Today, my guest is Alex Gelman, CEO of mTAB. mTAB has a platform for integrating and analyzing data so that brands make the most informed business decisions. Prior to founding mTAB, Alex worked as business consult at McKinsey and KKR.

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mTAB: https://www.mtab.com/

[00:00:00]

Hi. I’m Jamin Brazil, and you’re listening to the Happy Market Research Podcast. Today, my guest is Alex Gelman, CEO of mTAB. MTAB has a platform for integrating and analyzing data, so that brands make the most informed business decisions. Prior to founding mTAB, Alex worked as a business consultant at McKinsey and KKR. Alex, thanks very much for being on the podcast.

[00:00:24]

Thank you so much for having me, Jamin. It’s great to be here.

[00:00:27]

So I don’t think a lot of people in the industry know much about you. I thought it would make sense to maybe look kind of at your early days. Could you tell us a little bit about your parents, and how they affected your career?

[00:00:39]

Sure. So my parents are immigrants from the former Soviet Union. They immigrated to the–to the States, and as good Soviets, they were both engineers by background. In the US, my mom was an engineer at a hospital, a plumbing and HVAC engineer, and at nights and weekends was a real estate agent, and my dad built houses. He had a small construction company where we lived, and with his bare hands and a–and a few workers, did house renovations and built houses with his bare hands.

[00:01:13]

It’s interesting–and so the entrepreneur elements of how–sort of your DNA, I guess, clearly started from them as an example.

[00:01:23]

Oh, absolutely. So hard work was always–was very much the immigrant mentality, and very much the American dream. I mean, they came over with nothing, worked hard, and were able to provide my family, my brother and I, a very lovely middle-class life. And so hard work was always drilled into us, and then math. Like very good executives, they had a clear KPI and it was one KPI and that tracked, and that KPI was our math scores. So I was–my brother and I were always pushed to have great math scores. And here’s a–here’s a–one little anecdote that you will–you’ll appreciate. They used to drive around–they used to put me and my brother in the backseat of the car, and drive to not particularly–I grew up in Long Island, right outside of New York City, and they would drive to not particularly nice areas in New York, or not very high-income, and tell us, “Would you like to live here?” And my brother and I would say, “No, no, we don’t want to live there,” and they’d say, “Well, this is where you live if you don’t do well in school.” And then they would drive–I’m not making this up–and they would drive then to, you know, the north shore of Long Island past the mansions, and say, “Would you like to live here?” And we would say, “Yes, we want to live there,” and they’d say “Well, this is where you live if you do do well in school.” And so math and hard work were always drilled into us, and now my brother runs a quantitative hedge fund and I’m the CEO of a data analysis company, so I guess it worked.

[00:02:50]

That’s so funny. My best friend is from Romania. His mother moved him and herself here when he was in seventh grade. The culture–he didn’t actually speak any English at that particular point in time, and then moving right at that middle school period, which is such an inflection point for, you know, everybody, but, you know, for him, even more so, he has that exact same mentality in terms of his work ethic, and how he has really bootstrapped–like 100% of bootstrapped his life. And, I mean, this year, he’s going to make–I can’t tell you how much, but he’s going to make a lot more money than I’m going to make, how’s that? And it’s just predicated on his work ethic. I’m hearing a lot of narrative nowadays around how the Internet has created clear access or opportunity for everyone across–and getting rid of really the socioeconomic opportunity that has traditionally existed for wealthy kids, or kids of wealthy parents, because it was a lot–in those days, it was a lot of, you know, who my parents knew, that basically got me into that job. And now, because of the Internet and having direct access to markets, it’s–you know, you’re seeing a lot of hustle coming out of kids who don’t have very much or nothing, except maybe a cell phone and Internet access.

[00:04:14]

Yeah, that–I agree with that. Look, there’s a lot of luck, too. I was lucky to have been born a white male in the United States. I was lucky to have been born with two parents who valued education and loved us. So there’s an element of–you know, you can’t deny the element of luck, but yes, the value of hard work and hustle was absolutely driven in to us at a young age, and I think today’s world makes it possible that if you do work hard, you really could–in a–in a place like the US, you could really achieve whatever you want.

[00:04:51]

For sure. So McKinsey, KKR, big deals. How did you wind up in those large consulting organizations?

