied to your phone, to your Samsung products, though, so it’s really tied to what people are doing on their smartphones. But yeah, I would say that we will see how the future shakes out in terms of who is going to be dominant. I don’t think it will be one single player, but I also don’t think it will be five or six.

[7:42]

That sounds like your framework is really centered around use cases and the context of the interaction. So I have my Samsung TV, of course, and similarly, I have got my Alexa sitting there, but it’s actually funny. So I got Bixby on my Samsung TV that I set up. But I still use Alexa on my Samsung TV. From an interaction perspective, it is kind of funny.

(Oh, sorry, Alexa, stop!)

[08:10]

Ha! I’ve had that happen many times. So yeah, that’s really what you’re getting at is the fundamental goal. The reason that these major huge tech companies are so interested and invested in those platforms is not because they really want to dominate the speaker module. But it’s not because that the clock radio market was so important to them that they’re just going to go in there and crush that. What they really want to do is they view voice assistants as being the operating system of the Internet of Things. So you’re not just going to be talking to your smart speaker, or even just to your phone, but also to your car, to your television, as you brought up, to your refrigerator… I mean, you’re going to be talking to all of these different electronic appliances, and it’s going to be ubiquitous and the primary means, or at least one of the primary means of interaction, will be via voice. So that is essentially the big dream there. Whether it’s going to be something that’s dominated by one particular company, or whether there’s going to be maybe just some underlying framework that isn’t owned by anybody but that everybody kind of builds on, and that maybe you’ll be able to access Alexa or Google Assistant or whatever voice assistant you want, from any of these touch points, will be interesting to watch as it develops.

[09:49]

I mean, what I’m finding so fascinating is the way that we interact with voice. Alexa, for example, has skills, and I forgot what you said, Google Home’s reference was.

[10:05]

Actions.

[10:06]

Actions, right. So it’s a very much of a human interaction, that is, it is that part of the UX experience. So I could see a scenario where you could successfully address Cortana, and to your point, in a business context, and then, similarly, I could use Bixby for maybe my refrigerator or my appliances or what have you. And then maybe at a personal level, I just want to go ahead and interact with the lady whose name I won’t say. That is really interesting.

And I love how you started out talking about the science fact because being a geek and Star Wars nerd, and Star Trek fan, the way that both of those environments projected the future, it turns out that Star Trek was right with this voice AI always being part of you.

[11:01]

Yeah, and sort of as a side note there, Jeff Bezos is famously a Trekkie, so Jeff Bezos is actually famously a big Star Trek fan. And the Star Trek or Enterprise computer was actually part of the inspiration for Alexa. So it may not be entirely coincidental that they seem to be similar. From what I understand, the Star Trek computer is actually part of the inspiration behind Alexa.

[11:36]

Oh, that’s so interesting! All right. So you’ve worked with several firms, many firms, including today’s top firms, on voice application. What has been the most exciting aspect of that? And then also, what do you see as one of the larger challenges in this early stage?

[11:51]

Yeah, absolutely. So the most exciting thing about it is that voice has the potential to be, essentially, the lowest friction form of interaction between a person and a computer, and also the most essentially natural and intuitive one. Speaking conversation is something that we learn and understand almost innately. There are parts of the human brain that are just specifically wired to communicate this way, and so voice interface is something that, if done right, is going to be the most intuitive and easiest type of interface that anybody is going to be able to use. And you have actually seen that with the… I remember six or seven years ago, a friend of mine’s young child walked up to a television and started touching it, and the television did not respond. And the child thought that the television was broken because he had become so used to touch interfaces. And even before touch, we’re seeing kids that are talking to their smart speakers. And so it’s going to be expected that any sort of technology that you interact with, you’re going to be able to talk with. And if you can’t, it’s going to seem broken. But the big promise there is that, as I said, it’s a super low friction way of interacting with technology, and it also is a form of interaction that can take place when you were otherwise occupied. And so a couple of examples: the big one that’s been so successful right now are things like requesting music to be played, just saying “A word”: “play Despacito”. Or asking for the weather or any of those kind of quick functions that you want to do every day and that can be made really easy and low friction. But what I think you’re going to see is most of the audio consumption is increasing rapidly. People are listening to music and podcasts and radio broadcast or radio shows more and more on digital devices. An so the ability to kind of interact with what you’re listening to via voice is extremely promising because usually when you are listening, you are doing something else. So if you are a marketer, and let’s say that you have an audio advertisement that’s playing on Spotify or podcasts or something like that, the ability to just say —if you want to know more about this, say: “Alexa, tell me more”. And have that instantly send you an email that will tell you more about what was being advertised, and then take you right back to what you were listening to, I think it has enormous potential and power.

Another scenario, another context is driving. So if you are driving, you are in an inherently hands-free situation, your hands should be occupied, so not hands-free because your hands should be occupied. And so it is an inherently audio scenario in which you are able to, for example, order food on your way home for pick up from a drive through via voice in your car, I think has enormous potential to kind of transform a lot of those flows.

What challenges there are today? I would say the biggest challenges are discoverability. It can be hard to really know what is currently there and available, and to remember what skills you want to invoke to do what. So that has been an issue. And then there are other scenarios, other interactions that I think to be the best way to input information, but are not necessarily the best way to get information back. So if I asked for a list of the 10 most popular movies from last year via voice is probably the easiest way to request that information, but then having something come back and say: “The most popular movie was X. The second most popular movie was Y”, etc., might not be the best way to get that information back. So something like a list might make more sense as a visual response. And I think that the combination of voice and audio with visual, so opening voice up as one medium through which you can communicate, is opening up a lot of new possibilities. I think that multimodal is going to be a major part of the voice applications in the ways that we use voice over the next few years.

[17:02]

Yes, for sure. And I think from a researcher’s point of view, thinking about the opportunity for ethnography to be done even though you do not have the video component tethered to it, but always on a feedback option is really, really powerful. If you are thinking about CPG-type or products, whether they are software or service or whatever, that we interact with or real things, then you can always provide feedback as long as you have that particular device handy.

[17:34]

Exactly, and so…

[17:35]

And you could do that, to your point, before while multitasking. So you have the new Alexa Auto that is a really interesting —I think they’re doing a limited release right now. So it’s the in-car version of the Dot, or whatever, Echo. So the closer that you can provide feedback to the actual experience, the better the data, the less the time degradation of the insight.

[18:07]

Exactly.

[18:08]

And right. If you think about being in the shower, and Head & Shoulders wants to do a new product test, and I’ve got my device inside of the bathroom, I can actually provide feedback on that experience while I am in the shower, where before that was just always impossible. You could never garnish that kind of information.

[18:26]

Exactly. So something like the ability to quickly provide, like a net promoter score or rating and then some quick feedback or data about a particular experience can be done very low friction via voice. You could have something like, on your Head & Shoulders bottle or something like that that said: “To provide feedback or rating, just say this particular thing to Alexa and then answer two questions”, which is something that I think people would be much more likely to do than say: “Go on a website and fill that out.” Or if you have the ability to say yes to the bottom of their seat. Say you can use Alexa to provide this feedback, and then we can maybe even send you an email coupon or something like that.

And then you mentioned CPG. Another big, exciting possibility here is that CPG most of the time people purchase is replenishment and reordering. Traditionally, packaging has been mostly geared towards standing out and convincing the consumer to make a particular purchase while that purchase is available on the shelf, and competing with other similar products. However, with this huge shift that we are seeing into purchasing online, I think packaging might even be somewhat rethought as a way of convincing consumers not necessary to make a purchase but to reorder. And the ability to say, for example, let’s say that you’ve got a roll of paper towels, and when you’re done with the paper towel roll on the actual cardboard roll itself, it says: “To reorder this, just say Alexa XYZ”. And it could be just a quick two-turn interaction or something like that, and you would have a replenishment of what you just finished on its way. I think that has enormous potential for tons of consumer packaged goods.

[20:30]

Oh my gosh, totally. I have never heard that example before. Thank you for sharing it. That literally blew my mind. This is going to be the headline quote by the way of the episode because one of my big challenges in moving to a voice consumer journey is that it’s an invisible journey. So the opportunity for a brand like Scott to intercept the point of purchase is quite literally zero. It’s all about my brand affinity, which at the end of the day, paper towels are paper towels for me; maybe not for other people but I don’t particularly care as long as it does what I want it to do. And so, if you can get that brand into the speaker, paper towel ring thing or whatever, now all of a sudden you do have an opportunity to create that connection with the consumer.

[21:20]

Exactly.

[21:24]

And this is what’s interesting: you could actually spawn the transaction because it’s a voice-based trigger

[21:31]

You could just say it right there at the moment where they are thinking: “OK, I need to reorder”. You could just be instantly there, and it’s the simplest transaction it could be. It’s basically just this thing that I have, that I’m out of, I want to re-order replacement of exactly this thing. “To do that, say exactly this”. And it will happen.

[21:55]

I think we should scrap everything we’re working on. And that is the direction…

[22:01]

Ha! This is what I thought at the end of 2016. I thought: “All right. I got to scrap what I’m working on and pursue voice.” Because exactly, it’s things like this that got me and continue to get me super excited about it.

[22:18]

So, for our listeners, www.pulselabs.ai is Pulse Labs’ website, and if you’re going to go visit there, there’s really two paths. One is on the consumer side, the customer side, that is, somebody that may want to leverage the platform to gather consumer opinions through voice. And the other is to actually sign up as a panelist to provide feedback. So I want to talk a little bit about your platform. What type of insights are being captured in your voice surveys?

[22:48]

So right now, primarily, we have been focused actually on testing usability testing, mostly for designers and developers, skills and applications. So if you are building an Alexa skill or Google action, and you want to get a gauge on how usable it is, whether people are understanding it, whether one particular approach makes more sense than another, you can use our platform to quickly and easily test with real world users. And we are able to do all of our testing directly on devices. So you can test any Alexa-enabled device. We used to do the test on any Google Assistant-enabled device, and we provide a level of data on those interactions that is exactly unavailable anywhere else in the market today. So it is designed essentially… if you’re building something on voice to get real user feedback and really deep, detailed feedback on exactly how people are using your application, Pulse Labs provides a platform and a panel for providing and gathering that feedback.

[23:57]

So I have not come across a business exactly like yours in our space. Did you do any pivots? Was your start different from where you are right now?

[24:07]

We have not done any. Small pivots? Absolutely. Changes in approaches or changes in focus? I would say absolutely. Major pivots in what our product offering is and what our vision is? No. So our vision from the very beginning has been to provide user research to your real world, real people… user research to anybody (brands, developers, designers, agencies), basically anybody who wants a presence on voice, and wants to understand how real people are using voice, and how real people are interacting with voice, and how they can effectively build their presence there.

[24:59]

In 2023, $80 billion dollars is the projected number that will be spent on voice devices in a voice consumer journey context. What do you think research will look like at that point in time as we see such a migration of the consumers’ expense moved to that environment?

