Monika Rogers is the VP of growth strategy at CMB which is a top U.S. insights and analytics firm that provides world-class market research across Media/Entertainment/Culture, Technology, and Financial Services.
Prior to joining CMB, she had a role at Illuminas as head of client services and operations from 2022 to 2024.
From 2014 to 2022 she was an entrepreneur who raised over $2M in funding to build an innovative SaaS platform Digisite with both a consumer-facing insights community and B2B testing/analytics platform.
The Digsite platform was sold to QuestionPro in August of 2022 and integrated into their Customer Experience research portfolio.
Leading up to that she built the Fountainhead Brand consulting business from 2007 to 2014 which was a boutique innovation and brand consulting firm. Clients included Organic Valley, U.S. Bank, and Kohler.
Core services included strategic insights, uncovering new market opportunities, brand positioning, new product strategy, and shopper insights. Research methods included segmentation, conjoint, ethnography, online communities, and brand tracking. Fountainhead was sold to a regional ad agency in 2015.
What you will learn
- Unconventional methods for finding untapped markets and validating business ideas quickly.
- Advanced techniques for using AI in lead generation, content creation, and customer engagement to save time and maximize impact.
- A roadmap for transitioning from a side hustle to a full-time venture, including financial milestones and scaling strategies.
- Tactics for creating unique, value-driven offers that differentiate your brand in competitive spaces.
- Insights into using data analytics to refine and optimize your business decisions as you grow.
Transcript
Jeff Bullas
00:00:04 – 00:00:43
Hi, everyone and welcome to the Jeff Bullas show. Today I have with me Monika Rogers. Now, Monika is the VP of growth strategy at CMB which is a top U.S. insights and analytics firm that provides world-class market research across Media/Entertainment/Culture, Technology, and Financial Services.
Prior to joining CMB she had a role at Illuminas as head of client services and operations from 2022 to 2024.
Jeff Bullas
00:00:44 – 00:01:33
From 2014 to 2022 she was an entrepreneur who raised over $2M in funding to build an innovative SaaS platform Digisite with both a consumer-facing insights community and B2B testing/analytics platform. The Digsite platform was sold to QuestionPro in August of 2022 and integrated into their Customer Experience research portfolio.
And leading up to that she built the Fountainhead Brand consulting business from 2007 to 2014 that was a boutique innovation and brand consulting firm.
Jeff Bullas
00:01:34 – 00:02:10
Clients included Organic Valley, U.S. Bank and Kohler. Core services included strategic insights, uncovering new market opportunities, brand positioning, new product strategy and shopper insights. Research methods included segmentation, conjoint, ethnography, online communities, and brand tracking. Fountainhead was sold to a regional ad agency in 2015.
Monika Rogers
00:02:11 – 00:02:13
Thank you, Jeff. It’s a delight to be here.
Jeff Bullas
00:02:14 – 00:02:51
So Monika, when you s you know, like I’m curious about why people start their journeys and then where they go from there. It’s a little bit like the, you know, the Joseph Campbell hero’s journey is um and one of the things I love about Joseph Campbell is he said, none of us have inbuilt, you know, mission in life or a purpose really. He said you find that by following your bliss, which often is your curiosity. So can you tell me what started your journey into the industries, you know, the university degree you did? And then,
Jeff Bullas
00:02:52 – 00:03:06
and you told me you get bored quickly and quickly. I mean, by every three years of seeming to move on, um but we’re being in general here. So what were you curious about as a teenager that led you to start a university degree? And let’s take it from there.