[00:05:00]

So coming out of college, I knew I wanted to go to a–work at a large consulting firm, largely because I viewed my 20s as more education. So I wasn’t really looking for a job, I was looking for business boot camp. I knew I wanted to go run a business some day, and I just thought, you know, my 20s is the time to learn. Quite frankly, with both of those jobs, and I’m not going to go back and tell them this now, but, you know, they could’ve paid me nothing and I still would’ve taken them. It was just a fortunate coincidence that they paid me, largely because I was going there to learn, as I viewed my 20s as a launching pad for the rest of my career. So my first job, McKinsey, was, I just wanted to learn Business 101. I went to Dartmouth where I was a philosopher major, and economics double, but, you know, liberal arts major, didn’t know anything, and so I went to McKinsey to learn Business 101, and there I really learned the value of how to talk to the C-suite. It’s something that consultants are excellent at that market researchers actually could really learn from consultants. And then I went to KKR to learn how to talk to investors and boards and capital owners, which is a very different language than talking to the C-suite. And so those first years were really formative, and I was very fortunate to have some of the best business education in the world.

[00:06:30]

So then how did you wind up in marketing research?

[00:06:33]

So honestly, luck, random. So after KKR, I went to business school at Stanford and I started a–essentially a small private equity fund. It’s called a search fund, is the concept. But essentially what I did is I knew I wanted to run a company, but I didn’t have any good ideas on a company to start. So I figured, “Gosh, there’s some probably really great companies that are out there that are already being run, and I would love to scale them and take them to the next level, and so let’s go and buy these companies and grow them as opposed to start something from scratch.” The problem was I didn’t have the money to go buy a company. So I made a deal with essentially five of my professors and then 20 of their wealthy friends, and the deal was as follows: why don’t you guys pay me a little bit of a salary, not a lot, just enough for me to live and eat indoors, and I will go travel around America for two years, and I’m going to look for a really good company to buy. And if we find a company that we all like, you guys put up the money to buy the business, and I’m going to move there and become CEO. I was not necessarily looking at market research. I was looking at lots of different businesses. They had lots of–we had various characteristics of businesses we were looking at, and I really love data and analytics businesses, but honestly I stumbled upon mTAB, fell in love with the business, fell in love with the industry, and said, “This is it. This is the one.” And so the investors put up the money, we bought the business in May 2015, and I moved from New York to southern California, and I’m still here, three years later.

[00:08:17]

Not exactly in line with our normal conversation, but what would you see–you know, going through that process, what was like the plan B if mTAB–like, was there–was there another business that you thought, “Eh, this–if mTAB doesn’t work out, this is next in line”?

[00:08:34]

So I was towards the end of my search process. There were actually a couple of other businesses that we looked at before mTAB, and we walked away because they weren’t–for whatever reason, we decided that they weren’t the right business for us. There was no plan B after mTAB, actually. We were–we were on our last dollars, when we were working with mTAB, and I don’t know, I guess I would’ve either gotten a job, or tried something else entrepreneurial. I doubt I would’ve gotten a job. I–the entrepreneurial bug had bit me, and I was pretty set on starting something or buying something.

[00:09:12]

I–the few interactions that you and I have had inside of the industry over the last few years, I would–I would concur, from a character perspective. A CEO is a CEO, you just can’t help it.

[00:09:22]

I don’t think I’d make a very good employee. I feel bad, because I have very different expectations of my–of my teammates, but I don’t–I–Lord help the person that I have to work for, so.

[00:09:38]

Let’s talk a little bit about mTAB. What is the core offering, the value prop? And who is your target customer?

[00:09:45]

So we help market researchers analyze, visualize, warehouse their mark–all of their data. Within large Fortune 500 companies, we act as the single source of truth for the market research or consumer insights departments. We also work directly with large market research firms, as well as small market research firms, but really our target audience is the big global enterprise dealing with lots of disparate market research data, and needing a way to get their hands around it.

[00:10:20]

This goes back a few years, about six, but I was helping Visa, I was on a small committee, working with the CMO at the time, on their data strategy. And through the discovery process, I identified that they had 13 NPS studies going on simultaneously, and the end result of that was, I mean, obviously, costly, but more impactfully was that you’re getting variance on the data by data source, and because there wasn’t this complete view of–or single source of truth, it was creating confusion in terms of, you know, what companies–what the company should actually do. Is that–is that a good example of a company that should’ve used you at that point in time?