[25:17]

I think that research is going to be based around “How do you make this as easy as possible for the users?”, “How do you make it as convenient as possible?”, so they have easy access whenever and wherever they needed. But also, if you are a brand, “How do you remain top of mind here?” Do essentially, how do you be the orient, and how do you set yourself up so that if a customer just wants to order paper towels or something like that, it’s your paper towels that they are ordering. And that is part of the big play for the voice platforms: they want to have some control and say over who gets that top position. With Google AdWords, it’s always a fight to be on the first page. With voice, it is going to be a fight to be the top, the number one, the one that is recommended, and the one that is provided. There is going to be a lot of research, a lot of understanding devoted to how to make yourself number one, and then how much number one is worth.

[26:31]

Yes, that’s really interesting, especially in the context of how many generic brands are now owned by Amazon and Google. This speaks to the overall importance of ensuring that you are “the Kleenex” of your brand category.

[26:44]

Yes, exactly, exactly.

[26:48]

All right, so the NEXT conference is coming up. You are going to be talking about voice. What is one practical take-away? I know that you are tilting your cards here, but what is one practical take-away that our listeners can gleam from your upcoming talk?

[27:01]

So the practical take-away will would be if you are a marketer or a brand and you want to build something on voice, what you want to do, what you want to focus on are one or two very key use cases that voice can do better than what is currently available right now, that are valuable to you, and then execute on those. Too often, we tend to see either brands think: “Okay, we’re going experiment with this. Let’s put together some application”, and it might be either frequently asked questions application, or maybe they’ll just say: “Let’s take the API that we have, that feeds all of our product line for our website and just connect it to Alexa.” Usually those approaches don’t work so well.

So the important thing is to think of things like what we just talked about, such as the ability to reorder paper towels at the point when you’re done using your current batch, and make that seamless and easy. Those are the sort of approaches that are most successful, and that we will see the best ROI.

[28:19]

Yes, that’s great. I think that the application of Kmart in Australia —I heard this through the Voicebot podcast, which I’m sure you’re listening to, and I’m going to try to distill the information a bit – they were talking about how they actually had a tremendous success. I guess there’s some legislation around not being able to procure a product through voice yet. But the ways that Kmart became dominant in a voice framework is that they provided proximity to the actual product. So if the consumer wants to buy something, they would say: “Is it in stock?”, or “Where is it near me?” and that is how they would get directed specifically to the store. So it is an interesting story for me in that they started talking about how the brand is empowering the consumer and getting close to them, adding the value. Another one, I think it is Chrysler, that has an automatic start feature on one of their automobiles. It’s actually one of the top 100 Alexa’s skills. So it could be cold outside, and you can just tell your voice device: “Hey, start my car.” And it will start. It’ll warm up the car for you before you before you get in. The more the brands start adopting this technology, and the better they’re going to be positioned when this action stuff actually scales.

[29:42]

Yes, exactly. Exactly.

[29:46]

Well, I can’t wait to hear your talk. My guest today has been Dylan Zwick, co-founder and Chief Product Officer of Pulse Labs. Thanks so much for being on the Happy Market Research podcast, Dylan.

[29:57]

Thank you very much for having me. It’s been a pleasure. Thank you. Thanks a lot.

[30:02]

For all of you who are listening, if you’re not signed up for the Insights Association’s NEXT conference, I would highly recommend you do that. Again, that is June 13th and 14th in Chicago. You can also find out information on our website https://happymr.com/next2019. I’ll be including links to Dylan’s information and his company’s information in the show notes. I really hope to see you at the NEXT conference. Have a wonderful rest of your day!

Ep. 217 – Amit Dhand – Online Surveys vs. New Methods

My guest today is Amit Ahand, Co-Founder and CEO of Nailbiter. Founded in 2014, Nailbiter is a unique platform that offers CPG manufacturers an opportunity to see their consumers make purchase decisions at the shelf and at home. Prior to starting Nailbiter, Amit has been a key executive at IRI, Catalina and Affinnova.

Find Amit Online:

LinkedIn

Website: www.nail-biter.com

Find Us Online: 

Social Media: @happymrxp

LinkedIn

This Episode’s Sponsor:

Today’s podcast is sponsored by Schlesinger Quantitative, your trusted provider of global online surveys that drive the best decisions for success in the marketplace. Schlesinger Quantitative has built an entire division of experts with extensive online research experience and an unparalleled understanding of quality drivers across panel, sample, and data.


[00:00]

On Episode 217, I’m interviewing Amit Dhand, founder and EVP of Client Services at Nailbiter, but first a word from our sponsor.

[00:01]  

Today’s podcast is sponsored by Schlesinger Quantitative, your trusted provider of global online surveys that drive the best decisions for success in the marketplace.  Schlesinger Quantitative has built an entire division of experts with extensive online research experience and an unparalleled understanding of quality drivers across panel, sample, and data.

[00:35]  

Hi, I’m Jamin Brazil.  You’re listening to the Happy Market Research Podcast.  My guest today is Amit Dhand, co-founder and CEO of Nailbiter.  Founded in 2014, Nailbiter’s unique platform that offers CPG manufacturers an opportunity to see their consumers, make purchase decisions at the shelf and at home.  Prior to starting Nailbiter, Amit has been a key executive at IRI, Catalina, and Affinnova. Amit, thanks very much for joining me the Happy Market Podcast today.

[01:07]

It’s my pleasure, Jamin, and I appreciate you doing this podcast.  I think this is very overdue in the market research business. And I look forward to the conversation; I look forward to tracking your broadcast in the future.   

[01:22]

Awesome, thanks very much.  So, I’d like to start with a little bit of your background.  Can you tell us where you grew up and a little bit about your parents and how that’s impacted where you are today?

[01:33]   

That’s a great question because I ask that question in job interviews all the time.  I grew up in India and did my undergraduate degree there. I grew up in a small- business family is the best way to describe it.  My dad, many of my mother’s siblings, they were small business owners, traders. This was in India of a different era, which was much more socialistic, much more repressive, if you will, from both a society standpoint as well as business standpoint.  So, I always saw my dad struggle, make ends meet, do well, and then get pleasure out of being an entrepreneur, I think, and also the trials and tribulations that go with it. But the one advice that he gave me consistently was to never be like him. Educate myself as much as I could and get a job in a nice, big company and be comfortable.

So that’s what I did, but I did pursue my passion, which was physics.  I didn’t do the engineering track, which is common in India if you have grades that’s what you do or medicine.  I was doing my masters in physics, and that’s when professor politely pulled me aside and said I didn’t have that much of a future in physics [He laughs.] because I didn’t have the temperament to a professor or a researcher.  Strangely, now I’m a market researcher. So, that was my journey to looking for something new. And my sister was getting her masters in the U.S. at the time. So, I was looking for what’s next. For a lot of kids in India back then was the U.S.  So I came to the U.S. for my MBA.

[03:16]

In what year was that?

[03:17]  

That was in ’96.

[03:20]

Got it, got it.

[03:21]

A different millennium.          

[03:22]

So, I just have to ask.  I’ve been to India just a few times.  Did you grow up near or around Mumbai?

[03:28]

I was in Mumbai, yes.  I grew up in Mumbai.

[03:31]

Yes, that’s been my sole sort of anchor point to India.  As you know, Neilsen is based out of that location. And then quite a few different support companies for Neilsen located there.  Anyway, it’s a really interesting… Obviously, I don’t have the… more of a recent set of experiences. But, on the other side, I don’t have the historical point of view, but it is a very different culture.  But I would say it does mirror a lot of what I have experienced in other parts of Asia.

[04:04]  

Yeah, it’s an ancient culture.  I think India strikes a really good balance between an ancient culture that is modernizing, I believe, the right way.  A lot of people go to India and look at what doesn’t work, and a lot doesn’t work, and we’re used to complaining about that.  But if you think about how many millions of people have been lifted out of poverty in the last 30 years, it was unimaginable, right?  And with some degree of freedom or high degree of freedom and democracy while making that happen. So it hasn’t been a small feat. But next time you go to India, go attend a wedding.  That’s a whole different experience.

[04:45]

So, that’s actually (funny you bring that up).  That is on my bucket list of things to do is experience that.  I have had quite a few… So, at Decipher we would sponsor H1B’s.  I’ve had a lot of very good employees who I’m actually still friends with, who I was able to recruit from overseas, India, of course, being one of the main areas.  Fantastic engineering talent as you already said. But, interestingly enough, the overshadowing characteristic of the talent that we were able to procure was customer service.  There was one particular employee, Anthony, and he would get regular, unsolicited feedback from his customers directly to me, the CEO, saying, “I just love this guy. He’s so amazing.”  Just picking on him, but there’s quite a few. There’s more than a handful who have followed suit. Anyway, I want to dig in a little bit with your father’s perspective. As an entrepreneur, you’ve probably heard the Elon Musk quote:  “Being an entrepreneur is like chewing glass and staring in the abyss.” Sounds like that would have resonated with your father. Why did you decide to bunk the better life at the corporate level? I’ll call it the easy road even though we know it’s not as easy as all that and decide to branch out and start a company.              

[06:13]

Yeah, you know, I’ve asked myself that question many times; my dad’s asked me that question hundreds of times.  He can’t believe that’s how I ended up. Let me complete the journey real quick and then this will make sense, right?  I gave up physics, came here, got my MBA from Virginia Tech. And back then – this is pre-email and internet days – so you applied by mail.  And I had a cousin, who went there for chemical engineering, and he introduced me to a professor. I got a scholarship to go study there, which is rare for an MBA coming directly from India.  So I took it. It was an interesting exposure to the U.S. culture. And graduated MBA in marketing and got into market research. And we can talk separately about that. But, having spent some time in CPG market research more specifically, I had two sorts of burning questions.  One was the field seemed extremely rigid and archaic, right? And we used to think physics was rigid and archaic. Nothing changes in physics until it changes and then it all changes in a week. But market research has been rigid and archaic ever since and has stayed that way. So I think part of me becoming an entrepreneur has been the motivation to bring change into the business because, as someone who has exposed to other ways of doing things, other disciplines in research as well as technology, I feel like there is so much marketers could be gaining from the data that they’re spending billions of dollars that they’re just wasting, right?  So, that was one desire. The other desire was to be responsible for my own destiny.

So, I actually wasn’t an executive at IRI.  I started as an analyst, moved my way up, and then I wanted to be a sales guy, which everyone found super strange.  I was a statistician when I began there, but then I was dying to be in sales, and not just sales but commission-driven sales because I wanted this degree of destiny.  If I do well, then I do really well; otherwise, you kind of go down in flames. And I liked that; I liked that challenge. I feel like entrepreneurs are self-motivated in sort of a negative way.  What I have seen is that entrepreneurs work on great challenges, or they don’t work at all. And I’m guilt of the same: I get called out by people on my team that, if I’m working on a project that’s not strategic and not big and not interesting, then I miss all deadlines.  But, if I’m working on solving a problem that’s pretty important to the company or to our client and it kind of seems very complex and difficult, then I’ll be at it for a week without food or sleep. That I can do. So I feel like a lot of entrepreneurs are very intrinsically driven.