Monika Rogers
00:03:08 – 00:03:31
Um So as a teenager, I thought I was going to be an international correspondent. Uh I did not get into the college I wanted to get into and so I needed to get to plan B. Um So I worked full time through undergrad, got a business degree because that’s what my parents did. Like I had two choices, business or engineering. That’s, that was it, at least in my parents’ eyes. Um
Monika Rogers
00:03:31 – 00:04:00
And I was in undergrad and I took this class and it was called a new product development. And in it, there was like a little study where they said you could ask people the similarity of cars and based on asking similarity of cars, you could determine a segmentation and a map of cars in the marketplace. And from that, you can derive the attributes of those car brands. And I was like blown away, right? Like
Monika Rogers
00:04:00 – 00:04:29
you can do what you don’t have to ask somebody a direct question to get a direct answer. There’s all these new interesting analytic ways to approach the world. And that’s what gave me the research bug. And at that point, I kind of approached my professor and said, how do I get into this career related to market research and go on to get my degree and, and start in that world? Um As you said, the journey didn’t end there, I think um I was very fortunate Um
Monika Rogers
00:04:30 – 00:04:59
coming out of undergrad before I started grad school. Um, I was working at an engineering company. I was doing sales. I helped them invent a new product. It was really exciting. Um But I was on my way to get my market research degree. So I went and did that and I said I can do this anywhere, right? Because that company was like, hey, we want you to do, you want to do marketing, get an engineering degree? I’m like, that doesn’t make sense, right? But there’s this, this thought that in order to sell something you have to be an expert at it. And so I’m like, well, I could sell toothpaste, I
Monika Rogers
00:04:59 – 00:05:29
sell anything. Um So I went to General Mills and I did marketing research there. I loved it. Um But I wasn’t a fit for a big, big company kind of culture. Um, I really had the bug to start my own business. Um But was a little afraid to do that. So I went to a small ad agency and did that and it kind of evolved its way into ultimately starting my own business, starting my own consulting, um and starting a tech company, which was, which was really, really fun. Um And to your point,
Monika Rogers
00:05:30 – 00:05:59
um I, you know, after eight years running a tech company and selling it, I’m not a rinse and repeat kind of person, like what’s the next adventure? So, uh here I am at CMB, really trying to take a lot of the learning that I’ve gotten from building a technology company into that organization to help them build solutions, market and sell those solutions to the world. So it’s, it’s a pretty fun uh pretty fun uh place along the path.
Jeff Bullas
00:05:59 – 00:06:15
Oh, so you mean you’re really trapped in market research almost from the university days, aren’t you really? But does that mean that you’re quite curious about the business world and how it operates? And um what are the, what are the drivers for the for business?
Monika Rogers
00:06:15 – 00:06:50
I think that’s what a foundation is, like market research does, right? I mean, it allows us to figure out what is the question, what is the opportunity, what is the challenge and how might you approach solving it? But being an entrepreneur, I had the opportunity to do that, right? And figure out how to run that company and run a business. And so you learn a lot about that and I think this role is a hybrid of that because you’re, you’re seeing the company’s vision, you know, where the company is trying to go and you’re trying to figure out how to get there and you’re
Monika Rogers
00:06:50 – 00:07:06
using all the tools at your disposal. So I don’t do market research in my role, but the company expertise is market research. Um And so it allows me to kind of tap into my knowledge of the industry while still doing more of the leadership kind of work.
Jeff Bullas
00:07:08 – 00:07:25
So, you know, pre conversation before we hit record here, uh You mentioned that you really wanted to get into growth, you didn’t want to be doing operational type stuff like, you know, the nuts and bolts, you wouldn’t. So it sounds like you, you like it, you like the more strategic big picture game instead of the nuts and bolts. Is that correct and growing?
Monika Rogers
00:07:26 – 00:07:52
Exactly. To me, that’s the exciting part. I mean, the nuts and bolts all have to happen and you have to find the right team around you to get all of that, all of that done. But for me, the thing that gets me up in the morning is that challenge, what’s the next challenge? What’s the problem to be solved? And what are the insights I need to get there? And then what’s the strategy and how, who do I, how do I put the right people in the right place to play the game of chess, right? And, and get to the finish line,
Jeff Bullas
00:07:53 – 00:08:20
right? OK. So you, you’ve done, let’s go back to your company that um you built this ali platform Digi. I, is that how it’s pronounced or digi site dig dig site? OK. So that was a SAS platform, which is a, was that a monthly subscription, annual subscription site that customers signed up for to do their own type of analytics and research? Is that what it was?
Monika Rogers
00:08:21 – 00:08:46
Yeah, it was um it, it still exists as a platform and basically what we built it to do was to help companies get insights faster. So we were looking at kind of um I think because you were telling me about how you started your current journey. Uh We were looking at the world of social media and realizing that market research needed to operate differently, right? And at the, at that time, a lot of interviews or
Monika Rogers
00:08:46 – 00:09:12
research was done one on one over the phone or in person and focus group facilities. And we wanted to create a social media style platform to do that. But instead of a long standing online community that might take weeks to set up and cost hundreds of thousands of dollars, we wanted to have that be very instant, right? So you could quickly say, hey, I’m thinking about this new flavor of ice cream.
