Sebastian (00:02):

You are listening to the Insightful Connections podcast. Our guest today is Mary Mathes. Mary is Director of Data Insights at Alpha Diver. Founded in 2011, alpha Diver is an insights and consulting firm that applies decision science to drive consumer interest and action. Unlike other insight firms, they're psychologists, neuroscientists, and strategists use a model-based approach, grounded in neuroscience to guide leading brands, retailers, and the Wall Street analyst community to more deeply understand and predict marketplace behavior in ways proven to help clients drive double digit brand growth via strategy and activation. Prior to joining Alpha Diver, Mary was an analytic methodologist for the US government, and prior to that she was an account manager for Nielsen basis. Mary, thank you so much for being on the podcast today.

Mary (00:45):

Happy to be here. Thanks for having me.

Sebastian (01:09):

So question that I always like to start with, and I think in your case it's gonna have a really interesting answer, is how you got into market research originally and how does that help explain where you are today?

Mary (01:20):

Well, I, as far back as in high school, I think I had narrowed in on that I wanted to do something in business is my focus, you know, for undergrad, you know, I took an introductory marketing course, I took introductory accounting courses, et cetera. And then when I got to Notre Dame for undergrad and got into the business program, one of the required classes was the market research course. And as part of the class, we were put in groups and given a real world market research question or problem that some group, either, you know, on campus or in the local South Bend community was trying to solve. And our task was to figure out how would you use market research to help him answer this question, address this business problem, et cetera. And my group was working with St. Michael's Laundry, which is like the on-campus laundry service that primarily was functions to, you know, do students laundry for them.

Mary (02:10):

But they brought us this question around, you know, you know, we're right here on campus, we have dry cleaning, all of this other stuff, like why are more faculty and staff not availing themselves of our business? How do we grow that part of this business? So we crafted a survey that could be distributed to faculty and staff on campus around were they even aware that it was there, did they not? Like why would they use it, not use it, et cetera. And we all, you know, soft launched it and tested it amongst a few, you know, staff and faculty members that we each knew and kind of got some basic data, put together this report, et cetera. And that was really where we had fulfilled the obligation of the project. It, it was, we had done what we needed to do, but afterward our group actually went over and had a meeting with the people that ran the laundry service and like really talked about what we had found and like, here, if you really wanted to use this survey, like here's how you could do it and here's what you, how you'd wanna analyze the results and all that.

Mary (02:58):

And our professor tagged along to kind of help out and offer other commentary in that meeting afterward. He said, you know, in all the times I've been teaching this class, I've never seen a group do that. I've never seen anybody like really follow up and okay, this was a project, but I like, would they actually use this and how could we make this helpful to them? And he thought that was pretty cool. And of course we got extra credit, which, you know, at the time was, was meaningful. But I think kind of helped solidify like, yeah, I think this is really interesting and like, there's business questions and problems here that can be answered by getting data and I, I know your focus is more the qual space. You know, I've tended to work more in the quant space, but bringing the two together as what, you know, ways to solve problems.

Mary (03:39):

And that was kind of the start of it. And then I ended up moving here to Cincinnati originally and starting with Nielsen Basey right out of undergrad and was their form five and a half years or so, you know, started out as a, you know, a baby analyst and then, and moved my way up learning their approach and forecasting and a lot of quantitative analysis techniques. And, and then have moved around a couple of places since then to where we are now. You know, as you know, here at Alpha Diver back in Cincinnati after almost a decade away between going to grad school and spending some time in Washington DC I'm an analyst by nature and that's been the red thread through all of my roles and responsibilities. I'd say since then is there's finding the story and the data and figuring out how we answer the question and what it all means and what we're supposed to do about it.

Sebastian (04:24):

Doing a bit of background for this interview. Mm-Hmm. I found a, an article that you'd written sort of about how your experience, as correct me if I'm getting it wrong, but as an intelligence analyst Mm-Hmm. <Affirmative>, you know, help sort of inform the work that you do for your clients, you know, today at Alpha Diver. I'm curious if you could tell me a little bit more about your background in that space.

