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I have as my guest today Melanie Courtright, EVP of Global Research Science at Research Now SSI, the global leader in digital market research and data services.

Thanks to the merger of the two market research data leaders Research Now and SSI at the end of 2017, the company has one of the world’s largest first-party data assets built on permissioned research data. With a combined history of decades, the company has developed its core of data through a variety of panels, such as eRewards and the Opinionology panels, just to mention a couple. SSI acquired the Opinionology business in 2011.  And eRewards, an industry pioneer of online research data established in 1999, acquired Research Now and became Research Now Group in 2014. Since the merger, Research Now SSI is something of a standard setter for data quality.


[00:00:00]

Hi. I’m Jamin Brazil. And you’re listening to the Happy Market Research podcast. I have as my guest today Melanie Courtright, EVP of global research science at Research Now SSI, the global leader in digital market research and data services. Thanks to the merger of the two market research data leaders, Research Now and SSI at the end of 2017 the company has one of the world’s largest first-party data assets built on permission to research data. Since the merger, Research Now SSI is something of a standard for market research data quality. Melanie has spent more than two decades in the consumer insights industry and is a leading voice in market research for trends and the next generation of data collection. Thank you Melanie for joining us today.

[00:00:48]

It’s my pleasure to be here. Thank you for having me.

[00:00:50]

So I’m super-excited about our conversation. You and I have operated in the same circles for two decades and known each other for I think about half that. Your work at Research Now and SSI has certainly put you in the forefront of tech in the market research space focusing specifically on online and then later mobile and social today. On top of that you’ve written some award-winning work that has informed our industry. But before all the nerd stuff, I think it would b really helpful for our audience if you would talk just a little bit about your background and how you wound up in market research.

[00:01:28]

Sure. That’s a fun story. I didn’t actually grow up wanting to be a market researcher. I’m one of those people who found my way into market research. I was actually planning to be a professional vocalist. My formal education is in languages and music. I speak Spanish and I learned Persian Farsi while I was in the military. I also read biblical Greek. I was a first soprano. I’m still very active in singing. And if you were to be in my car on my way home any day you would hear me singing at the top of my lungs all the way to and from work. But – so after I left the military, I started doing some research. I joined Texas Instruments and I worked on a Department of Defense program for Texas Instruments. And then after that I left when my third child was born. I began working from home doing transcription and translation work for a local research firm. I spent years with that firm translating, cleaning, and coding verbatim comments from employer and customer feedback programs. It was during that time that I really learned a lot about the needs of employees and the needs of consumers translating and transcribing their words into a consumable coding that companies could use. So I spent a lot of time just getting to know the hearts and minds of people all over the world through that couple of years spent with verbatim comments. And from there I just grew in my love of research and in my roles across all the companies I’ve been at.

[00:02:52]

It’s so funny. You know I started out – I call it the bells of market research. So I started out doing mall intercepts. For those that don’t know, those are the people that you all loved that are in malls that have clipboards with pieces of paper on them and they intercept you asking if you have ten minutes to answer some questions. It was hard but it’s funny because having that as my initial point of reference in this space gave me great insight in terms of opportunities of automation or how we could introduce technology to solve some material problems, which is why I did my first online survey in 1996. So I think that entry-level experience is super-beneficial for leadership.

[00:03:37]

Yeah, and even as an executive now one of the things I’ve tried to make sure I do is stay close to consumers. The best way to help our brands and clients be close to their consumers is by being close to consumers ourselves, spend time following their trends, knowing what devices they’re using. There’s nothing more important than just really understanding consumers if you want to help clients make decisions about them.

[00:03:59]

Yeah, that’s the truth of it. So let’s talk a little bit about your role. It’s certainly expanded and I think most recently into the EVP realm of global research at Research Now SSI. So what does that mean? What are you in charge of?

[00:04:12]

Well the global research science role is actually new to Research Now SSI. It was established after the two companies merged. I’m really excited about this role. My team’s responsible for reviewing and approving all of the methodologies that under guard our products and services. If you’re not familiar with methodology, methodology to me is just how we make sure that the data we provide represents the population our clients are trying to make a decision about. And so one of our most important focuses right now is creating a combined company sample plan across our panels and measuring our ability to hit benchmarks. Research Now SSI is showing their commitment to quality and methodology by investing in a team of experts that will approve everything we do as a company along the data services spectrum. It’s a great role, a great team. Some of the smartest people work in this group and I am honored to have the role at the company.