Monika Rogers
00:09:12 – 00:09:41
You could test that overnight in a platform where you could find your participants, you could engage with them in a social media style kind of conversation and boom, you have the results, right? And so that was the platform. It was at first sold on a monthly subscription, but with trans transition to annual subscriptions and larger organizations. So we were, we were selling um you know, more large contracts where people were doing this on a weekly or monthly basis.
Jeff Bullas
00:09:42 – 00:10:07
Yeah, that’s interesting because I’ve been involved with a company called um Shuttle Rock, New Zealand Company 300 staff now, uh which we’ve moved from a project by project basis to a subscription model and just like we’ve moved to more enterprise rather than um a smaller, small to medium business which tend to churn a little bit more. So, um I don’t know what you discover, but it’s interesting that everyone’s tried to move, you know,
Jeff Bullas
00:10:07 – 00:10:57
uh to more a software as a service type model, uh subscription rather than one off projects. They tend to get better valuations when they get acquired or if they go and float in IP O. But uh and there’s also all sorts of names around that now. So for example, Shutter Rock, who I’ve been involved with was on the board of for a long time, um was uh they’ve called it Creative as a service. So that’s rather interesting, but I digress. So um let’s move on to CNB and you’re in growth now. And you’ve just released a new product service, which you’ve called A I plus H I, which I’m gonna explain those two acronyms A I, we know all about. OK, H I is human intelligence. So see, sounds like it’s the intersection of
Jeff Bullas
00:10:57 – 00:11:04
artificial intelligence and human intelligence to actually help us make wiser decisions. Is that correct?
Monika Rogers
00:11:05 – 00:11:42
Absolutely. That’s, that’s exactly the, the concept I think what we recognized um is one of the first most obvious use cases for Ja I and, and A I generally, but, but Ja I in particular has been market research, right? People are like, hey, I want a prompt and say so I wanna market to millennials, such and such and such and such. And here’s the profile, what should I do? Right? And, Jenny, I’ll give you an answer, I’ll give you an ad campaign or I’ll give you whatever. So I think there is this initial kind of idea, right? That market research could just be replaced by A I. In fact, we can just create synthetic,
Monika Rogers
00:11:43 – 00:12:20
synthetic people and we can ask some survey questions and we’ve got all of our insights right there, right? And I think the way that CMB is looking at it is to say what kind of but not really right. I think there’s a lot more context, a lot more nuance and to be honest, a lot of value that insights has brought to decision makers over the last 25 years. So the question is how you, how you use A I uh capabilities to level up the research that we’re doing. And I feel like there’s a lot of
Monika Rogers
00:12:20 – 00:13:07
emphasis by a lot of SS platforms to drive speed and efficiency, which is super important. Um, we’re looking at how we can leverage all of that research. There’s 1500 market research tools, by the way, 1500. Uh So how do you vet through 1500 market research tools, all of which I’m sure have adopted some kind of A I into their tech, right at this point and figure out what’s the best of the best and then how you combine that with the proprietary methods that we’ve created over time to create something better, right? That gets us faster and better insights. And so that’s really the A I plus H I combo is, is recognizing that our clients don’t have time to bring in and vet all that
Monika Rogers
00:13:07 – 00:13:31
they may bring in some big players, right? Like a qual trick that has some A I capabilities, but they’re probably gonna continue to need expertise to really maximize the research that they’re doing. And so our focus is really on building those kinds of custom solutions using the latest A I technology.
Jeff Bullas
00:13:32 – 00:13:45
So this service you built, is that a product that you give to a client or you use it internally? How does, how does it describe how the product works in the market.
Monika Rogers
00:13:46 – 00:14:34
Yeah, we’re definitely, um I would say at our core, a services kind of organization. And so we’re at this point, right, most of what we’re doing is using the A I tools on behalf of our clients. So they may come to us with a problem. Uh, say I want to, um, I wanna prove out that these events that I’m doing are effective. I will say, OK, we’re gonna, we’re gonna build these uh these kind of conversational chatbots surveys that you could put right in your event venue and it’s gonna automate the learning. But by the way, you’re gonna have instant access to the results. So we’re doing a lot of the kind of consulting work to get things set up. But there are places in the process where the
Monika Rogers
00:14:34 – 00:14:55
you may have direct access to the platform that we’re using in order to uh interface with data prompt it with questions, things like that. So it’s kind of a combination. But at the end of the day, we’re not a tech company that’s providing a solution. We’re uh we’re a consulting company that’s embedding sass into our solutions,
Jeff Bullas
00:14:55 – 00:15:07
right? So you basically have done some research in the marketplace and you’ve done all the hard yards and you actually maybe picked up several platforms that you use to help you get the results you need. Is that correct?