Mary (04:42):

Sure. So I moved on from Nielsen the end of 2009, just to remind everyone, financial crisis, it happened in 20 2008. A lot of people were moving around and leaving for a variety of reasons. And I was kind of at a point of, all right, this has been good, it's been interesting, I've learned a lot here, but I feel like I'm ready to maybe do something else. And I feel like I made, you know, maybe it's time to go to grad school. And I quickly ruled out an MBA because someone had given me the piece of advice of, well you already have a degree in business so if you're going to go get another degree, why not study something you haven't studied yet? And that made sense to me. So I went and got a master's in international relations instead through Creighton University, which ended up being really a feeder school to a lot of the, the intelligence community in Washington DC There's a lot of students that we have air off at Air Force Base is also close by.

Mary (05:34):

So you have a lot of military folks there, et cetera. So there's, there's a more logical than you might think tie in with, you know, intelligence work and wanting to get into that space, et cetera. And through a series of internships, first one for the State department and then another one in DC in the intel space, I found myself out there doing a very different kind of analysis for about seven years or so. And for most of that time I was what they called an analytic methodologist. So I was still able to use a lot of data Oh. And do some research on research and some, and you know, my background and understanding public opinion work and surveys, you know, was useful in a couple of different ways for helping other analysts understand what's a good poll from a bad poll if they're wanted to use something as a source.

Mary (06:20):

You know, <laugh>, we also learning that various countries have various ways of reporting about things like election polls and, you know, making a bigger deal out of very close numbers than perhaps they should. 'cause There's this thing called margin of error that we all know about. But if you're not somebody that's playing with data every day, you know, you might think that one percentage point difference really means a lot more than it does. So helping them put things in context, stuff like that. But really I think the big thing that it teaches you is it's just so what I, as my colleague Siggy puts it, it's not enough just to figure out what happened or why it happened, but the last part of any piece you write or anything you do really has to be about, so what does it mean or why should we care and what could we do about it?

Mary (07:03):

Those second and third order implications of things and really thinking about that and using that in my work today, you know, I I really try to avoid writing a headline that's just 83% of Segment X said this, you know, suggesting that they, you know, that blah, blah blah, blah. Trying to draw it out to, okay, and I'm pointing this out to you because this is why you should care. This is why this is a useful piece of information for you to have and what you might do about it. And making sure that I always think about that I think has been really beneficial and my work and you know, in the work I do for clients and with our team. And you know, I think the other piece of it too is learning to be comfortable looking at a lot of different sources of information.

Mary (07:41):

Not having to only rely on, well we must go out and collect the data. That's the only way we're going to know the answer. This is an audio format, but I'm sitting here drinking out of a mug that Cheekly calls me the world's best Googler <laugh> because I, you know, you do develop a skill of like finding information and thinking about different ways to search for things. And that is something that I still use today too. I still spend part of my day reading traffic as I call it, where I'm following various, you know, newsletters in the market research space, in the space that our clients are playing in and following. Like what's going on in the news about the brands that we're covering, the brands we work with, brands we'd like to work with, et cetera. And making sure that I am in the know and I can go and tap into other sources of research beyond just what we're doing to really make it Sure it's a full well fleshed out story.

Sebastian (08:29):

Yeah, that's so interesting to me. It reminds me a little bit about a comment that I, I heard Reid Kiff, the CEO of se go make an interview recently. Mm-Hmm. Where, you know, one of the things that he would like to see the industry do more of is to embrace alternative and diverse sources of data rather than always necessarily defaulting to arguing for our particular data silo. I think that's really interesting and that seems like a, a really important way to prove the impact of what you're doing for your clients.