I was intrinsically driven; I think my dad was because if you look at compensation, which a lot of people look at.  When you’re successful, it’s very easy to see the house and the car and all those things and a lot of people look at that.  But most entrepreneurs, myself included, these are by-products that we enjoy today that we didn’t seek, right? So the idea was to do something different, to be recognized for doing something different.  So I would not think that entrepreneurs and Elon’s the biggest example of someone who’s not shy, who craves the recognition; so, I can’t say I don’t. But, fundamentally, drive change and not rest on your laurels; you’re always looking for the next problem to solve.  So it is an interesting sort of mindset. What’s happened today is entrepreneurship has become easy. It is not my father’s world where… By the way, all his business was in cash because they had a 90% income tax rate, 90%. Imagine that.

[10:37]

I can’t.   

[10:38]

….which meant you really couldn’t do official business.  Everything was done in cash. And on payday, he used to go to the office with two huge suitcases of cash, and one time he got mugged.  And he lost one suitcase; he had to go borrow another suitcase for the cash.

[10:56]

Wow.

[10:56]   

So it was an extremely difficult environment:  you had to bribe your way through everything; he was in manufacturing; so, it was also a physically dirty environment to be in.  None of that is true for the entrepreneurship that I practice. I think the one fundamental difference between him and me is that he never trusted anyone.  He was quite successful; so, I’m not knocking anything he did. But his whole thing was trust no one and, you know, you’re an island as an entrepreneur. And I don’t buy that.  Thankfully, I got some genes from my mother also, who trusts everyone, and I trust everyone. And my operating principle – and I think that’s easier to do in the U.S. than some other markets – is trust people ‘til they give a reason not to trust them and you surround yourself with people who generally are trustworthy, loyal, smart, intelligent, better than you in most things.  And, surprisingly, you will do well.

[11:57]

I think this overriding principle of karma, if you want to call it that, is exactly right.  Framed, as you’ve already said, in our modern society, which is (in North America anyway) certainly easier than it was 20, 30, 40, 50 years ago.  We have the luxury of being able to trust or maybe we’re just more willing to take those risks because we have less… We’re not worried about food anymore, which is something that my father was worried about, growing up.  And so, this freedom, if you want to call it that, that we have as entrepreneurs to be able to step out and solve the big problems, as you said, is exactly the point. It isn’t about the monetary outcome although clearly that’s great when it happens, but the motivator is 100% centric to working with people, solving this big problem, and then bringing about an effective change inside of an industry.  And I want to just rewind just a little bit. Market research from your vantage point, using your words, rigid, archaic – why did you feel that was the fertile soil. How did you get introduced effectively into it as “This is where I’m going to make my bed”? for Nailbiter.

[13:16]      

So, market research is a space I learned really well from the inside out and, more specifically, CPG market research.  And Affinnova was a company that had been in business for many years that then CEO was my mentor had pretty much taken over, acquired, invested in and decided to make it more of a data company than kind of a design optimization engine that it was.  And he brought me on board in 2006 and together we made some strategic decisions. And one of them was to be in market research because it was an entirely new tool; it was evolutionary algorithms applied towards market research. And it flourished; it did really well.   Now, it was extremely hard to convince big CPG clients to start using us. It took us many, many years (eight, nine years) eventually to make the company what it became. It was a top 20 MR firm when Neilsen purchased it in 2014. So, I was one of the handful of people who worked day and night to make it happen, to take it from a couple of million in revenue to 40+ million global operations.  So I really saw what entrepreneurship means in this space from the inside out so that when the Neilsen acquisition went through, a few of us had a couple of bucks to spare. Now, the rational decision would be to invest your money and… It wasn’t enough money for us to retire, but it certainly was enough money that we could take it easy. But I decided to go for broke, and we invested (when I say “we,” it’s several of us, myself being the principal investor) in doing something new, and I wanted to stay in a space that I know well.  So market research is data; data is the pursuit of something empirical, which I really like. I like that answers are finite; they’re definite. So, there’s a lot of aspects to this business I like. I’ve always enjoyed the people in market research. No matter where you go: you could be in China; you could be in India; you could be in France; you could be in Latam (Brazil, Argentina). I’ve been everywhere and always found like some degrees of uniformity: They’re slightly nerdy but more marketing-driven than maybe people who are in the pure sciences.  A really nice combination of intelligent, intellectual people who are pursuing answers. Broadly, that’s the space I wanted to stay in. Another thing that I learned over the decades is that CPG is a recession-proof business; so, if you’re going to do something risky you might as well pick clients that are more stable although this is probably the least stable time to be in CPG. But I enjoyed that I had built a reputation along with my co-founder and some of the other people in CPG. So that is the place that we decided to pursue. And then we tried a lot of different things before we landed on video.  So, I’ll pause there ‘cause I was going off on a tangent anyway.

[16:32]

That’s fine, perfect.  So, CPG is recession-proof.  I love that framing. I feel like the space has been proven to be ripe, right, for disruption when you think about the Amazon effect inside of CPG’s.  I’ve talked about this on a few different podcasts and I’ll probably talk about it on a few more: and that is the impact of voice is going to make, is making rather, on the user purchase journey, especially in the CPG space.  Purina’s stat something like in the next three years, they’re projecting 50% of their product will be purchased in a voice environment through Google Home, Alexa, etc. I personally and my wife are starting to acquire products through, you know household goods, through Alexa.  And in that purchase journey, what’s really interesting is just going through the exercise, you wind up buying things differently. The only intercept is what Alexa decides to put in front of me. Are you seeing that as part of the instability in the CPG space or is it other factors that are driving it?      

[17:48]

So, we come at it from two ways:  One is the consumer dynamic that you referenced is very true.  I do think that voice is a little bit more further away than a lot of people think.  I think VR was considered something that’s around the corner five years ago. A lot of interesting companies in context; a few others sprout up but VR didn’t quite happen largely because of some hardware issues.  I think similar problems are going to exist with voice, but eventually these technologies will take over. Now, what’s interesting with voice though and video and VR is they are perfectly placed and already available as great market research tools.  So, they may not be good enough to conduct all sorts of marketing transactions or sales transactions on; they’re very, very robust for market research. And one of the things that we keep educating the industry, and I was just invited to speak at ESOMAR…  We’re kind of begging the industry to take video quant, which we are doing. We do very little qual. Everything we do is very, very robust sample sizes. We’re not doing very ethnography. Our whole idea is capture a transaction; don’t worry so much about getting into the head of the consumer.  Make an effort towards behavioral but let it be robust; let it be truly projectable; let it be something that CPG can make multi-billion-dollar decisions on. And that’s that data we are driving to create and are successfully creating all through voice and video. Five years from now, it could be that all your social interaction with friends and the internet at large is audio-video.  And that happens to me: Our main office is in Virginia. I drive down for four hours once or twice a month, and the whole drive down there, I don’t have to touch my phone. Voice activation, even with my accent, works nearly perfectly. I can type emails; I can text; I can use all sorts of things in that type of interaction. Why would someone want to type? And, if they can’t type, how can they do online surveys?  So, the survey companies, everybody has to make sort of these giant leaps forwards into an entirely new interaction with the consumer in the shop or… And that’s where I feel audio and voice and video and all of these will move faster than they will as sort of a broader e-commerce platform. The problem with voice is the margins: it’s very expensive and going to remain very expensive for that case of Diet Coke to be shipped to my house.  So, it might work for some pet foods or the premium end but, if you think about 70% to 80% of pet food being more towards the middle or lower end, the price point of going to Walmart and picking up those 50-pound bags at a really good coupon, that value is not going to be beat for a very long time to come. So you will see the very high end and we’re seeing the top 1%, 2%, 3% people disproportionately move their dollars because convenience is more important to them but, for middle America, CPG’s sort of bread-and-butter, we think that these other systems are like about a decade away.            

[21:14]

So AR, VR, there’s obvious hardware issues.  Nobody is going to walk around with those crazy headsets and whatnot.  Even snap glasses are highly iffy according to my children. I personally like them, but they tell me, “They’re not cool, Dad.”  The voice, though, as a platform… Consumer preference, as we both know, always wins. So then the question becomes, as you’ve already articulated, when.  My theory, which is completely based on no data, is that it’s going to be half the time of e-commerce, right? So, when you think about like 1996, I love your framing of “We did mail back then.”  I did mail back then. In fact, all my surveys were CATI and in-mall intercepts. That’s basically telephone interviews for those of you who don’t know. And so, then moving that online officially with Decipher in April 2000, that was a big transition.  It’s taken a long time for commerce to move online, and still the majority of commerce isn’t there. So, still got a long tail associated with that transition. Obviously, it’s picking up steam with Walmart’s investment in home delivery, etc. Kind of the Uber of, just pick whatever category is taking over…  I think you’re right from a practical perspective; this is not something that’s going to happen in a short period of time. So, if it was 20 years for the internet or 15 years for the internet, it seems to make sense to me. But, conversely, on the other side of it, when you think about with voice, you’ve got (what is it?) 40 million Alexa units in North America last year.  

[23:00]

That’s amazing.

[23:01]

Yeah, it’s crazy the adoption that’s happened on that front.  Now that we’ve got the, as they call it in the retail, the 13th month coming up this weekend (Black Friday and Cyber Monday) in a few days, we’ll see what those sales pop out at that point, but anyway.  It’s going to be interesting to watch. So, I want to talk a little bit more, dig in a little bit more on your company Nailbiter. The first question I have (Man, I have done tons of market research; in fact, right now I’m doing market research for a couple different companies) but Nailbiter – that is every project it feels like, right?  And I can’t believe I never made the connection to business. I’m a little bit jealous. How did you guys come up with the name Nailbiter?

[23:51]

So, I would love to take credit for it, but it actually came up in one of our early meetings.  We sold one of our early projects to Ricola. We went in for the results meeting, and I think it was the General Manager or the senior person in the meeting that said, “Alright, let’s get going.  I’ve been biting my nails to see what’s going on.” And they had a very specific Costco issue that they had tried a lot of different ways to do research and they couldn’t figure out because the issue was very subtle.  I mean it was a big issue for them, but it was very subtle for the consumer, too subtle to survey anybody to ask them about it. It was about the size of the bag and the location and how things get dragged out and things like that.  Up until then, we were called Motions Research, which was a typically boring market research name. So, coming out of that meeting, I was with my colleague; I said, “You know what? Nailbiter is a lot better than Motions Research.” And it stuck from day 1.  And you’ve been in market research long enough to know that the people you have to be most memorable to are the ad men, right?

[25:00]  

100%.  That is exactly, exactly, exactly right.  Insights Nation, this is the key point. This is going to be the title of this episode for sure.  

[25:13]  

And it stuck.  Every meeting I used to go to, the ad men would say, “I’ve been waiting to meet you.  I wanted to see who you are and what this is about.” And then they would remember me; they would remember us.  We would call them the next time; it would make the whole process of getting in the door a lot easier.

[25:31]

Totally, man, totally.  So, tell us who is the ideal customer for Nailbiter.  