Monika Rogers
00:15:08 – 00:15:47
Yeah. And then we’re kind of constantly doing that, right. So we’ve got a team that’s just sitting there checking the next platform and the next platform or the next update or iteration on the platforms that we have. Because that’s the challenge right now, right? We’re not at a point in the life cycle of A I that you can just pick something and then it worked for a year or two years or three years. It may work, but it may not be optimal. So we’re having to kind of constantly vet and find new and better solutions. And that is a part of the value proposition as well as you kind of work with us and, and come with us on that journey and not have to do all of that homework yourself.
Jeff Bullas
00:15:47 – 00:16:25
Yeah. And the interesting thing in the marketplace with A I is we’re seeing, I’m seeing two marketplaces. You got, the bigger companies are adopting A I into their existing solutions. Um And then you got the ones that are those pure start ups like starting with a clean sheet and going. So a and that raises a whole lot of questions too because I did some research recently of my own, which is my research is writing an article and then publishing my blog and going this is research. No, I don’t say it’s research but I’m just saying, well, this is my curiosity. I just did some, did some hard yards during the last week and I So I did, what I’m seeing is that
Jeff Bullas
00:16:26 – 00:17:00
in the world of A I, because it requires so much training, um so much, you know, processing power, so much data center P power um that it appears that the bigger players are maybe poised to win the game of A I. And I’m sure in the marketplace you’re dealing with A I market research firms and the intersection, those, you know, the human and the machine. Are you seeing the bigger players as being better positioned to actually win the game in this particular market segment you’re working in which is market research and A I.
Monika Rogers
00:17:01 – 00:17:47
Uh yes, I mean, the fact of the matter is that one, our clients are very large organizations, right? So we’re working with very big companies who even in order to vet a vendor like ours, to use an A I solution within our stack, have, you know, we have to be IO certified, we have to follow, you know, we have to meet certain requirements. So the legal and regulatory with A I, right, it’s gonna just keep uh ratcheting up and therefore you have to have a base level of research that of, of sorry, of, of capabilities and, and resources to do that. It gets harder and harder for that independent consultant or freelancer or small research company
Monika Rogers
00:17:47 – 00:18:18
to have those capabilities unless you’re financially back to start up. And you’ve got, you know, a couple million bucks behind you to get you off the ground. But it’s very hard to just enter the market, maybe as market research companies did in the past. And then I think the other thing is there’s gonna be winners and losers in this space, right? So we see tech platforms growing at a 13-14% rate within the market research industry and the consulting companies growing at a 3% rate. Ok?
Monika Rogers
00:18:19 – 00:18:47
There’s going to be winners and losers here and there are a lot of companies who’ve had layoff and downsize over the last couple of years. So the question is who is going to win? And the companies that are gonna win are the ones that can invest additional resources to build new capabilities and the ones that are gonna lose are those that are so cash poor, right? That they don’t have time to build new capabilities and they’re just continuing to deliver what they have for the past 25 years.
Jeff Bullas
00:18:47 – 00:19:29
Yeah, you’ve got sort of like the people are coming from, uh, what do they call old thinking? And, and then you’ve got the ones that start with a clean sheet and that’s really fascinating. But I think the big versus small uh is sprinting to watch it play out. And for example, Mustafa Suleiman, that was behind um, deep mind. Uh he actually started a 1.5 billion start, million $1.5 billion start up uh to create a product and, uh, he basically, I think it was 18 months in, uh, threw up his hands and joined Microsoft and that team all moved over there. They weren’t bought, they acquired the team.
Monika Rogers
00:19:29 – 00:19:44
Got it. Yeah. Uh, what they called it Aqua Hire or? Yeah, there, there’s a term for it now. Uh, but there’s companies out there that, that, that, that’s exactly what they do. They hired the team, um, because that’s what they’re looking for.