Mary (08:59):

Absolutely. You know, you reminded me of another article that I wrote for quirks. It's been several years ago now, but really using this anecdote that we kind of floated around when I was in DC and in the policy space around. And I think it's a good analogy for, you know, the way that we work, that there was this rumor apparently that, and this was like back in the Soviet days and long ago, but you know, that Russia had this extreme focus and like had missiles trained on this building that was in the center of the Pentagon. So like the Pentagon is actually, it's a, it's a Pentagon obviously, but there's a center courtyard in the middle of it. It's actually like open air and visible from above when you perhaps take a satellite image of it and there's this building in the center of it.

Mary (09:39):

And so they were convinced that this building had to be very, very important because there were always people milling about it and it was in the center of the Pentagon. So clearly they thought it was a nuclear silo. They, you know, who knows, but was a very big focus. And that's what you might think if you're relying on one source of information, which in their case was the satellite imagery. Well we see it, we know that it's there and there's people milling around so clearly it's gotta be important, right? That was the only data point they had. Well the building in question was a hotdog stand and the reason there was people milling about, presumably it was because their satellites were passing over when it was lunchtime. That was the entirety of its importance. You know, the important stuff was happening, you know, inside the actual walls of the Pentagon that you can't see.

Mary (10:19):

And you know, I think it's a good corollary for if you're only relying on one source of information, you can only glean what that source of information will tell you. If you had somebody inside who you could ask, you'd be like, no dude, that's just a hotdog stand. Don't worry about it. You know, or other ways of triangulating to the right answer. You could figure that out. And at the time, you know, I was writing it because there was a big focus on what we have to do is passively collected data, you know, just asking people what they think is terrible. So we just, you know, need to follow them around you know, their internet and just watch what they do on the internet and watch what social media sites they go to and how long something sits in their cart on Amazon. And that will really tell us what we need to know, right?

Mary (10:55):

Except it doesn't, 'cause it still only tells you what they did, but it doesn't tell you why they did it. It doesn't tell you like, did they really sit on that site for 30 minutes 'cause they were so engrossed or did they go to that site and then they left the room for 25 of those minutes and then came back? You can't tell no one way of getting to the answer is gonna give you everything. It can always get a more complete picture if you can look at a variety of sources and that start to corroborate each other and triangulate to an answer. And I think there's so much data out there and I do think that's something that I'd, I'd love to see more cooperation in the industry of, okay, you've got this panel that does this and we have, you know, our implicit measures that would give us that. And if we could survey your people, then we could put, you know, their actual observed behaviors together with, you know, the psychology behind the behaviors and you could get a richer data set. But there's still not a ton of willingness to play nicely in the sandbox together, in, in some of those ways. And I've always, I think you can almost always find the benefit when there's willingness to do it. It and we're certainly always open to talking about partnering and collaborating.

Sebastian (11:56):

Yeah, I love that anecdote. Makes me think of another one. Maybe you've seen it, I circulate on the internet sometimes whenever there's like a big news item, you know, people one sort of barometer for like how big of a deal it it is, is how busy are the pizza restaurants in Langley, Virginia where the CIA is

Mary (12:14):

<Laugh>

Sebastian (12:15):

Is everybody ordering pizza 'cause they're staying in the office. Right. I don't know if you've seen that, but I see that sometimes people, they're posting like the Google like, you know, how busy is it right now? Oh, it's off the charts busy. Right. You know, like, so I'm curious, as far as I know Alpha Diver kind of sits at the intersection of neuroscience and and market research. Mm-Hmm. <affirmative>. 'cause We've been talking about how different data sets can sort of enrich each other. I'm curious, you know, if you can tell me a little bit about how those two disciplines sort of support each other and what the role of neuroscience is in better helping us understand audiences.