[25:39]  

Heavily focused on consumer goods, consumer packaged goods, FMCG for the rest of the world for a couple of specific reasons.  So, I’m not someone who is going to badmouth online surveys. Online surveys played a very important role. In fact, in 1998, when I was first starting in market research, I really liked the idea of online surveys.  You guys came up in 2000; you were the pioneers then because a lot of people still didn’t believe that this thing would be a thing. But online surveys have become like a crutch for everything. You have a question: let’s go ask 1000 consumers ‘cause it’s so cheap.  And we’ve noticed that more and more the industry has been doing that. The industry that suffers the most in using online surveys in these ways is CPG because CPG has some unique problems. One of them is recall. I don’t know what toothbrush I use and I’m in the business of toothbrushes, Colgate’s customer.  And suddenly, I wouldn’t know what I paid for it even though I do most of the grocery shopping in my household. So, for me to do a 20-minute survey on toothbrushes when I don’t know so many things about my decision – no matter how good the model at the back end is that crunching the data – the inputs may not be as good.  So, we felt that if we had a more behavioral way of capturing the actual transaction, let’s apply it to CPG and that thesis has really paid off. So ideal clients are any industry that wants to hear from the consumer, wants to see the consumer, wants more global quantitative behavioral information but is not being well served by surveys because while we are quant, no one can touch the scale of surveys today for the price that surveys are.  So that’s where we feel we have the greatest bang for our buck and, indeed, we’re able to side by side show data that just coming out of our system is a lot more actionable because you don’t have to ask any questions. The system just records the transaction and then decodes it; so, it’s open-ended yet much more insightful, if you will.

[28:07]

Alright, so then, describe to us what the actual product is from Nailbiter.  Let’s pick on Purina. I’m an executive of Purina. What is the delivery?

[28:20]

Sure.  So, actually, Purina has been a client, but everything I’m about to say is not from any of their projects, but think that you are launching a new product.  And you have invested millions of dollars in concept testing, developing it, R&D. You really believe in the concept. You’ve spent a lot money optimizing the packaging, and then you have 20, 30 million dollars invested in TV after the product hits the shelves.  So, this major, major investment is about to hit the market and, by the way, at a smaller level, you’re doing this every month. At a big level, you’re doing it a few times a year. So, CPG company’s job is to innovate and stay ahead of competition and private label; so, they constantly have to come up with things that are new:  new marketing, new products. Now, that product goes on shelf; a lot of in-store marketing is happening. What you’re getting in the early days is some distribution data; you are getting sales data. None of that data has any insight. So the insight has to wait til maybe the Catalina or Neilsen, IRI tracking systems that are more household level take off.  Or you could do some mystery shopping and shop-alongs and things like that. In our system, because again we are watching people make shopping decisions, we can see what percentage of stores are carrying the product; we can see what percentage of shoppers have seen the product, have touched the product, have picked it up, have carted, or put it back. And then, people also speak sometimes; sometimes they don’t, but if they say something like, “Well, I don’t get it” or “That’s too expensive.”  Whatever it is, their few words per shopper, across 500 shoppers, you can come back to that executive (and we’ve done this at most of our clients in days and weeks) and say, “Your product is having a real challenge because the packaging is black; the pack on the left of it is black; the pack on the right of it is black. So, when we did our pack testing online, it popped because everything was white, but the shelf has changed or the retailer has planogrammed it differently from what they promised you.  No one is even seeing it. Or they’re seeing it but they don’t get it that this is a premium, organic product because you have the simple packaging and all the claims are on the back. And a 20-pound bag of dog food is not something that one lifts to see the back or maybe they do. So, all of that gets captured; it gets turned into very tangible data and measures that they can make effective decisions on very, very quickly. So that’s sort of the power of bringing something new to the table but then having it be actionable so that output of it is not just, “Hey, that’s cool insight.  So let’s do another project with this video company next year” versus like this is an always-on-system that you’re making decision on every week.

[31:33]   

Are you leveraging AI or some other math to do the insights at scale or is it just human beings just crunching?   

[31:42]

So, it goes in three levels:  The first is automation. There is a small degree of AI in the way the video is processed, but I don’t want to overplay the AI piece either.  

[31:57]  

You’re the only one, by the way.  Everybody else overplays the hell out of AI.  I’m sorry. It’s just a max-diff. Anyway, go ahead.

[32:04]

Correct.  Hey, I’m drowning in AI, VR and all the acronyms, but our original thesis was that 100% of the video could be processed programmatically.  And it was true when the video quality was very pure. So, we had also thought that we would create some sort of Google Glass kind of a panel:  high-res images coming and high-res video coming in, but none of that could scale. Thankfully, Google Glass we didn’t use because they stopped making it.  But we wanted scale, and scale comes through people’s mobile phones, and that’s what we use. So, we have two technology platforms: One can recruit people just-in-time and convince them to make a quick video of their transaction for a little bit of a reward.  (Don’t want to give too much reward to change behavior either.) The second and more important can take video in any format and process it three ways: The first way is automatic, programmatic AI, if you will. There we can slice up the video into images, enhance the images, look for brands, and make correlations through that.  That gets us to about 30% or 40% in English. If you’re talking about Chinese, that gets you to 10%. Then the second layer is a crowd. So, we need to process extremely high quantity of videos. And we need to know what’s inside this video. So once the machine has done its job, we have our platform – just like it can recruit real shoppers – it can recruit in the same market people who will see the short video or even like a five-second snippet of the video and say, “In this video, is this brand, this brand, this brand and this is the price.  They can decode the video very, very quickly on a crowd platform. And then finally, once the data is 70%, 80% baked, then our people take over. So, we do have analysts who watch videos. There’s no way to get around it. I watch videos from time to time. What they’re looking for is to see what degree of accuracy we’re getting in that platform. Whatever manual stuff needs to be done, they do it. My joke is that HI is still a tenth of the cost of AI. Human Intelligence, you can have people…

[34:39]

100%, by the way.  This is such a great point that you’re making.

[34:43]

Yeah, and they don’t need a lot of training because CPG market research, above everything else, is about common sense.  If you’re someone smart and educated, I can give you a little bit of training. And, again, remember that we’re not processing these videos ethnographically.  We’re looking for specific markers. And then audio is a lot easier to do, to transcribe and use programmatically. So that’s kind of the platform we’ve had to build because AI is just not that good.  And if you talking about native video, AI is not going to get good. Where you can actually use technology is if you can use crowds to capture. It’s a very interesting thing. I had a lot of companies (I think Google tried it) when you translate capture from visual to text, enough people do the same thing.  They know that this is real text. They can translate a book. And that’s very interesting. We use something very, very similar to translate, transcribe these videos. And we really think that the gig economy offers market research companies this tremendous benefit of becoming tech-enabled but not through AI but through HI.  It’s just that you don’t have to hire hundreds of employees. You have this just-in-time workforce that you can leverage.

[35:56]

Yeah, just from a community component, I really like the idea of the power of HI. When you’re talking about the gig economy, just being able to have more of a distributed wealth because you have an open work opportunity.  It has a tremendous amount of community value or human value, I should say, assuming it’s the right shoe for the right foot, right? To your earlier point, there are obviously clear applications and winning applications of AI over HI.  I want to circle back for just a moment about this point that you made early on, which is on surveys. And I think this is a really important point for the other executives. Do you see surveys as the budget that you’re competing for?   

[36:45]

That’s an interesting question because most of the business we win, we never find out what they cut because it’s very rare that we even do business in an RFP setting.  In fact, most of the RFP’S that we get inbound, right? We know we’re not going to win; we often don’t even bid, the reason being it’s a mind shift. And if they think of it purely as a replacement for something that they would do in a survey form, then they’re going to be disappointed because in surveys, one of the big benefits, it’s closed-ended again for a very small amount of money, relatively speaking.  You get a lot of quantity of answers, right? And what we are saying is that the game is about the quality of the data and the actionability of the data; so, we don’t get put up against surveys. But in a different context, we think of ourselves as a video survey. So, better educate the marketplaces. We’re not a tech company. We wanted to be a market research and data company. We had to build a lot of technology to facilitate the type of data we wanted to extract.  Now we have built that extraction engine based on video. We’re very open, and we’re talking to a lot of other market research companies outside CPG to license it. In a way, we think of it as a platform, and you can think of it as a video-survey platform. So, we actually don’t think of our technology as being different from online surveys. We think that this is a big part of the future of online surveys, right, the audio-visual component because we also have a survey engine.  So, if I want to know if you’re male or female, what’s your age, income (all of these standard questions), I don’t need to make a video out of that and increase all my costs to get that information. You can give me that information very clearly. So I want to use video truly for observational, if you will. So, that’s how a kind of see the evolution and that’s where I think most of the platforms today that are online survey platforms, I think will be adding audio-video to their platform within the next few years.  So I just see that, all of that kind of just coming together. I don’t think that for the next decade, we’re moving away from online surveys, but I do think CPG tends to be leader in market research. So I think it will lead the way in video and audio. I don’t know if that answers your question.

[39:13]  

Yeah, I mean it’s really interesting point for me.  As an entrepreneur, I always think about what is the…  Actually, the person that this idea came from is a man named Doug Gallypso.  I have a tremendous amount of respect for him; he’s on my previous board of FocusVision.  Anyway, he actually asked me a question one time: “Jamin, are you competing for an existing dollar or a new dollar”?  And it was this Ah-ha moment for me. And it’s one of the reasons like, if you think about like Uber, Uber was so successful because it wasn’t trying to create new budget, right?  I was already going to pay for a taxi ride; it’s just a better taxi. You know what I mean? And so, like there was no argument in my mind of, “Oh, I’m going to pay for an auxiliary service that’s going to create a better experience.”  One of the things that I’ve seen and actually been part of in entrepreneurship is I’ll come up with new thing (We’ll call it an online survey, which sounds ridiculous right now, but it wasn’t in 1996) and say, “OK, now, I’ve got this new mechanism by which I’m able to gather consumer insights, and, Oh, by the way, it’s great.”  So, the corporations in those days, they really struggled with it, but it did have parity with a budget line item. In other words, it’s still a survey, right? It’s just a third category or whatever number categories there are. That’s where I’m seeing what technology has brought forth in the last, I’ll call it, three years, like a plethora of video, audio, and text-based hybrid qual/quant tools that’s basically qualitative at scale.  And everything is pointing (and I’m also done with my rant) everything is pointing to one thing, which is a better conversation with the consumer. When you think about what surveys did a hundred years ago the way it started when this whole industry started, it was I needed to have a conversation at scale with my constituents. In order to facilitate that, I needed to be able to do a standardized set of questions across people. And so, then those have to get analyzed, obviously.  And the way that was done was data tables, and then from that we now know that there are 2.3 children in every household. But the reality is nobody has 2.3 kids or whatever the average is. And so, what these qualitative at scale products are bringing to market is actually, to your point, a different… So it’s not the same thing; you can’t compare them. It’s not a survey, and it’s not a focus group. It’s something that’s like right in between those two things. But where I’m seeing corporate budgets having a hard time tracking is how do I pay for it.  In other words, “Am I not going to do the survey?” “Well, no, maybe I still need to do that.” “Or am I not going to… Well, no, I still want to see the face or whatever it is. I want that human interaction piece.”