Jeff Bullas
00:19:44 – 00:20:26
Yeah. And that nearly happened with open A I last year when uh uh Altman got fired by the board which lasted five days. And Microsoft said, no, you’re not because we’ve got a lot of money at stake here and they were gonna basically take up all the team and move them to Microsoft again, cos they got the money. The thing is it’s taking so much time and resources to actually train the models. So the interesting thing for me too is, um, in what you’re doing and where we are with generative A I is, do you have an, and I use a hybrid of Google and Chat G BT which is starting to blow me away more and more, the more I use it.
Jeff Bullas
00:20:27 – 00:20:48
And do you, do you see a problem with, you know, the big problem was hallucination. In other words, Chat seemed like it wanted to keep the human happy by giving an answer. And so it would make shit up, right? OK. To use an Australian term. And the reality for that is can you trust the data and do you validate the data through a certain process?
Monika Rogers
00:20:49 – 00:21:31
Yeah. And that is uh I think another key reason why in a market research industry, right, you’ve got to have an A I plus H I component because you need proof points of all of these things and you need the oversight of um and to be honest, if you’ve got the deep industry knowledge, you’ve got the deep, you know, the deep understanding you, you see the, you see the BS immediately, right? When I mean, you could, you kind of see when it’s starting to go a little off the rails, but we have to look at it because imagine we have a, we’ve talked to 1000 people, we have A I open ends. We, we’ve asked questions and the A I is prompted and we’ve got all those responses and now we’re gonna be prompted
Monika Rogers
00:21:31 – 00:22:05
A I to do some analysis and help us make sense of all that we have to be able to validate that. So we have to have mechanisms in place to see where the origin of those responses was. How did that come from? And then the way we look at it is we’re still gonna be analyzing some of that data, right? With human eyes, we’re gonna be triangulating some of those things. So over time, there can be things that we can automate the validation of. Right. And I, I think there’s been conversations about that with a IA I might be able to validate A I but
Monika Rogers
00:22:06 – 00:22:29
where we are right now there’s a lot of that that has to be done at every step along the way. So, in prompting the first time we had a I prompted an open ended interview, right? Conversation, it went off the rails a little bit like it started. It was supposed to be a 15 minute interview and it just kept asking questions, right? It wouldn’t shut off. And so the response like,
Monika Rogers
00:22:29 – 00:22:52
Well, wait a minute, like it’s been 25 minutes. Why isn’t my interview ending? Right? So we had to kind of figure out, OK, we’ve got to retrain the model to ask those questions there. So you got that then as I mentioned, you’ve got the data coming in on the back end. How you analyze that the other big industry issue is fraudulent respondents. So you think you’re sending a survey out to real people but turns out that there’s, you know, but
Monika Rogers
00:22:52 – 00:23:15
bakers out there trying to take your surveys. So we’ve got to figure out how to use A I to help us find that, but there’s a human layer to that too. So everything that we’re doing, it seems to require this multi layered um approach. And that’s really what kind of got us the the light bulb went off and said, ok, we need to codify this and, and, and, you know, and make it into a solution.
Jeff Bullas
00:23:16 – 00:24:03
Yeah. I think there’s a lot of, you’ve already got two ends of the market and the truth’s gonna sit in the middle with two attitudes and philosophical approaches to A I, one is dystopian and one is utopian and, uh, and we’ve got Hollywood to blame for a lot of dystopia. Um, not the utopia uh because, you know, drama and violence and death and destruction and the end of the world sells well, movie seats, right? It’s really quite simple, right? So it sounds like Facebook really. Um So the reality is that um the truth’s gonna lie somewhere in the middle. And I had the privilege of actually uh interviewing Nick Bostrom who’s written Deep Utopia is a leading uh a I thought leader and philosopher um
Jeff Bullas
00:24:04 – 00:24:37
along with Ray Kurzweil and reading his new book, which is fascinating, uh singularity is nearer, which is uh still to be finished. But Nick Bostrom had these two approaches, deep, you know, deep uh super intelligence in 2014, he wrote and the latest one is a deep utopia. And it was fascinating to view him because uh his approach is very, very left field, you know, and for me, uh having a big brain, he’s a polymath out of Oxford University. And it was just fascinating to see,
Jeff Bullas
00:24:38 – 00:25:13
I suppose projecting the future of, you know, what’s, what’s it mean to have purpose in a world of a, I, if a, I can do everything right? If I, if I, if I, I can write a blog article better and quicker than me. Uh why am I writing? You know, if I’m an artist doing, you know, a canvas and the A I can do it better and quicker than me. But that’s another story. But uh it’s interesting that you guys have actually relaunched A I plus H I, which I think is where I certainly do sit myself in that I see A I as an amplifier and enhance our humanity.