[00:11:11]

Oh my goodness, that’s a perfect example, and you can come work for us as a–as a head of marketing, if this podcast–if this podcast thing doesn’t work out for you, Jamin. I mean, that’s spot-on. So when we were doing diligence on mTAB, I’m a–I’m a pretty diligent person, and we met with about 60 customers before doing the acquisition. And when I asked, “Why do you use mTAB?” and I kept asking “Why do you use mTAB?” to customers, and they–and here was the modal response, which is: The data is always right. Before mTAB, there’s spreadsheets sitting on 13 different computers, and you know the intern last year did something with the variables, but you forgot what exactly it was, and the Japan file is sitting over there and it’s not connecting to the Argentina file for this reason, and it’s a disaster, and nobody trusts the numbers. Once it goes into mTAB, it is–it is fact, and so–that’s what folks need, they need the single source of truth. They can’t have SPSS and Excel files on different people’s desktops and sitting in different data vendors’ proprietary tools. So what we do is we suck up all of that data, all the regional data and all the trended data, and all the different studies from data vendors, and we put it into one easy-to-use tool, so that there’s no debate about what the numbers are. And you can move onto the more interesting things like analysis and insights and storytelling, which is what market researchers ought to be doing.

[00:12:47]

So the–so there’s a couple things I want to piggyback on. I don’t want to lose sight of the importance of story, but before I get there, I viscerally connect to that. I know that, you know, as a primary researcher even back in the ’90s, we would conduct research, and then you would wind up with–you know, you’d of course do a bunch of analytics on that data, and if you have multiple analysts going through it, or even yourself and then some time passes, and you go back to reference, “Oh, which one is my–is the correct SPSS file?” or whatever data format you’re using at the time, it can get–confusing is an understatement, and there’s a lot of rework and even risk associated with using the incorrect or not-final data file.

[00:13:30]

Oh, absolutely. And we make sure that–that’s one of the services we provide, is that once a file goes up into mTAB, that’s it, that’s the final file. Which is why we are so rigorous about doing lots of process checks here, is we have to have 100% accuracy, because once it’s in mTAB, it has to be right, because that’s the value proposition that we’re selling to our clients.

[00:13:51]

The other part that you talked about is the story. I’ve heard this a lot lately, most recently by Rozhie [ph] of LinkedIn, and then Edwin Wong of Buzzfeed, story trumps numbers. Not in the way that–you have to have the numbers, and the numbers have to be right, nobody’s saying anything different. But the way that the people connect with the–the people being inside of the organization–connect with those numbers isn’t through a pie chart, it is through a narrative that is being built out in the organization, and that the more compelling that story, the more the organization is willing to adopt it and then make the necessary changes. Are you seeing in your customers these types of trends?

[00:14:35]

Absolutely. That’s why they–that’s why they come to us, is they don’t want to spend any more time mucking around with the data. They realize that that is something they should outsource to somebody else. They should outsource the merging together of data files, and they should be the ones focused on building out the story. And so when our customers interact with our software, they already–they–in an interactive dashboard, they press a few buttons, they export it to PowerPoint–they have a native PowerPoint–and they just build onto that story right away. And so when you look at–when you read something like the Grit Report, and you look at the amount of time that market researchers are spending cleaning, shaping data, and building PowerPoint slides, it is crazy. It’s crazy. They need to be thinking and developing new experiments and syndicating the story, writing the story and then syndicating it out throughout the organization, not mucking with data and building PowerPoint slides. And unfortunately too many market researchers are still doing that, because they don’t have a good grasp on the data, because they’re using outdated tools and methods.

[00:15:45]

That’s so funny. I’m really believing that that’s such an important message for market researchers to hear right now, and that is historically we have spent between 80 and 90% of our time simply doing research logistics, and now we’re at the stage where we need to be inverting that, and spending maybe 20% of the time or less on the logistics, and a lot more in the added value and uncovering the why, and then the–and then helping the client develop that story that is compelling, and that can be adopted inside of the organization.