[42:02]

That’s why I think today is a very good time for us.  There are two reasons for it: One is marketing requires data to make decisions.  No marketer today is going to do the 1950s, “Well, I’m smart; so, I can just guess it.”  Every decision they make requires data. And our pitch to these big companies today is very frontal where we say, “Look, you’ve been buying billions of dollars of data, yet you keep losing market share.  And e-commerce, your market share is down ten points over your traditional commerce. Why? Because you’re playing with yesterday’s tools. So, if the data you’re buying today is so perfect, then why are almost every big manufacturer, especially the food manufacturers, in trouble?”  So, clearly, there’s a need for better data; there is a need for better decision making. Not every meeting goes that way, but some meetings you can have that discussion, and you can kind of do that broaden-the-horizon thing. But the second piece quickly has to be actionability. So, I gave you the example of new products.  Same thing applies for marketing. We can literally tell our clients that their new product is going to succeed or fail in two weeks. Before the product reaches 20% distribution, we’ll make a prediction. And in the right situation, if it doesn’t sound too sale-sy, I’ll tell the client, “I’ll give you double your money back for whatever you pay for my data, if my prediction is wrong.”  But, more importantly, if my prediction is right and 80% of new products fails, I’m not going to come back and say, “Oh, look, your product failed, and I predicted it, and screw you.” “But I’m going to come back and give you three ways that you can fix the problem before the retailer even realizes it. Get your product out of this part of the shelf, put in that part of the shelf. That is also your shelf; so, that it’s an easier transition.  Get the price down by 30 cents. Put a coupon on it. I will give you very, very actionable answers that will change the metrics and will change the future of the product.” So, that type of conversation – again it has to be much more subtle than the way I’m presenting it to you – that works. And the last thing I’ll say about this is that market research has to… We, as researchers, open our minds grudgingly, if you will, when we are pushed by people like you to think about online.  It took us a long time, but then everyone loves online today. But we’re going through the same problem again with the internet of things, VR. All of these other communication tools, and experience tools (voice, Alexa, right?) are going, scaling up, but we’re ignoring it where we have our head in the sand, going, “Well, online survey is the way to go because I can get a sample of 1000.” So it is our job, I think. to expand our clients’ minds, but we have to do the R & D at our cost so that the information that we bring to them is actionable.  And that’s been a big problem with neuro and behavioral and those techniques where you go and say, “Look, I hooked up 100 people to an ECG and look what I found.” “OK, how do I sell more Coca-Cola based on this data?” “Well, you can’t.” So that’s where the disconnect is, I think, and I think it’s going to change.

[45:38]

I mean there’s a couple things there.  Rogier Verhulst from LinkedIn had this great quote that I keep coming back to:  “Every research project needs to have the ‘now what’ and ‘so what’,” as the follow point.  Sexy technology is just not the answer. It’s the better insights, to your point. And in the second part, Kristi Zuhlke from KnowledgeHound had this framework of what’s the ROI on each project.  And it’s incumbent on the research company, the provider, as well as the internal research to make damn sure that they know what the financial outcome is of that research. It isn’t just, “Oh, well, now we know there’s 2.3 kids.”  There needs to be a “Why,” that “Now, OK, oh so that means I can sell more stuff to this particular demographic” or whatever it is. That’s the other piece. And I think as long as market research can cement those anchor points in their deliverables, then it makes it a lot easier for the brands, the CPG companies, to know ‘cause it’s a zero sum game for them,  “OK, I’ve got $50,000, whatever it is, to do my research. So, what’s the optimal allocation of those dollars across my suppliers or knowledge partner or whatever in order to answer those questions so that the executive is able to make a decision with confidence?” And that’s kind of the broad point that you’re making and I just couldn’t be more excited about is that us, as an industry, for us to continue to grow and really I think assume our position of dominance inside of the corporate org chart, we’ve – like you said – we’ve got to bear the burden and then not be afraid to talk about this shift in consumer insights.  Four years into your startup, you’ve probably seen a wide variety of people enter your work force some successfully, others not. What do you see as characteristics of an All-Star Employee in context of a startup?

[47:38]

You know this is something that I think about a lot because all startups live and die by getting a good team of people together, but market research and data-driven startups even more. Because we’re really not pitching an algorithm or a technology, there needs to be these human translators that can take the data and talk to customers about it but really from a perspective of both empathy and consultation.  So, a quick sidebar is that we have a very strong principle and we’re extremely technology-driven as a company but we don’t give any of the technology to the client because our clients pay top dollar for the data (we’re very premium priced) and, in return, they want to talk to a human being. Why? Because they work on 50 projects at a time these days. They just want to be sure that that person at the other end is not going to leave them hanging with a dashboard, which a lot of companies do.  So that’s built into our pricing and our business model. So, when we look to bring people on board, anyone who’s going to touch a client must know market research and must know market research really well and pretty much all aspects of market research that the client deals with because we don’t live in a vacuum and our data doesn’t sit in a vacuum. You have to have context. So that’s like a given. Of course, the people who work on the product and technology have technology background, but today I would say a lot of them have become market researchers.  So that’s very, very important. But beyond that, it’s really people who are smart. That you can literally look at the high school or college GPA and tell if someone’s smart. Not all smart people have high GPA’s, and I’m proof of that, I think so. But anyone who got a good GPA early on in their career probably is smart. It’s not easy to get good GPA’s. So, if you have those two things, then the third thing is motivation. That’s it. If the person sitting across from me is motivated to work in a startup, to be a part of something new, different, growing rapid pace…  First of all, it’s infectious, you can tell. You can see it in their face. You can see it in the way they speak. You can see it in the interest in the product and how much research they’ve come before coming here. You can see it in the follow-up that they do. And certainly, you can see it perhaps in their resume as well.

Then you have another type of person who is kind of becoming insecure about their job at a big research company and starting to look around.  And that person is going to fail in a startup environment. Another type of person that I look for which is a little rarer is all the stuff I described before with enthusiasm, etc., but more goal-oriented.  One of the hottest new hires we’ve made, Graham (I’ll call him out). He said in the interview that he wants to be doing his own startup in five years or be CEO of startup in five years. He’s a young kid. And I like that because if you have a goal, and I can help you in your journey towards your goal, then you are much more likely to do what it takes to be successful at Nailbiter.  And your success will be the company’s success. When I joined Affinnova, I was very young, probably naïve and stupid. Those characteristics also help a little bit, but I was extremely determined for Affinnova to succeed not because I liked the CEO and he was a mentor and all this stuff and the company was great but I wanted to succeed. And I felt like here’s a vehicle that’ll help me get around the trap of manager, VP, SVP at Neilsen, that traditional path.  I’ll make money; I’ll be independent; I’ll travel, which I love to do; I’ll travel the world. And I made the job what I wanted to be. And that’s what people do when they join a startup and become successful; they start kind of asking for things: “Can I do this?” “Can I do that?” And, within reason, you have to let them because then they will do things they’re good at because they want to succeed. And again, if it’s aligned with company’s goals, the company will do well.  So, these things sound difficult; they’re actually not. But the flip side is “Don’t pretend to be a startup.” And I’ve seen that a lot at bigger companies: “We’re a startup within a startup.” “No, you’re not.” A lot of CPG companies are doing that these days: they’ll create like a startup room in the basement, and this is a startup within a startup, but at 5:30 everyone is gone. And rightly so, because if that startup within a startup becomes a billion-dollar enterprise, those people who worked on it, they get nothing.  They get a decent bonus check. But, if you really did a startup and you worked 24/7 to make it successful, you’d be a billionaire, probably the wrong word to use in market research. I tell everyone a billion dollars doesn’t exist.

[52:56]

Unless you’re Ryan Smith.  I think he did OK on the Qualtrics exit.  

[53:00]

That’s true, that’s true.

[53:03]

Congratulations to them, by the way.

[53:04]

They are exceptions.  That’s my answer to people. And even the market research piece at Affinnova I would teach because we had more resources.  Here we do hire people who have the experience but that experience and skill set is very secondary to intelligence and motivation, I think.  Those are things, you can’t learn them; you can’t just put them on.

[53:29]

So, we’ve talked a lot about Nailbiter today.  Do you have any parting words or ways that people can get in contact with you if they’re interested in finding out more?  

[53:38]

Yeah, contact me on LinkedIn.  I love talking. You are very easy to talk to.  I hope to continue the dialogue with you. I’m not very good at communicating through email and other things, but I actually have someone who checks LinkedIn and a lot of interesting people I find reach out through LinkedIn.  And I enjoy having conversations. Anyone who’s listening to this who has no interest in buying data from us but wants an education, I’ll be happy to teach, especially people who want to copy what we’re doing and steal from us.  We love that too. We’d rather have 50% market share of a big pie than 100% market share of a small pie.

[54:18]

Love that.

[54:18]

So we are going to be reaching out a lot more through conferences and through forums to educate the marketplace because I think we’ve hit upon something, but we’ll find out.

[54:28]

My guest today has been Amit Dhand, co-founder and CEO of Nailbiter.  Thank you very much, Amit, for joining me today on Happy Market Research.

[54:38]

My pleasure, Jamin.  Thanks for inviting me and thank you for this podcast that you’re doing.  I hope that more and more people will listen. And I think you’re somebody with interesting ways of interviewing people.  So I wish you continued success.

[54:50]

Well, thank you very much for that.  And thank you, everyone, for your time and attention today.  I hope you have a wonderful day. As always, please, please provide us reviews whether it’s on Apple iTunes or GooglePlay.  Your reviews are how other people like you are able to find our podcast and it is our oxygen. Have a wonderful rest of your day.

[55:15]

Schlesinger Quantitative is proud to have sponsored of this podcast.  Schlesinger delivers comprehensive online survey solutions, including survey programming, world class project management, intelligent recruitment, survey hosting, and data delivery services.  An uncompromising commitment to your success sets them apart.

WIRe Series – Rebecca Brooks – Alter Agents

Welcome to the WIRe Series. Recorded live in Austin, this series is bringing interviews straight to you from the WIRe MRx Meet & Mingle event. In this interview, host Jamin Brazil interviews Rebecca Brooks, Founder and CEO of Alter Agents.

Contact Rebecca Online:

LinkedIn

Alter Agents


[00:00]

My guest today is Rebecca Brooks, the CEO and founder of Alter Agents, which is a super cool name.  It’s totally like 007’s research, I think in a good way.

[00:14]   

Thank you.  

[00:14]

How are you doing?  

[00:15]

I’m good.  How are you?

[00:16]

Good.  Yeah, we’ve known each other for ages in the industry.  It’s been ages since we’ve seen each other at the same time.  

[00:20]   

I know.  It’s really good to see you.

[00:22]

So, we’re at the… live at the WIRe events today with…  in Austin with IIeX. I have not been to Austin in literally over 20 years, and the city has completely changed.  How long have you been part of WIRe?

[00:36]      

I’ve been part of WIRe…  I mean I feel like since the beginning.  I started going to the first meetings in L.A. about ten years ago, which is when it started.  And I’m really happy to be more fully engaged with the group than ever before. So, I’m the Los Angeles event lead in program.  I’m also a mentor; I’m part of the Executive Group. We’re going to our Summit next month. So it’s become a really integral part of my professional life.  I love it.