Mary (12:48):

Mm, sure. So the origin story of, of Alpha Diver is I think really my colleague Hunter that founded the company was getting really frustrated that there didn't seem to be a model or a theory behind the way that, you know, agencies were making the recommendation or the way that data was being gathered. It was a lot of, I think, you know, going back to my, you know, international relations political science world, I think they call it barefoot empiricism, right? If we just collect a whole bunch of data and then we wait around in it long enough, we'll find the answer versus the way that the hard sciences tend to approach things of we have a hypothesis and then we figure out how we will test to determine whether or not the hypothesis is proven true or false, right? It's much more model-based and you know, he was introduced to Siggy Hale who's our director of research and our principal neuroscientist who at the time was, you know, working out of UCLA and running one of their neuroscience institutes there.

Mary (13:42):

And all of his work was really about how our brains have evolved to make decisions. And he started consulting with Hunter to really bring more of that model based approach and more of that academic learning around what's really happening in our brains when we're making decisions and bringing that more into the work. And then kind of brought everything more formally together, eh, quite a few years ago now at this point. But when we've really evolved to this place where that model that Ciggy was working on of the things that really drive and hinder behavior and decision making in our brains at that core level and coming up with a market research focused way of measuring that IE getting to a survey instrument by which we can really quantitatively and at scale get this beat on what's really driving people's behavior in these different contexts of interest.

Mary (14:31):

And let that really inform the way that we do our work and the way that we design our studies. And of late, what it's really evolved into is coming from academia, this very informed and you know, we think very predictive model of how does a product enter the market, generate interest and get itself adopted and reach true power brand status, you know, your Coca-Cola or McDonald's et cetera of the world where virtually everyone's tried it at least once. It's you know, really become routinized and part of our daily life. How do you drive from really high interest in something, a novelty to actual routinized behavior where it's become a part of daily life for not everyone necessarily, but for, you know, a pretty sustained portion of the population and it really has staying power and like what is that lifecycle of a brand and how do you diagnose where you're at and what you need to do to get where you wanna go.

Sebastian (15:21):

It's really interesting. So in practice, what does that typically look like for the way that you guys conduct research?

Mary (15:26):

There's kind of two main things that we sort of two halves really of the business right now. There's the 50 lists that we have been developing the last year, 18 months or so, and really using, which are something that we conduct on our own as internal research as a way of getting really a pulse on these brands in, in these spaces that we're really interested in. So we do a snack 50, which is snack and confectionary brands. We do above 50 sodas, energy drinks, waters and so on. We've done it in the QSR space, we've done it in the beverage, alcohol space, et cetera. So it's a gen pop sample evaluating these decision making drivers and bears that we talked about and evaluate and having consumers evaluate these brands in the context of our model. Both those drivers and barriers of behavior, but also that interest in action piece that I talked about.

Mary (16:14):

You know, their interest being is this something that you have momentum and interest in? Are you interested in trying it? Would you like to have more of this brand in your life really? And then, you know, the action is like, are you in fact actually acting on that and purchasing it, consuming it with some regularity? And you know, when you plot it on a two by two, you find this very consistent pattern of, you have a lot of things that drive a lot of high interest, which are, you know, your new exciting brands and might be doing a lot of really interesting things to get awareness like your liquid deaths and you know, some of these new energy drink brands that are trying to stand out from the Red Bulls and the monsters of the world. And then you have sort of this downward curve into things that are really, really routinized but aren't necessarily that exciting anymore.

Mary (16:57):

Like your Cokes, your McDonald's or Pepsi's, et cetera. And then you have kind of this promised land space where you manage to remain both very interesting and very exciting and not very many brands live there. And then of course there's the space you really don't wanna be in, which is where you're neither interesting nor <laugh> nor actionable <laugh>. And so if you find yourself there, you wanna obviously wanna get motivated to get out. So we are doing that to keep this ongoing pulse. We've built a database and we've built a trend line over time as we monitor these things. And so that we're doing that on a regular basis to feed that base of knowledge that we have and really apply and ref and keep refining this model. And then there's, you know, engagements of course where a client has a specific business question, we're set, we're trying to help them answer, which is usually in the realm of, you know, segmentation.