[00:16:19]

Well, just [INAUDIBLE] table stakes now. It’s just table stakes, and the tools are just making it easier and easier that the C-suite doesn’t want to hear, “Oh, we spent a lot of time on logistics.” They just want to know the answer.

[00:16:32]

Exactly. So what three lessons did you learn as a management consultant that helped you–are helping you with the strategy of mTAB?

[00:16:41]

So it’s funny that you asked the question that way, because as a management consultant, I’ve been [INAUDIBLE] to create buckets, and typically I create buckets of threes, so my team always makes fun of me, because I always say, “There’s three things here.” So what three lessons did I learn? Well, you know, this is one that I thought about–it’s interesting you ask that question, because I’ve been thinking about this a lot for the last three years, because when I was a management consultant, we’d often come into companies, and we’d–there’d always be–there would often be comments of, “That’s not a new answer. Why’d they hire McKinsey? Why’d they hire Bain or BCG? They should’ve just asked us. You know, we knew that answer,” and internal departments, very often the market research department, would get frustrated that management hired these consultants to come in for millions of dollars to give them the answer that the market research department already had. And they thought, “Oh, you know, this is–this is–this is just garbage and nonsense that they’re hiring the consultants.” And, you know, I actually feel bad for the researchers, because they’re kind of right. They’re–they had the data all along, they had the answer all along, but they weren’t being listened to. So I’ve been spending a lot of time thinking about, “What did we do–what did I do as a management consultant, what did we do at McKinsey, that we can take some of that and infuse it into the mTAB product, to empower market researchers to have a seat at the boardroom table, just the way the consultants do?” So there were–there are three things that I think that consultants do really well that market researchers can learn from, and that we’ve tried to take and infuse into the mTAB product. So number one, storytelling. So we talked a little bit about this, but I think it really is worth mentioning again. Consultants don’t just come in and say, “Here’s your data.” They come in, and they say, what was the situation, what’s the complication, what’s the resolution? Typical structure of a story. And they give an answer. So they don’t just deliver a 180-page deck that’s full of data and says, what are all the respondents said, and every variable by every single cut. They pull a select slide, and they build out and they tell a story. Number two, they’re hypothesis-driven. So I find that too many market researchers boil the ocean. And by that I mean, they get a data file, and they go, “What does the data file say?” Consultants who are hired at obscene rates for 10-week periods don’t have time to do that. So instead they come in and they say, “Here’s a hypothesis I have, and here’s what I’m going to test,” and they still go about it in a–in a scientific way. They run a–they have a hypothesis, and they test it, and if they–if the hypothesis fails, they’ll reject it, and they’ll take a new one, but they don’t boil the ocean and say, “What does the data say?” but they run tests. And the third thing I think that consultants do really well that market researchers can learn from is they break down silos. When you go and you hire a Bain or a BCG or a McKinsey, they’re flying around the entire organization. You know, they have access to all the data, and they have access to every department, whereas market researchers, I’m still surprised by how siloed they are, and even within the market research department, you have one person that’s doing–working with syndicated research data one, and another one is working with syndicated research data two, and a third one that’s working with proprietary data, and when you ask them, “Well, how are you looking at your–the cohesive set of knowledge?” they go, “Well, that’s not my job. I’m only the Cantor data person, or the GFK data person, or the Qualtrics expert. I don’t look at the cohesive set of knowledge.” And so I think market researchers are doing themselves a disservice. So what we’ve done is try to infuse some of that value that consultants bring into the mTAB product to empower market researchers to be really internal consultants within their organizations. So all of the hard work that is the table stakes that we talked about before, we take that off of clients’ hands. We have a–we have an analysis and insights department that will bring together lots of different data sets from across time and across geography and across different data vendors. We’ll put it into one tool, we’ll visualize it, and we’ll do it across all of the departments and all the sets of data, so that a market researcher can come in and just say, “What do we know about X?” and see the answer across the entire suite of knowledge, and then instantly, at their fingertips, be able to export a PowerPoint slide that’s already designed for them. That really is the power of what we’re trying–what we’re trying to do here, which is really empower the market researcher, because they are–they’re such an important and critical voice within the org–within these larger organizations, and it’s a voice that I think has gone a little bit quiet as there’s louder people out there shouting, but it’s often that quiet knowledgeable voice that has the right answer. So it’s our goal to empower the market researcher to raise their voice and be heard throughout their organization.