[01:04]

We’re going to dive into your business in just a minute, but I want to just focus a little bit on WIRe.  Talk to me little bit about the Mentorship Program. What sort of person are you looking for to fill that seat?  And the other side of it is the mentee. What kind of person is a good fit in that role?

[01:22]

Yeah, I think that anybody with ten plus years of experience in the industry, whether it’s all on the client or all on the supplier side, is a valuable mentor.  And really someone that will help younger women navigate the corporation world. A lot of them are trying to come up in their business. So, they’re looking to get promotions; they’re looking to get raises.  And that’s a difficult thing for anybody to navigate but especially young women, particularly if their organization is very male-dominated. So the WIRe mentors really have invaluable experience in that regard because they’ve all been successful enough to navigate that path, right?  And then, in terms of the mentees, I mean we’re really looking for women that will not only benefit from the program but that will also continue the legacy of WIRe and, in a few years, turn around and mentor themselves and that are really committed to the program.

[02:18]

It’s an important work on both sides of it.  What kind of time commitment is involved?

[02:22]

For me…  Well, I’ve been with my mentee now for two years.  

[02:26]

Wow.

[02:26]

Yeah, she had the option of leaving and going to somebody else, but she stuck with me, which was nice.  So, we talk every month. We try to do it in person if we can but schedules don’t allow that. We usually have a list of objectives that we’re going through from short-term goals to long-term goals; so, we’re always addressing those, talking about them.  And then I’m available to her if things arise. Yeah, but usually once a month.

[02:55]  

So, shift gears a little bit.  Alter Agents, tell me a little bit about what you guys do.  

[03:01]  

So, we’re a full-service market research consultancy.  We’re really methodology agnostic, vertical agnostic. We do qualitative and quantitative.  We work with large companies like Hyundai Motor America and Viking River Cruises. We work with smaller brands like Humm Kombucha and Evelyn & Bobbie.  Really what we found is that our niche isn’t in a particular type of research or with a particular type of industry, but really more around those clients that need a more consultative partner.  You know a lot of people can execute a project but those clients that really need somebody to guide them through the study design… We get really in deep with why the research is being done, what questions are going to answered from it.  What are they going to do with that? What decisions are going to be made? And then, we work with them on really evangelizing the findings throughout the organization at the end. We don’t just deliver a report, but we’ll do workshops; we’ll do additional deliverable for the C-suite.  So we really try to be more of a partner in a broader sense. So we tend to work best with companies that have small research departments or are really understaffed in that area or overworked in that area where we can take on a heavier load than the traditional research company.

[04:20]

Have you seen this activation of research as a trend inside of our space?  

[04:25]  

Yeah, I think I’ve always gravitated towards it in my career.  It was very challenging for me when I would deliver something to a client and then it would just go into the void.  And I wouldn’t get to see what happened with the data. And I loved having clients come back because then I could see:  What have they done? What decisions were being made? So for me, it was always kind of a personal desire and itch I needed to scratch.  So I tended to gravitate towards those clients that wanted that back and forth communication. But I do feel that the industry, as a whole, is kind of pulling into either DIY (Here’s your technology and your product) or pulling more in the direction that my company is, which is more sort of consultative, white-glove, hands-on kind of servicing.     

[05:13]

So, you’re launching some research on how brand category affects purchase behavior.  Tell me a little bit about that.

[05:19]

Yeah, I’m really excited about that.  We should have our data out in the summer.  But the idea is that we’ve been noticing a lot with our clients that the influence of technology in any industry has been driven towards consumer convenience, the idea that you want to eliminate as many barriers as possible for the consumers they can go to purchase.  And what that’s creating, whether we’re talking about luxury cruising or automotive or a beverage drink… what that’s creating in this environment where, depending on the context of the purchase, the shopper can actually be almost mindless about it. So, if you think about a subscribe-and-save feature on Amazon, where you set it up once and then you never have to think about it.  Your dishwasher detergent is coming every month, right? It’s great for Amazon, and it’s great for the brand that won that subscribancy. But if you’re a brand trying to break into that or if you’re trying to convince people, you have an additional barrier now not only to convince them to try your product but to delete their subscribancy.

[06:24]   

Yeah, that’s a big…  That could be a big… I mean the whole reason you set that up is to one-and-done and forget it.

[06:29]

Right.  We’ve been talking for years at Alter Agents in our e-books that we’ve been putting out about how traditional research isn’t addressing the questions that marketers need to answer.  And this, in particular, I think is something that we’ve been seeing affecting more and more of our clients the way that consumer expectation for convenience counteracts traditional marketing efforts.  And so, we need research to be a lot smarter about the context of the purchase, the priorities of the shopper. So, the research that we’ll be doing and distributing this summer is really about demonstrating that there are different questions that we should ask beyond awareness, familiarity, consideration.  We need to really get deeper and talk about it from the consumer’s perspective. So we’re hoping to have some really strong numbers behind that.

[07:17]  

Talk to me a little bit about the gap that…  I was talking with Michelle earlier that your point of view is that there’s a gap that’s widening between everyday CPG products in the marketplace and then how it’s engaging at a category level.  Tell me a little bit about your thesis there.

[07:35]

I really think again it comes back to the technology has been working to make those everyday purchases as simple as possible for people, whether it’s a subscribe-and-save or whether it’s the way that grocery retailers have been reorganizing their shelves to put the most desired products upfront and all of the science behind the way people are physically shopping.  All of those things are pushing the consumer to not have to think about it. And that is a very different kind of shopper context than when you’re looking at brands that are pushing more towards the purchase as an experience where the purchase itself is part of what you’re getting from the brand. It’s not just the end product.

[08:17]

It’s almost like the box as Apple can redefine packaging as part of the product experience, but now you’re actually going upstream further it sounds like.   

[08:24]

Yes, yes.  There’s the high-end luxury stuff like BMW flying you over to actually pick up your car in Germany and drive it around the country and then ship it home.  That’s a very high-end extreme. But even things like a Patagonia jacket: you go into that store and you have an experience that is as memorable as the jacket itself.  There’s this real sort of pull into these strong extremes. And this sort of blanket, “This is how people shop” or “This is how we should market to people” just doesn’t work without understanding the context of the category.

[09:01]

This is a super interesting topic.  Google and Amazon have been gobbling up generic brands.  Paper towels, for example, I can’t remember which one won it, but that happened last year.  As opposed to Brawny or Scotts… So now, when you’re acquiring your product if you’re blind from a consumer-journey perspective because you’re ordering in a voice environment, that’s a big problem if you say paper towels versus Brawny.  I have to pick on Brawny. I don’t know why. ‘Cause I grew up with the commercials of the Brawny guy. With your connection to customers, are you thinking about how they’re standing out from generic? Is that part of the conversation?     

[09:45]

Absolutely, it is.  I mean one of the things that technology has really done is pushed brand further away from the decision-making process.  I mean everybody shops on Amazon. You’re filtering by… Well, first of all, you’re searching on the type of product you want:  “I want blow dryer,” “I want markers.” And then you’re filtering on things like Prime or price or whatever. And then brand comes into at the end, if that.  I mean maybe at that point, you’re picking the best reviewed product and not even thinking about the brand. So what does a marketer do in that context? Right.  They need to understand the triggers that are pushing people to those products; brand may not be one of them. Maybe, your marketing strategy isn’t so much about the brand name and the brand feeling as it is about the distribution channels.  So that’s really where we’re trying to push our clients and push our researches sort of what is that space that they’re making that decision in.

[10:41]  

Yeah, which we saw with the Berkshire Hathaway announcement about Heinz getting crushed in that context because they weren’t…  They were considering the brand piece of the thesis but not necessarily channel distribution, which as it turns out a big problem.    

[10:54]

Right, if you think about traditionally we’ve grown up on the 50 top global brands and now a lot of them have been CPG and I don’t think that will be the case in ten years.

[11:03]

And it’s really hard for a brand to position themselves as the Kleenex in their category.  I mean that’s very hard to pull off.

[11:11]

And we’re seeing it not just in CPG but we’re seeing it across the board when we work in a lot of different categories.  Even our Viking River Cruises client, their target demographic are people over 60, and they’re expecting a lot of technology and convenience and ease-of-use when they go to their website.  They want a lot of those decisions taken away from them to make an easy purchase. So it’s really across the board.

[11:38]

The consumer is valuing time more than anything else right now.  More barriers there are… It’s a no-brainer kind of point that I’m going to make, and everybody already know what it is:  The more barriers there are, the higher the likelihood of drop-out through that process. But I think we need to pull back more and re-envision.  There’s a lot of sites that I shop where I’m like, “Oh, my gosh, where is the Buy Now?” Like I’ll add stuff to my cart and I can’t figure out how to check out.  I’m like, “What the hell is going on? How is that the hard part of this?”

[12:11]

People experience a really amazing convenience in one category like being able to dial up an Uber on your phone, and then they expect the same convenience somewhere else.  So, why is it so easy for me to get a car to take me from one place to another, but I have to hunt down my broker with smoke signals? So there’s a frustration that’s growing.  I emphasize this a lot: It’s not the younger generations only, either; everyone is getting really used to convenience, and everybody’s expectations are rising. You have these sorts of tensions of brands needing to meet consumer demands for convenience but then in doing so, are losing some of the brand focus.    

[12:54]

Last question:  How do you think market research is going to adapt over the next five years?

[12:59]

It’s hard to be in the prediction business in this industry these days.  You know I started in market research when things were still done on paper, and online was something where there was a lot of skepticism about it.  So I’ve seen the industry go through a lot of changes, but I think that the changes that are coming now are coming at us from all angles. It’s coming at us from machine learning, and AI, and automation of analysis, which is really fascinating and kind of scary at the same time.  There’s no stopping technology, and there’s no stopping how quickly it’s going to advance. And I think it’s going to continue, in really our industry as well, the consumer’s convenience. Our research buyer’s convenience is paramount for them also. So, a lot of these technology tools are pulling in that direction, but then you have companies like mine that are also trying to retain the quality and the depth of analysis.  Honestly, who knows? It’ll be really interesting to see.

[14:09]

It will.  The other point I riff on there is the point of insight consumption is interesting too because tools have democratized access to the consumer.  It used to be the case that it was just the researcher that had that capacity to conduct research, thinking about the old days of pencil and paper and phone.  And now, all of a sudden, anybody and everybody does, in fact, conduct research. From a market research category perspective, we really need to think long and hard about who really is our target customer, and how we’re going to help the organization as a whole adopt insights.     

[14:47]

Well, on a tangent, I really feel like market research is very similar to what’s happened to the news media since the internet has begun where…

[14:56]

That’s a really good analogy, actually.

[14:57]

Yeah, there were a few people in control of the information, and everybody was getting the same information.  We used the same methodologies, the same basic principles, and then the internet came along and democratized information and that’s what’s happening in market research now too.  And I think one of the startling things about it is that we have some quality concerns.

[15:14]

That’s an understatement.  It’s capital concerns, right?  I mean that’s a big problem.

[15:20]

That when people can go out and do it themselves without the background, without the information, what is the quality of that data?  And even though it’s very accessible and easy to get to…

[15:30]

Ton of misinformation.