[00:05:05]

That’s fantastic. Well congratulations on that. I want to dig in a little bit deeper here. Do you have somebody you want to highlight?

[00:05:12]

The whole team is filled with rock stars. So on the knowledge side is Jackie Lorch. Everybody knows Jackie Lorch and she is an SMR representative like I am. There’s also Pete Cape. They call him doctor Pete. He writes for some of the industry articles and magazines over in the UK. You’ve got Keith Phillips and that’s just on the knowledge side. On the actual consulting side we have Eric Levy, and then we have a whole data quality team who handles all data quality questions. It’s an amazing team of some of the smartest people in the business and they all work for Research Now SSI trying to make sure that everything we do is top-notch.

[00:05:52]

That’s awesome. So since I started in 2000, that’s my really when I spun off out of primary research and into technology empowerment for research. Seven years later, fast forward, Kristen Luck sold her company and it seemed like a great time for us to join forces. And as you know, she’s been – is the founder of Women In Research or WIRe, instrumental in connecting women inside of our community so that they have increased opportunities and education. What is it like to be a high-profile woman in the market research industry and then do you see any challenges, anything you’d like to share on that front?

[00:06:34]

I mean first I would say I think it’s the same as being a woman executive in any industry. It can be really rewarding and it can also be very challenging. Our industry is blessed to have a great set of women leaders across the spectrum of roles and responsibilities. And we have some really great gender equality initiatives that make me proud and I’m excited to be a part of. But it can also be a little bit lonely and daunting. There’s still in our industry more men in the upper echelon than there are women and it’s funny since there are so many women in our industry. Then I would say that the challenges are just around – there are still a lot of places where your role – people try to define what your role should be based on your gender. They try to put you in a box as a woman, a sort of pre-defined box about what your role should be. And I would say honestly that I think I’ve spent my entire career sort of breaking boxes. I am the only one who gets to decide what my limits are and what my roles are and what my boundaries are. And I encourage women to do that for themselves. Don’t let anyone else tell you what you can or cannot be. And the only other thing I would say is women are often required to act like the role they want to be before they’re given the role. Men sometimes have some assumed leadership capabilities and they’re often given roles that they can kind of grow into. Women usually have to prove themselves before they get those roles and so my encouragement to women is to start acting like the role you want in three years now. So if you want to be at the higher level in three years, start acting like you’re at that higher level now and prove to everyone around you can do that role. Start doing it now. Think big, plan ahead, and don’t let anybody give you any boundaries.

[00:08:17]

That’s super-smart. Thank you for that. Did that position get informed by your military service?

[00:08:23]

Absolutely. I will say in the military I learned how to be comfortable working around men. I learned how to challenge stereotypes and challenge norms. It’s funny. Before I joined the military, I had never actually picked up a weapon. And when I picked up a weapon for the first time there were a lot of people who said well she can’t shoot. She’s a girl. She’s not going to be any good at it. She’s a girl. And I became the first woman in the military to get a perfect score on marksmanship. The army actually gave me a plaque and a trophy and the army does not give trophies. But I just – I never let anybody tell me what I can or cannot do. I never let the noise in my head become reality to me. I set my own boundaries and I broke stereotypes. And I learned how to do that in the military. I also learned discipline in the military though. There’s this thing called the art of discipline is about practicing and exercising and honing your talents so that when you’re under pressure, you can rely on muscle memory. And I do that all the way to today in every aspect of my career. There are so many times when I’m in a nervous or anxious situation or I’m speaking or I have to make a quick decision and I need to be able to rely on muscle memory. And so that discipline and that practice and that exercise came from my military experience.

[00:09:35]

Unbelievable. Thank you very much for sharing that. So I – being an old guy, I was around in 1999 when your rewards started and it was interesting because your rewards created this profoundly strongly brand around data quality, this huge point of differentiation in the market. Additionally, you guys were really disciplined on saying no to projects that were bad fits against your panel. How has research now guarded that sample quality given the various mergers and acquisitions?

[00:10:08]

Well so the fact that the merged company, Research Now SSI is investing in such a large team of research science experts to tell you that we still take this very, very seriously and it’s because we look across the entire spectrum of what quality means. Quality starts all the way from the way you recruit, the way you engage, the way you rewards. It’s definitely about the exercises that you ask people to complete, it’s about really good member experiences, but it’s also about scale and it’s about knowing when to say no and it’s about representativeness. Quality can certainly mean like in survey data quality measures but it also really means representativeness. And we look at all of that. So our biggest concerns through the recent merger have just been data stability and data representativeness. We spent an awful lot of time creating a new reliability measure that you’ll be hearing more about soon. And we’re still completely invested in quality.