[00:21:54]

It’s a lot of context that’s missing from primary market research that you’re providing the customer. So when I think about all the projects that I’ve done, the thousands that–and that’s just because I’m old–that I’ve done, most of the time, I am dealing with, to your point, a siloed dataset from which I then think come up with, derive, and answer. But you’re absolutely right–God, it’s true, the millions of dollars I’ve paid consultants to answer questions for me, and they’ve only polled 60 industry experts or what have you, as opposed to the thousands that you might see in a normal study, and they’re coming up with meaningful–and the way that they’re doing that is this triangulation of context, where the business is right now, and then the primary research. So it is the case that they’re incorporating this syndicated data, but they’re also doing–adding the storytelling and qualitative elements on top of it. And I think you’re absolutely right, there’s a ton that we can learn as researchers to help uncover and address the why, and really make impact inside of the organization as opposed to being more in this defensive role that I think a lot of researchers find themselves today, where they’re trying to be the protectors of the methodology.

[00:23:14]

Our goal is to empower researchers to go on the offense. Our most impressive clients, what they’ll do is suck in various forms of syndicated data, and not just one set, but two or three sets, so that they’re the experts. There’s so many market researchers I ask, and I say, “How are you analyzing and double-checking the data from your market research provider?” And they go, “Oh, I ask them for cuts of the data.” And they’ll wait a week for a cut of the data from their syndicated data provider. That’s crazy. You have to–you have to have your hands around the data. So our best clients, they’ll suck in data from three different market researchers, then they’ll link that data set to their front-end survey, whatever they use, let’s say Qualtrics, and then they’ll pull in their proprietary data, just as you said, and overlay that, and then they’ll have a view of, “OK, with all of the data we have, let’s triangulate from the syndicated data to our own proprietary data to our sales and marketing data, what’s actually happening.” And those are the most impressive market researchers I see, and they–we have some of those as our clients, and those are the ones I’m most impressed by.

[00:24:20]

So I always end the interview with an opportunity for you to either inform the audience on something that you’ve got, like an offering that you have, that you’re particularly excited about, or, you know, some other key insight. So what is it that mTAB has to offer right now that can add value to brands?

[00:24:38]

I think we talked a bit about that.

[00:24:40]

I think you might be right.

[00:24:43]

I think–I think–I think we talked a bit about that, but I think that two of the more–the bigger things that we’re working on right now, we’re really spending a lot of time on our data visualization platform. We’re trying to make it easier and easier and easier for people to get to the numbers. But in a way, they still have the feeling that the data is accurate, and they can still work with complex data. There’s too many visualization platforms out there that A, are just not suited for market research, or B, just dumb it down too much, and aren’t really sophisticated enough to deal with 22 geographies and 10 years of history and four different data vendors. So we’re building on an incredibly sophisticated data visualization platform that still is incredibly intuitive to use. That’s one of the things we’re most excited about, and on the back end side we’re building out more and more connectors to this front-end survey tools. So whether you’re using a Qualtrics or a Decipher or a Confirmit or SurveyMonkey or just have raw SPSS files, we don’t care. We want you to be able to plug in all of your sources of data and get it into your data warehouse so you can operate from that single source of truth.

[00:25:57]

Interesting. My guest today has been Alex Gelman, CEO of mTAB. Alex, thank you so much for joining me today.

[00:26:03]

Thank you, Jamin.

[00:26:05]

Have a great day, and thank you, everybody who’s listening. How are the levels? Testing, testing, testing. Yeah? Are we recording? Hi. I’m Jamin Brazil, and you’re listening to the Happy Market Research Podcast. Today, my guest is Alex Gelman, CEO of mTAB. MTAB has a platform for integrating and analyzing data, so that brands make the most informed business decisions. Prior to founding mTAB, Alex worked as a business consultant for McKinsey and KKR. Shit. There are–today, my guest is Alex Gelman, CEO of mTAB. MTAB has a platform for integrating and analyzing data, so that brands make the most informed business decisions. Prior to founding mTAB, Alex worked as a business consultant at McKinsey and KRR. Alex, thanks for being on the podcast today. Hi, I’m Jamin Brazil, and you’re listen-