[15:30]

Accurate, right.  So yeah, I mean I think we’re in that… beginning to see that transition start to happen.  It’ll be interesting to see how our industry reacts.

[15:39]  

My guest today has been Rebecca Brooks, CEO, founder of Alter Agents.  Thanks so much for joining me on Happy Market Research Podcast.

[15:45]  

Thanks, Jamin.

[15:46]  

Let’s enjoy the WIRe event.

[15:47]

Alright.

WIRe Series – Karen Lynch – InsightsNow

Welcome to the WIRe Series. Recorded live in Austin, this series is bringing interviews straight to you from the WIRe MRx Meet & Mingle event. In this interview, host Jamin Brazil interviews Karen Lynch, Senior Director of Qualitative Insights at InsightsNow.

Contact Karen Online:

LinkedIn

InsightsNow


[00:00]

I’m here with Karen Lynch.  We are prepping for the WIRe event tethered to IIeX in Austin.  She is the Senior Director, Qualitative Insights at…

[00:12]    

Insights Now.

[00:13]

Insights Now.  There you go. This is a little-known fact.  I have participated with WIRe from the very early days when Kristin started it while working with Decipher.  And I actually stopped going to the events because I felt (and this was my Ah ha moment), I felt so uncomfortable being the only man in the room.    

[00:38]

Oh, got ya, got ya.

[00:39]

Which is a really interesting counterpoint to like last night – I went to dinner, and there were three guys and a girl.  And I’m thinking to myself, “It’s so interesting having the shoe on the other foot.” And just not having that perspective until you’re in that environment.

[00:53]   

Yeah, yeah, absolutely.  What you just talked about is what it feels like to be a minority in the room, right?  And so, in many industries, women deal with that all the time: they step into a room filled with men.  So that’s why we celebrate with Women In Research, why we celebrate women in these roles because it’s a strive for equality and strive for balance.  And the closer we get, the better it is for all of us. And your support at those sorts of events brings us closer. So, thank you for that.

[01:20]

For me, it is such an interesting head space.  The framework of business… Recently, I was reading a Harvard Business Review article and they were talking about how temperatures set in offices are set to men’s ideal temperature.

[01:37]      

Oh, that’s interesting.

[01:38]

Which is like three degrees cooler than women would prefer it to be.

[01:42]

Yeah, most likely.

[01:42]

And I thought, “Gosh, it’s like just set up in that sort of like framework of…  And I’m not trying like us versus them, us being obviously the man. So, I don’t mean it that way.  I just think there’s so much that’s built up in society that we just take for granted as sort of normal.  And then, to your point, being the only “minority” in room, really does change that dynamic. So, my point in bringing all that up is just that WIRe is an inclusive organization and it’s…  Regardless of any sort of demographic profile, you can participate whether being a supporter or even joining different events they’re putting on. It’s a great opportunity to increase your overall exposure.  Important work. So, ah, tell me Perspective Thinking: “Accessing Perspective Thinking and the Impact on Research Product Development.” What in the world is that?

[02:43]

What are we talking about?  So, in market research we’ve been talking a lot about implicit, explicit testing over the years.  We talk a lot about System 1 versus System 2, thinking that there’s only two ways of thinking and two ways of making decisions.  For those of you listening that don’t necessarily know the difference there, it’s as simple as something in System 1 might be a quick, automatic decision like “Hey, I’m going to grab the gallon of milk that has the red cap ‘cause I know that’s whole milk.”  You don’t have to think much about it; it’s pretty automatic. And then there’s System 2, which is like, “Now I need to buy a car.” And you just don’t grab one off the shelf. You sit and you think and you’re deliberate about it. And those two modes of thinking are at play with every consumer decision that’s made, but what they don’t account for is the imagination.  And so say, you wear glasses. So say, you’re in the frame shop and you’re trying on different lenses and you’re letting your imagination go to “Which one of these makes me look the way I want to look when I’m at my most professional?” “Which one of them portrays my creative side?” “Which one of these puts out there that I’m an open, friendly guy?” So, you’re doing this imaginative thinking.  That’s Perspective Thinking: You’re making a decision with something else at play than both System 1 and System 2.

[04:01]

So is that kind of like a System 3?

[04:03

It is System 3.  So that’s what Perspective Thinking is.  It’s System 3. And it’s at play in a lot of different decisions that we make.  One of the examples that I use for people is “Imagine you were driving somewhere.  Say, you’re driving home from work. And you know the route that you always take; it pretty straightforward.  But then, you know what? Traffic jam. In your mind, you start to wander navigationally. What other ways might I be able to get home from here?  Because of this traffic jam.” That’s System 3 at play. It might be, “Oh, gosh, they just put a new grocery store in my town. I’m going to have to shop there.  I don’t know what that’s like. Where will I park? What will my behavior be upon entering a brand-new store? Will it be laid out the same way I’m used to?” All that kind of thinking, it’s the stuff of our mind wandering.  That’s System 3 or Perspective Thinking.

[04:52]  

So, going back to System 1, which is really more habit, engrained in how we just process instantaneously a decision.  System 2 is much more factual. You break or degrade a product into a series of features and then do your comparing and contrasting in that framework.  And then System 3, which moves into a much more complex perspective, which is this creative thinking element, the envisioning, the, as you said, the creative thinking aspects.  How do you employ that from a research perspective? ‘Cause the first two are easy for me to do, right? The third one: that’s an interesting challenge.

[05:34]  

Yeah, because it’s all around hopes and fears and thoughts about what’s happening in the future.  And I think most of us in market research understand that if you were to ask a consumer about the future, they shut down.  There’s actually some psychology involved or neuroscience, I should say, involved with how part of your frontal lobe shuts down when you’re asked about the future.  Your brain can’t go there. So a consumer can’t project into the future and have it be credible for research purposes. But we have tools, right? At Insights Now, we use a tool that helps kind of tap into the spirit of imagination.  It’s a play-based method, for instance. And we put people into this playful state of mind where they’re actually able to get to some more imaginative thinking and bring those thoughts to life. So it’s thoughts about their hopes and their fears and their aspirations.  And then brand teams can kind of go to that space of hopes and fears and aspirations and move forward to different stages of their process with them.

[06:30]

That’s really interesting.  Can you give me an example? Is there a set line of questioning?  Is that how you frame the…?

[06:40]  

So, sure.  What we do is we set up an environment conducive to play, first of all.  And we have a method called PlayFull Insights where we’re using Lego bricks to kind of put people into that playful state of mind.  And we have a series of skills that we build as we proceed with PlayFull Insights where people are literally developing their skills, not just manual dexterities but skills because we’re building with Lego bricks but their storytelling skills and their ability to think in metaphor and their ability to talk about themselves in that imaginative space.  So they get to a very safe place of sharing and vulnerability and they let us into those subconscious thoughts about what the future might hold for them all through this kind of method and the deliberate process that we go through to bring them there.

[07:27]

Yeah, psychologists have been using play as a mechanism for dealing with trauma for years, and it’s interesting…  you know sandbox kind of therapy. PlayFull Insights. That’s “Play” and then capital “F” ull, right, is the…

[07:42]

Right, deliberately, yeah.

[07:43]   

Yeah, of course.  Talk to me a little bit about the name.

[04:47]

Yeah, so the idea again, going back to what you were saying about the benefits of play and why we wanted our research to be full of all of those benefits, the idea is that in a qualitative setting, which what this particular method is, we want people to be at that kind of relaxed state of mind, at that place that they can go to when their walls come down like children on a playground or in a sandbox if you will.  So what we want to do is capture the spirit of play and all of that great release of endorphins that happens as a result that brings people to this place of this vulnerable sharing, as I was saying. So PlayFull Insights, which is all about getting insights… That’s the business that we’re in, of course, and the conference where we’re at, of course. But the full part of it is just how loaded that is it. People often don’t even know what’s there, right?  There’s a model in psychology called Johari’s Window where some people aren’t even aware of what’s hidden below the surface, but with a method like this, we can bring that to the surface, and they can reveal things that they didn’t even know they necessarily had to share, but it comes out. We’ve brought them to a state of mind through the power of play to load us up with good stuff.

[09:00]  

Age?  Is there like a cut-off for…?

[09:04]

So, sure.  So, sure. I just did this work actually with adolescents.  We can start as young as adolescents. If it’s too young, it’s like their imaginations…

[09:14]

Normal.

[09:15]

It’s just normal, but they also, if they’re too young, they literally just want to play.  And they don’t want to be strategic about it, deliberate about it, which is what we are doing.  It’s hard to tell a child, “You’re not just building from your imagination alone; you’re building what we tell you to build.”  So too young is not really great, but adolescence is when it kicks in, through teens. It really works very well all the way up through kind of the senior citizen age where No. 1 there’s an element of cynicism, where they really do just like to talk and not necessarily talk on purpose but, most importantly, there manual dexterity starts to deteriorate a little bit.  It’s a little harder for them to assemble Lego bricks, for instance. I mean we have other play-based methods that we could use with other adults in that kind of demographic, if you will, but this particular one that we’ve just referenced, PlayFull Insights, kind of cuts off at that age.

[10:04]

How did you come up with it?

[10:05]

So, it’s actually my baby, if you will.  Several years ago, the Lego Group actually started and developed the method of Lego Serious Play.  And a few years ago, it came on my radar. They made it open source in 2009. And so, it got on my radar in the early 2010s, and I became a facilitator of the Lego Serious Play method, which is great for team building, strategic planning, creative problem solving, breakthrough methods for internal purposes.  And because I was in the field of qualitative research, I worked with another qualitative researcher, a colleague of mine, and the two of us said there has to be a way to adapt this for research purposes, which is a little different because the consumers don’t necessarily know what we’re doing there or why we’re doing it.  They’re not privy to all of our objectives, and we want to keep it that way so they don’t kind of get in the way of the research process. So we had to adapt the method a little bit, but it was just a natural fit for us because the insights gleaned from metaphorical conversations are really genius. So anyway, this colleague of mine, we just got to work on how to make it happen, right, forcing connections between one method in one field to this method in our field.       

[11:16]  

I love the creativity associated with that.  I’m sure you guys we’re playing with some bricks at that point in time

[11:21]

Absolutely.  That’s what it’s all about.  A lot of fun. And it makes everybody happy, right?  There’s a whole lot of fun and smiling energy that comes into a room when we have Lego bricks spread around.  

[11:30]

Do you have a favorite project?  

[11:32]

For that particular method?

[11:34]

This particular methodology.

[11:35]

Well, it’s hard not to talk about one we just came off of.  We just came off of a case study actually where we executed with Kraft Heinz some work exploring fun with adolescent children, in fact.  And some of things that we learned from these, again, pre-teens about who they are and what they aspire to probably will stay with me for a long time.  We got to some great depth of insights with the generation that, typically, doesn’t really talk that much in a focus-group setting.

[12:03]

I know you can’t share any specifics.  I’m dying to ask you.