[00:11:03]

When you think about representativeness, I think most people would default to national rep, etc., etc. But are you also incorporating an origination source in that?

[00:11:13]

We are. So – and the reason that matters is that it’s all about sample frame. If you’re working with a source that is small in frame that’s only recruiting from a few places it can be very difficult for that frame to represent a large population. So Research Now SSI recruits in every way imaginable. And we look at the source and the quality of every one of our partners and every one of our recruiting campaigns. But when you put all of those together, all of the loyalty partners, all of the gaming partners, all of the mobile channels and the API partners all together at scale, almost all of the coverage bias that my research can be known for are erased and the data quickly falls into norms and benchmarks. So we now know that we can hit external benchmarks on ailments and on consumer behaviors and all sorts of different ailments because of our scale. So we’re taking the quality message a couple steps further.

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Got it. The scale part I think is really an important point. It offers you such a competitive advantage in the marketplace. There has been an increase in sample APIs or blended or whatever you want to call it. My concern around that is sometimes we can lose – by automating the process we can lose the connection with the origination source, which may or may not have an impact on the data. I know that there could be ways to address that but I’ll stop talking. Everyone wants to hear you talk about this.

[00:12:45]

But what it comes down to is scale matters but not only scale, but the ability to hold the sample frame consistent over time. You really have to be able to have the financial commitment to maintain long-term relationships with your partners and with your members and be able to hold a really consistent sample frame. Broad, diverse, and consistent is the only way you get to this every day you could deliver accurate data. Lots and lots of members so that if that member A is used in survey A, you have somebody just like member A who can take survey B.

[00:13:20]

That’s right.

[00:13:21]

That kind of really broad scale, not only of the survey participants but of the surveys themselves so that technology isn’t adding any bias because of the types of surveys that are being conducted. So the scale matters in terms of your financial resources to maintain long relationships, in terms of your access to people, and broadly diverse people, and in terms of the surveys that you have in your system so that there’s no bias there either. It’s all about every layer of bias and taking it out through scale.

[00:13:50]

So over the last decade, we’ve had a couple of market research misses I would say. And one of the things I think that we were big on is the race to mobile adoption as a viable survey data collection type. From your perspective, what do you see as some of the bigger misses of the market research industry over the last decade?

[00:14:09]

Well I have – I definitely have one and I think that that is developing and adopting an explicit measure of the accuracy of our data, but really specific when measuring data quality about measuring in-survey data quality about speeding and sufficing. And that’s interesting. But you can have a perfect data set that doesn’t accurately represent any population that you’re trying to make a decision about. And we have not yet developed and adopted this really explicit measure about the accuracy of the data. So this is something that Research Now SSI and my research science team are very committed to. And we’re going to be sharing things with the industry very soon to help them understand how to know for sure if the data is accurate for decision-making or if it’s just pretty data.

[00:14:58]

Oh, that’s super-interesting. I was going to do a white paper. I just kicking the can down the road between Q and A surveys. At Decipher we built what’s called survey stress test, which is just an automated survey populator. It’s like a bot for surveys. And again, we just used it to populate data to make sure that we’re hitting all the skit patterns and quotas were processing correctly. It’s just a shortcut, right. I’ve always wondered how much different that random generated sample would be from – a very inexpensive sample that you could acquire in the open market exchanges today but anyway that’s super-interesting. So now kind of thinking forward more what does the next three years hold for us? What are the trends?

[00:15:43]

Well I mean so first I’ll say our industry doesn’t change super-quickly. We all know that. And three years isn’t that far out.

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OK.

[00:15:50]

There are a couple of things I’m really certain about though. One, in the next three years I do think that we’ll see important progress on the connection of data across the marketing spectrum from product development to marketing activation. And the second one is I think we’ll see more technology firms coming and joining us from outside our industry. On the data front, like we really are beginning to see opinion data merged with first-party data, second-party data, third-party data. It’s all coming together to tell really long-tailed data sets. We have clients where we’re matching our panel to their client list and more opinion transaction data. We’re also bringing that second-party data. We’re also bringing in purchase data and Acxiom data and Experian data and behavioral data, Live Ramp, Drawbridge. We’re bringing in all these really great data sets to tell these really cool stories and there’s all the cookie data on top of that. These data platforms are coming in and you’re going to see some very interesting case studies over the next couple years that say that this isn’t just a cool idea. It’s being used in practice. It is being used to make very fast and more comprehensive decisions. I am fascinated by that. Research Now is hiring data scientists and we’re using data platforms and ecosystems that we didn’t use a couple years ago and we’ll be even further a couple of years from now.