Jeff Bullas
00:25:13 – 00:25:31
And sure we need guardrails, we need to be, you know, checking it for truth, uh historical facts and so on. So, um is this, what sort of guard rails do you put, actually put around what you do uh in using this A I plus H I tool?
Monika Rogers
00:25:31 – 00:26:16
Yeah. Um Before I go there, I want to react to something you were saying because I think this, that there is a really important philosophical point here to be made. And that is when I started market research, right? A long time ago, there was really one goal that was my understanding of why the company hired me and was paying me to spend, you know, a million dollars a year on market research. And it came down to proprietary insights, right? General Mills wanted to have knowledge and insights into the market that none of their competitors had. Right? And they believed that if they had those insights, they could develop better products. They could be first to market first mover advantage. And that’s where the profit came from. Ok. The profit came from being first to market.
Monika Rogers
00:26:17 – 00:27:07
That’s forward to where we are. Now. Everybody can prompt A I with the same set of questions. Guess what? Our role is the same. We have to get proprietary insights for companies that nobody else has, right? And if you just rely on A I, everybody has A I, and it’s all a level playing field, where’s the proprietary? So I think they’re there, you know, in my mind, right? The goal and objective of A I plus H I is to get that competitive advantage to get those proprietary insights into organizations. And that has to do with the types of questions we ask and the approaches that we take um the way that we do the analysis. Um Hopefully we’re, we’re, our human intelligence is getting us beyond, right? What anybody else can do. So that’s like to me the,
Monika Rogers
00:27:08 – 00:28:01
I don’t know, maybe it’s the optimistic utopian side of, of all of this is that together we can get somewhere better. Um But also believing that A I isn’t gonna surpass my ability to uh to think creatively and, or to get to something proprietary that any company couldn’t get with A I. So that’s, you know, the philosophical piece, the guardrails piece like where does it go off the rails? Um It’s all the way through because honestly, it starts with bad data, right? We have fought, fought and fought about bad data. Um from the beginning of time and insights, folks who fought to be farther in the funnel, you know, not data, insights, strategy planning, right? We’re trying to be down this, down this wheel of, of, of impact. Um But right now we’re being dragged back into data
Monika Rogers
00:28:01 – 00:28:39
because if the data isn’t high quality, you can’t integrate it with other data, you can’t prompt it with A I and get good answers. So the first guard rail is good data. We need to focus on having good data. Um And then I think the, the next piece of it is the interpretation and the context associated with what, how do you approach that and what do you do and, and what questions do you ask? Um and making sure that you’re um validating everything that you do along the way that you know what you’re getting is not garbage. Um So it’s the garbage in and the garbage out, I guess is the two guard rails, right? Both sides.
Jeff Bullas
00:28:39 – 00:29:23
Yeah. Yeah. It’s very interesting because uh, I’ve been using A I Chat G BT for nearly two years. And what’s mind blowing is this has all happened in less than two years. We actually haven’t chatted since G BT was released. To the, you know, the general world where it hit global human consciousness rather than the geeks and the researchers and the labs. Um in November 2022 we haven’t hit November 2024 yet. So this has been the pace of this. I’ve been in tech since 1984 when the PC IBM PC was sort of launched. The clones competing with that were launched
Jeff Bullas
00:29:23 – 00:30:05
and I saw the explosion of P CS selling to Corporates. Then they were networked and they were connected to the world through the web. And then we had social media and then we’ve had now we’ve got A I on top of that, I have never seen the pace of change. And so I’m talking close to 2550 . Let’s do the math. Over 30 years, I’ve never seen this change in over 30 years of being in tech. It’s mind blowing. And the trouble is that humans just try to keep your head around it like you and I are both working in A I I essentially and I feel overwhelmed constantly. And one of the reasons I write about A I is to try and make sense of that noise and distill it
Jeff Bullas
00:30:06 – 00:30:32
trying to make simplicity out of complexity, which is what we as humans try to do where pattern recognition machines try to steal this noise and confusion and go, I’m trying to find some elements of truth here. Well, for me, so and you guys must be, is 1500 market tech tools alone. That’s mind blowing. So, do you guys feel overwhelmed sometimes in all that noise?