[12:06]

Well, alright, no, I can tell you.  They talked about themselves (this is not proprietary; we, actually, shared this out at a different event in a case study.)  They talked about who they were when they were at their best, and they talked about exhibiting good sportsmanship and they talked about being kind and non-judgmental and they talked about overcoming obstacles and barriers and had this great kind of emotional intelligence that they showed to us, which I don’t think we give younger generations a lot of credit for all the time.  So it was really nice to see them building models that talked about who they were at their best because they’re really fantastic human beings.

[12:47]

Ah, that’s fantastic.

[12:48]

Yeah, good stuff, really fun.

[12:50]

This is obviously a qualitative structure.  Do you have a specific facility that you do this in?  Or do you travel around?

[13:00]

We travel around.  As long as you’re trained in the method, you can do this at any traditional focus-group facility if the client team wants to be behind the mirror.  We have the supplies that we need. So we bring those with us, and we set up. We’ve also done it on site at corporate offices when we’re doing more of a co-creation where we have client teams, for instance, right in the mix with other adults.  We’re building literally side by side and then comparing and contrasting what team “Company” would build versus what team “Consumer” would build. And we’re talking about the differences and were getting right to the “So, what does all this mean?” right there in the session.  So it’s kind of a great co-creation method, if you will, when we’re on site in an organization as well.

[13:46]

If somebody wants to get in contact with you, how would they do that?

[13:50]

Oh, sure, thank you.  Well, the easiest way would be to shoot me an email:  It’s Karen.Lynch@InsightsNow.com.  Karen, traditionally K-A-R-E-N; Lynch, traditionally

L-Y-N-C-H@InsightsNow.com.

[14:04]

You have to actually specify that, by the way.  That’s good.

[14:05]

I know because some people are like, “Is that Karen with a “C”?  And I’m like, “No, it’s the traditional way.” I had traditionalist parents.

[14:14]  

My guest today has been Karen Lynch, Senior Director, Qualitative Insights at Insights Now.  Thank you so much for being on the Happy Market Research Podcast.

[14:21]  

Pleasure.  I could talk to you all day long.  

[14:22]  

Oh, I’d love that, and I am excited about getting…  Actually, back up really quick. Women In Research, how long have you been a participant?

[14:32]

So, just a few years now, probably about three years, I think.

[14:35]

Are you a mentor?

[14:36]   

I was a mentor last year.  It was one of the best experiences that I had ever done in my career.  Worked with a young woman who was a minority woman, was an African-American woman, and she often felt that in this industry that is heavy with women – not a lot of African-American representation – and she wants to be able to have a voice in that space.    

[14:55]

Oh, I love that.  Is she here at this event?  

[14:56]  

Yeah, she’s fantastic.  She’s not at this event, no, but she did some amazing things over the course of our year.  So I highly recommend anybody who has that kind of time and mindset to be a mentor and also give back just a little bit to this industry that gives us so much.  

[15:12]

Karen, thanks for being on the show today.

[15:14]

Sure thing.  My pleasure.          

WIRe Series – John Martin – Measure Protocol

Welcome to the WIRe Series. Recorded live in Austin, this series is bringing interviews straight to you from the WIRe MRx Meet & Mingle event. In this interview, host Jamin Brazil interviews John Martin, Founder and CTO of Measure Protocol.

Contact John Online:

LinkedIn

Measure Protocol


[00:02]

John Martin, Chief Technology Officer, Measure Protocol.  Thanks for being on the Happy Market Research Podcast.

[00:08]    

My pleasure, my pleasure.

[00:08]

So, we’re at the WIRe event, part of…  connected to the IIeX Austin events. What are your thoughts so far regarding IIeX?  

[00:16]

I mean it’s fantastic.  To be honest, I haven’t been there yet today.  I flew in.

[00:20]

You just got in.

[00:22]   

But I was just checking my Bizzabo app trying to pick out all of the…

[00:26]

Connections?

[00:28]      

Yeah, and all of the sessions tomorrow that I’m going to go to.  Looks like there’s a bunch of System 1 stuff, which is super interesting; a bunch of Big Data stuff, which is interesting.  So, yeah, it’s a really good lineup this year.

[00:38]

CTO of Measure Protocol.  Tell me a little bit about Measure Protocol.  What do you guys do?

[00:41]

So, we’re doing sampling on the blockchain.  So, we started life about 18 months ago right, I guess, at the height, of blockchain madness, of ICO madness, and started working on this idea that we just couldn’t run away from.  You know two out of three of us founders had a background in market research, had worked at Comscore and Kantar, and had another startup, which was a market research startup that we’d exited awhile ago.  And the deeper we got into blockchain, the more we just could not run away from how perfect a fit we thought that it was for this one particular use case that we knew so much about, given our history. And so, we’ve been sort of digging away at it for the past 18 months.

[01:26]

Your executive team, Ben?  Is that right?

[01:28]

Owen and Paul.

[01:30]

Owen and Paul.  Sorry about that.  And you guys have had a successful exit, which is really unique, especially in the context of blockchain since the very early stages of that whole technology.  What are you seeing as the central role or, even more specifically, the practical role of blockchain in market research? What is the problem that it’s solving?    

[01:54]

Right.  I think it’s going to end up coming on in two different phases.  When I think about what we’re doing, which is just quite literally putting sampling on the blockchain.  So, instead of a sample provider being in the middle of a researcher and a population of respondents, there’s software on a blockchain, which is not to say that we’re disintermediating all the sample companies, right?  It’s just to say that, from a technical perspective, this stuff is possible to be done in software alone. But, when I think about what we’re doing, there’s sort of three buckets of benefits: privacy, transparency, and economics.  And I think with the current state of the cryptocurrency market, the economics argument is somewhat off the table, right?

There’s this sort of really interesting, idealistic, futuristic business models that are possible when you have a cryptocurrency in the middle of these things where users become, to a certain extent, shareholders of what you are building, which is super interesting and can sort of inspire all of these accelerating positive feedback loops.  But, because of the crypto-markets now, that’s not as easily possible to get off the ground, but it certainly should be possible in the future. What we focus on today is privacy and transparency. So it really forces us to build essentially a sample company that is private by design and is… essentially has a sort of 24/7, 365-day year audit on what we’re doing.  So buyers of data and respondents can all see the providence of offers, can see payments go through, can see the validity or not of data that’s being claimed on the network and so on and so forth.

[03:33]  

I would have thought that security would have been part of the stool.

[03:38]  

I guess I bucket that under the privacy.  In fact, my talk tomorrow is about the privacy aspect.  And one of the somewhat surprising consequences of trying to build this stuff out on a blockchain protocol is that you have nowhere to put respondent data – not the data that they’re entering in surveys necessarily but when we’re doing sampling, when we’re running research, all day long we’re sort of collecting and curating and digging through demographic profile data, which is incredibly sensitive and it’s not at all the type of data you want to put on a public, immutable database, right?  So, you end up doing away with the respondent database; there’s no respondent database. And what we’ve done in our particular example is push profile data out to the edges of the network. So respondents have all of their profile data on their devices and then the challenge in building this business becomes… If you don’t have a respondent database, how do you run feasibility on a study? How do you know what the composition of the network is? How do you filter somebody into a particular study?  So, we’ve sort of come up with these baskets of cryptographic techniques to try to fish that information out, but in a way where we, as the service provider in the middle, have no access to the actual data itself. So it’s sort of privacy by design. You almost don’t have to worry about security because there’s nothing to secure. You keep all of the sensitive stuff off the blockchain.

[05:04]

The pilot project:  Tell us a little bit about that.  How did that work?

[05:08]  

So, I guess starting at the beginning of year we gathered together about a dozen clients and sample providers and research agencies and pulled a whole bunch of projects from them, cobbled together several hundred users on the system, the system which was really fresh out of the oven.  We’d kind of just baked this thing and released it to the world, and we set the thing running. And there was really three things that we were trying to do: The first one was just a technological smoke test. (Does this thing work? Does it do the things that we claim?) The second one was education for our clients, for these agencies and for the brands to try to…  because it’s a difficult thing to explain: this sort of notion of privacy, of not having a respondent database; this notion of transparency. It’s a difficult thing for somebody to just sit down and intuit, based on reading it from a paper or hearing it from somebody like me. So what we were doing was we said, “Look, let’s just run a bunch of studies for you guys and we’ll come in and we’ll show you what you get out of this, right, and we’ll show you all of the new types of data and we’ll sort of illustrate to you what lives on the blockchain, what lives off the blockchain, and why that might be beneficial.  And then, the third part of it was just to do research on research, was to see how users respond to this stuff, which was… I mean it warms my heart; it was bloody good, like the users were very, very engaged. We always think about privacy as being a hygiene factor, rather than a motivating factor. You know it doesn’t get people to show up but it might get them to be more active and to hang around longer than they would have otherwise. And so, it’s hard to say anything definitely just yet. And we’re going to publish our results in the coming weeks, but there was certainly nothing dispositive in what we did.  Really, really encouraging, and we’ve turned that into real customers and real partners right now, which we’re just lining up on the network.

[07:12]

That’s beautiful.  So, two things: one – like how do you guys get paid?  Where do you fit from a dollar perspective? Is it an existing dollar that’s been budgeted by the customer for that particular sample?  Or is it a new dollar?

[07:25]

So, today it’s probably coming out of two existing budgets.  It’s coming out of the sample budget. I mean we’re taking a technology fee today for each…

[07:36]   

Sort of analogous with the marketplace fees.

[07:38]

Yeah, yeah.  And then the other bucket that it seems to be coming out of so far is the fraud bucket, right?  We have what I think is a quite rigorous, interesting story about fraud and about validating people’s claimed profile.  And so, I think more and more we’re going to go up against the companies that are sort of taking 50 cents or a dollar off of every complete to run fingerprinting and so on.  I mean that’s not a threat; that’s just my prediction. I think we have a very good story about fraud for several different reasons. And I think there’s just a lot of survey fraud on web surveys, and the companies are spending a lot of money on it.       

[08:18]  

There was a presentation that was given a couple weeks ago by Proctor & Gamble, and she said that they had done some root-cause analysis of some research failures, and it boiled down to fraud at the respondent level.  And, when they looked under the hood, it was approximately 30%. Another great example is a friend of mine did a study with… I probably even shouldn’t say too much about it, but anyway it worked out where they asked a red herring question, “What is 1 + 1 + 4?” and as a pick list of six answers choice, of which 48% of the people got it right, which is not great.  But, anyways, you’re always going to get some level of error in data; it just seems like it shouldn’t be over half of the sample. I mean it’s exciting work that you guys are doing. So congratulations on that, and I look forward to your talk tomorrow. If someone wants to get in contact with you, how would they do that?

[09:22]

Ahh, MeasureProtocol.com and I’m on Twitter at JohnM.

[09:25]

Perfect.  You got to join our Twitter Chat.  So, MRX…

[09:30]

I see it, I see it, every other week.

[09:31]

Yeah, yeah, yeah, totally.  So, jump on there. Be a great way for other people to be able to get in contact with you.  And, of course, we’ll include this in the show notes. Thanks for being on the Happy Market Research Podcast, and I hope you enjoy the WIRe event.

[09:41]

Thank you, mate.  You too.

[09:42]  

Bye.