Mary (17:46):

You know, who are the consumers that, who am I getting now? Who could I get and who am I not likely to get and why? What explains the behavior of those different groups and what does that tell us about how you grow your interest with the people that are getable but aren't as bought in yet? And how do you do that in a way that doesn't alienate who you already have? And it also helps them put their brands and their categories in context of where do they fall on that interest in action spectrum? Where do their competitors fall? And again, understanding what's driving the people behind it all. What does that tell us about what you need to do to drive higher interest or drive higher action and move to a more desirable place on that two by two.

Sebastian (18:29):

You know, one of the things that really strikes me about Alpha Diver is the number of expert neuroscientists on your bench. And I think you kind of alluded to this with the, with the reference to kind of the crossover with academia that you guys have. And I'm curious, you know, in terms of structuring teams, how have you found the process of sort of merging those disciplines in, you know, the teams that you guys have built and what are some of the strengths that you've been able to, to leverage and, you know, what have been sort of the process of of putting those backgrounds together?

Mary (18:59):

It's an ongoing evolving process and you know what, we talk a lot about trying to use, you know, use our models and what we know about human behavior on ourselves and understand each other's strengths and weaknesses. And if you look on our website, you even see when you look at the main team we have, there's this little graphic underneath each of us that's a little bar chart of some people are going very much to the left and other people are going very much to the right on this metric. And it's actually lists, we call it the hail scale 'cause it's, it's another thing that Siggy created of gauging personality type basically. And we, we see we have a range across the team of people that are very, you know, whose brains look very much work one way, people whose brains very much work another way and somewhere in, in the middle.

Mary (19:39):

And that's something we're constantly trying to lean into and play to each other's strengths. Siggy is as the academic, as the scientist behind all of it all really wants to go deep and really dig into the models and flesh these things out and understand what's happening. And then you have Hunter and myself, you who are more like, well we have to get to the ideation of okay, that's really interesting, but what does it mean, what does somebody do with it? How do we use it? How does that help clients move forward in doing that translation? And yeah, so it's kind of continually finding that balance and you know, we even sometimes use the language in our meeting. It's like, okay, is this a session where we need to be charging ahead and like trying to, you know, in other context you might call it, you know, divergent versus convergent thinking like, are we diverging and thinking, brainstorming, going deep and thinking of all of the options and all the possibilities or are we to a point where no, we need to start coming back toward a, you know, a resolution and making some decisions and moving forward.

Mary (20:33):

And the other concept that we, we talk to each other about a lot is this idea of what we call approach mode versus avoidance mode. Approach mode is assume positive intent, be open-minded versus, you know, avoidance mode is you being, you know, resistant to change, not really wanting to be there, not really wanting to consider new ideas. And so always, you know, trying to go into things in approach mode, always try to engage, you know, bring clients into approach mode and that works better when everybody's in approach mode. There's a lot more openness to collaborating and sharing and it definitely makes it easier for ideas and, and conversations to flow. So that's definitely something we strive for as well.

Sebastian (21:10):

I can tell you guys are neuroscientists, <laugh>, you're very thoughtful about the ways that you're thinking, which I think is to your credit.

Mary (21:16):

Yeah, I mean just some days more than others for <laugh>, you know, in any business. But yet when we have the time to sit down and think strategically and creatively, like we always try to think about, all right, what would our one models tell us is what's going on here? You know, and, and thinking about what's the dynamic going on in in the client's organization and you know, the team that we're working with and what does help best look like for this client versus that client and their situation and what do they need to feel that this project is a success or to feel that they can take this and run with it once our engagement has ended, et cetera.

Sebastian (21:48):

A lot like the laundry shop at the start of the journey.

Mary (21:52):

Yeah. In a <laugh>.

Sebastian (21:54):

I wanna shift gears slightly 'cause you semi recently wrote a piece about thinking like a creator in the way that you deliver reports and deliver insights to clients. And you know, I think one of the things you mentioned in the piece is that it's not necessarily a metaphor that you love, you know, there are maybe more applicable ones, but that some of the core ideas behind trying to create compelling content really resonate across any discipline where you're trying to influence decisions that people make. I'm curious if you can tell me a little bit more about that philosophy and, and how you leverage it at Alpha Diver.