Monika Rogers
00:30:33 – 00:31:00
Uh uh Yes, yes and yes and yes. And I think, you know, the first thing was trying to make sense of the categorization, right? Uh, as humans, we’re gonna categorize. So all these 1500 tools, what are the buckets of what they’re trying to do? Right? And then one of the buckets within those buckets, what are the ones that look like they, most of interest? And then you get to the point. OK, we piloted all of these, we started to work with clients, we started to figure out what we’re doing.
Monika Rogers
00:31:01 – 00:31:29
But now it’s like this does this really well, this does this really well, but we want this. So now it’s combining two tools together which then there’s another infinite set of combinations around, right? How might you combine these different tools with one another? So I think it is for sure. Uh a sea of ambiguity um that I’m swimming through. Um But I guess that’s what charges me up every day, right? I mean, that’s the whole reason I got into research it, it’s like
Monika Rogers
00:31:30 – 00:31:58
It’s trying to solve problems and to think through and understand all that complexity and knowing that, you know, I have Richard on my team or you know, who, who, whose job is to vet all these solutions and to figure all that out and I don’t have to do that. Thank goodness, but he also doesn’t have time to fill all the gaps and figure out how to prove this stuff. And I’m doing that. And so we all as a company, I think, have found um
Monika Rogers
00:31:58 – 00:32:21
that the silos needed to come down and we just all needed to decide what it is I’m good at and let’s get together and go solve that rather than saying this is my box and this is your box and this is your box. And I think that has helped us accelerate our movement through this um is just shutting the silos and figuring it out together.
Jeff Bullas
00:32:21 – 00:33:06
Yeah. Yeah, because I, I am essentially, it’s not artificial intelligence. Actually, it’s a misnomer. It’s actually human intelligence collected by the machine. Yeah. So it’s not artificial. What’s this? Uh it’s actually I was reading the other day and it’s something I’m sort of going. It’s been misnamed. OK. Yeah. The machine is actually making sense of human wisdom and creativity and we thought, you know, so the reality is that and what I’m excited by is that I’ve got access to a human brain now of 8 billion plus people and all the research by polymaths like Nick Bostrom and you know, Mustapha Silliman, the entrepreneurs and the philosophers and
Jeff Bullas
00:33:06 – 00:33:50
You know, the Charlie Munger of the world, you know, that has got great mental models to make sense of the world and made nearly a trillion dollars between him and you know, Warren Buffett. But so inside all this information, since wisdom and the other thing that intrigues me along with this is that uh what is, what is truth in other words, where does truth really lie? Because you talked about words right before. And there’s one phrase that’s been used to actually uh which really made me really think that it’s a term suitcase word now. But you ask someone what success means? Wow. OK.
Jeff Bullas
00:33:51 – 00:34:21
How many meanings for that word are there? If you open up a suitcase of multiple meanings, what does happiness mean? There’s another one for you and you know what it actually goes on and on and on and then you’ve got cultural context. What’s love mean? India has, you know, Indian philosophy actually has five meanings for love, right? So, the word and truth sits within meaning in context. It sits within context and culture as well, doesn’t it?
Monika Rogers
00:34:22 – 00:35:03
Yeah, that, that is exactly it. And that’s what makes it so difficult. And on one hand, I look at the difference in what we’re able to do in an hour versus a year ago. So I have a data set, right of 1500 open ended responses. Um And uh a year and a half ago or two years ago, I would have had to um you know, probably code some of that data in order to try to classify it to try to, right? And it would take quite a bit of time. Um I still have to do some of that now, but not really. Right. Like I can prompt the data immediately and say, OK,
Monika Rogers
00:35:04 – 00:35:45
I wanna know an answer to this question and it’ll show me the answers and the evidence, right? Um So all of a sudden like something that took, I don’t know, II I estimated like three quarters of my time, right? An analysis could be saved by having this A I assistance in, in doing the analysis, but it’s not zero because, or 100% right? I can’t save 100 percent of my time because we all see it. We all know it when we ask a question and when we make a prompt, how often, right? It’s gotta be 20- 30% of the time off, is it off? 20 degrees? Is it off? 100 and 80 degrees? Depends on, on, on the question that you’re asking and,
Monika Rogers
00:35:45 – 00:36:24
and the hallucination, I mean, I love my daughter. She’s, she’s getting a uh her, her master’s degree in biotech and she was looking for patents and she, and she, she went to Claude and said, you know, I’m looking for a patent, the patents for blah de blah and, and she came back, she says, yeah, one of the patents were real and the fifth one, it totally made up the patent number, the patent, like the whole thing completely made up. And so we have to, like, live in that reality right now. Right. And everything we do, we have to be able to think critically, we have to be able to look at the information contextually and we have to kind of think.