[00:17:11]

Yeah. I mean gosh, let’s unpack that a little bit. Market research as we know as an industry has been fairly flat in context of just overall global spend. In fact, in some cases I’ve seen articles where it’s been decreasing on a year-over-year basis over the last decade. So in that world, and at the same time, you’ve got literally an explosion of data whether it’s behavioral or transactional or whatever that exists on each one of us. So market research has been kind of stuck in this obvious place of well how do we relate to all this other data, which used to be in our realm of knowledge because at the end of the day, market research is one thing, which we are a facilitator of a conversation. It’s just a really complex conversation. And then we analyze and answer in form whatever the business question is that was originally asked. And I think the point that you’re making about the integration of technologies developed outside of the market research space is spot freaking on. The role of technology either is to entertain or make things faster, better. And that’s where on Twitter you saw my recent – this is about I guess three weeks ago, Winnie Murphy and AMA coproduced a paper on the role of market research. His thesis being that market research needs to be the keepers of why. And I think that’s really interesting and correct. But the problem in that is the way that we monetize what we do for a living, it’s like literally 60 percent of the cost structure is inside just the facilitation or the logistics of gathering the data. And you have third-party, whether it’s like integrations into WordPress or even into PowerPoint. Recently I got a survey in PowerPoint. It was a basic NPS survey, which I thought was hilarious. So you’ve got this complete democratization of what I’ll call traditional research being then integrated into systems that consumers are using every day that never even touch market research. And then the other part that’s super-interesting is how artificial intelligence is allowing us, and other things like sentiment analysis and NLP and whatever are allowing us to process qualitative what used to be a synchronous data collection approach, qualitative data and then process that at scale. So you really have quantitative outcomes of that space. And one of the – I’m thinking of a couple different start-ups I’m consulting for right now, their big problem is just don’t know how to pay for it because it doesn’t fit qualitative and it doesn’t fit – it’s not a survey and it’s not a focus group. It’s a focus group at scale or what have you and that’s confusing. So do I not need a survey anymore. So anyway, yeah, the technology is having a big impact on the role of market research in today’s insights.

[00:20:01]

It is. And I’m certainly a believer that market research should be the keeper of why but I also think that we need to be the keeper of what. We’ve relied heavily on participants to tell us through feats of memory, the whats, what have they purchase, when did they purchase it to gather all the data from them from their minds. And that’s a very challenging ask of participants. So we’re getting much better about pulling in the whats, the behavioral whats, the purchase data whats from other sources and then being able to really focus our surveys on the why behind the whats that we can observe. And that is exciting. It’s also exciting for me because there’s still a lot of methodology that goes into doing that well. A data set that’s big doesn’t again, mean a data set that’s representative and a data set that’s truth. So there’s still an awful lot of methodology that needs to go into this but it’s really coming together and tapping into working dollars like it’s never done before and getting the attention of the CMOs and the CEOs. So it’s an exciting time. And that leads me to that second thing I was pretty certain about, which is because our industry is sort of extending and expanding, it’s becoming attractive to some of the other technology companies that are in other adjacent industries. And so I think we’re going to see more external firms offering services like security and identification and even financial and technology products and companies that are coming into our space, coming up alongside of us and we’ll learn from them and they’ll learn from us. And we’ll just get bigger together.

[00:21:32]

That’s super-interesting. Well, those are all of my questions today. Did you have anything else you wanted to highlight that’s coming up that you want the listeners to know about Research Now and SSI?

[00:21:41]

Well in terms of my day job, the research science center, we have launched the research science center. The research science center is going to be a resource for the industry. One of the things I’ve heard quite a bit recently is that a lot of the conferences have stopped presenting deep methodological papers on things like sample frame and router design and how to take a tracker and completely turn it on its head and add all these other data sources and make it mobile-friendly. So we’ve taken that to heart and we’ve created this research science center and it’s going to be the go-to place. We’re not just going to have it be about Research Now SSI thoughts and opinions; we’re going to really expand it to the smartest people in the industry. So watch for more on that.

[00:22:26]

If you want to call it Jamin Brazil, that’s OK.

[00:22:34]

I think that’s taken.

[00:22:35]

My guest today has been Melanie Courtright, executive vice president of global research at Research Now SSI. Melanie, thank you so much for your time today.