Mary (22:26):

Well, I think we're always striving for newer, better ways to get the information across. And we do a lot of work in PowerPoint just like everyone else, but also <laugh> also striving for, is there a one page high level summary of this? And then we drill down deeper and deeper depending on what they need. Can we make a video clip that more succinctly gets this across and you know, that they can use to help explain it to someone else. You know, is it an article that we write? Is it that looking for these more than one way of conveying the insight and you know, understanding that a lot of people need to hear something, see it touched a set or more than once for it to sink in and really resonate. And so making sure that we're not solely relying on here's PowerPoint, we're all set, right? <Laugh>.

Mary (23:13):

And I think in the way that we talk about our work in our LinkedIn presence and you, the thought leadership that we're trying to do et cetera is sort of the same thing, you know, you know, trying to mix a variety of ways of talking about the content, ways of bringing it to life, you know, whether it's videos, whether it's speaking at conferences, writing articles, et cetera. I, I'm personally advocating that I want the like blog section of our website to be divided up into like, do you wanna read? Okay, look here, do you wanna listen? Here's the podcast stuff. Do you wanna watch? Here's all of the webinars so that you know, no matter however you wanna get the information, we've got you covered somewhere. You know, we think that is very important knowing that people have different ways of processing information, different ways of preferred learning styles, you know, that we're, we're trying to have something for everybody to meet them where they're at.

Sebastian (23:58):

Mary, what keeps you motivated?

Mary (24:00):

I think honestly just that I continually get to learn things. You know, I'm, whatever the project is, it's gonna be some space that I didn't know a whole lot about that before. And now by virtue of having done the project, I've learned something new, I've learned something knowledgeable, I feel more knowledgeable about it. We're doing a project that's very big on coffee right now and I mean I would've fancied myself to be fairly knowledgeable about the coffee market, but I'm learning all kinds of things from doing that and you know, that's cool. And when I was in DC the, you know, thinking, oh, like I'm doing this really important work and we're, you know, potentially influencing, you know, big foreign policy decisions and all that and that's true, that's certainly was worthwhile, but it's also a little bit amorphous of like, well it could take years, potentially decades before we really would see what's the real impact of that and was it positive or negative, you know, versus when you worked at, like when I worked at Nielsen, we were, it was like, well they launched it and it did well or we advised them not to launch it and they didn't and you know, the person kept their job swift to move on to another concept, you know, a little bit more immediate where you can see those benefits and we, we have clients come back to us and say, yeah, we did what you suggested that we did and we saw this double digit growth result, et cetera.

Mary (25:09):

And that the more immediacy of it I think is also very motivating that it's much easier to see the result of what we're doing in a shorter timeframe. I enjoy our team, we're a good tight-knit group and you know, that makes it fun to go to work and we have kind of a hybrid format where, you know, like I'm, I'm home today but about half the time I'm in our office and it's really good conducive to just having a free flowing conversation about things that are happening when we can kind of sit down together and it's a good environment.

Sebastian (25:36):

Sounds very approach mode.

Mary (25:38):

Yes, exactly.

Sebastian (25:39):

Cool. Last question. So people wanna find out more about Alpha Diver, where did they go?

Mary (25:43):

Definitely our website. It's Alpha dash diver, A-L-P-H-A dash D-I-V-E-R. Also follow us on LinkedIn. You know, we're pretty good about posting regularly about what we're doing, if you wanna find out about the snack and bi fifties. We've got a lot of content about those there and, and there's a lot of content on the website about those. I'm on LinkedIn, you know, Hunter's on LinkedIn. We're always posting and and commenting on stuff as well. So yeah, those are probably the best places to find us. Mary,

Sebastian (26:10):

Thank you.

Mary (26:10):

Thank you.