Monika Rogers
00:36:24 – 00:37:00
Right. Um, and so it can’t just be, in, in my opinion, it can’t just be a I for everything. There may be some use cases that the accuracy rates are great on. But in terms of market research, there’s a long way to go, there’s a long way to go. And I think there’s a big evolution in play. But you can’t just wait as a researcher or a leader in a company, you can’t just wait for it to be perfect. So you’ve got to get in the game now and figure out what you can and can’t do. And that’s, that’s part of the
Jeff Bullas
00:37:01 – 00:37:47
B Yeah. Oh, very much. And uh for me that you mentioned a couple of words, there, one was um accelerate what you can do in a certain time frame. And on top of that, then I think what A I allows us to do is to amplify our humanity by distilling that through that as well. So maybe we call this a process. But the reality with that is that I certainly feel that I am learning so much faster. My main problem is my memory as in, uh I’m getting a little bit older, I think, you know, maybe I have dementia. I don’t know. But anyway, it’s maybe one, too many glasses of wine occasionally. But anyway, the reality is that my human memory is maybe the thing that holds me back the most,
Jeff Bullas
00:37:48 – 00:37:53
you know, when I don’t have an A I under my arm. Right. So, the, yeah, because I’m
Monika Rogers
00:37:53 – 00:38:31
going, that’s a huge opportunity for insights, right? If you’re on the client side of insights, you’re right now trying to gather up all the data in your organization, right? And make it possible for anyone in your organization to prompt that data, right? Because you, because you’re not gonna remember what everything is or where to find it or, or, or, or you know what it might mean collectively rather than individually. And so there’s just a huge opportunity to, to be looking at synthesizing across data sets, not just within individual studies. And that’s another really exciting uh area.
Jeff Bullas
00:38:31 – 00:39:21
Yeah. The other term I want to go back to what you mentioned is proprietary. In other words, uh it’s, you know, basically General Mills wanted to actually get insights about something. So they actually had knowledge that no one else had, that’s getting much harder with A I now cos everyone’s got the tool. But when it comes down to it, I think there’s two parts of it that I find interesting. Number one is I think proprietary frameworks is maybe one place to start. In other words, you’ve, you know, you at CNB have maybe come up with what you call your own proprietary framework for how you approach doing research that no one else has quite done. And then it also comes down to the other part of that equation too is asking better questions
Jeff Bullas
00:39:22 – 00:39:30
within those frameworks because the chat G BT, if you have an expert who really knows their fuel, they can actually ask better questions.
Monika Rogers
00:39:31 – 00:39:59
Mhm Yeah. And, and then the other part of it is that the A I is only good as the data it’s being trained on. So there are audiences out there, right? That is harder to find or harder to understand um that you, you can go far with custom research still. So there’s opportunities to collect proprietary data still, there’s opportunities to ask and prompt different kinds of questions um that might not be in the in the
Monika Rogers
00:39:59 – 00:40:25
A data set may or may not be an easy leap for A I to make in terms of a conclusion from the data, it has um as an opportunity as well. And, and, and I also think there are some creative components to A I too, right? I mean, the ability to visualize things, the ability to be on the reporting side as well as that we’re experimenting with as well. And it’s, it’s really fun to see some of the tools that can en
Monika Rogers
00:40:25 – 00:40:51
you say, OK, I want to create three powerpoint slides on this topic. I want to use this for my data, but I want you to bring in these things from secondary data and have it just create the charts for you, right? And then you can look at it and go, is this what I wanted or not what I wanted? So there’s other tools in here too that bring faster visualization, better storytelling and that are kind of a fun, fun part of the journey as well.
Jeff Bullas
00:40:52 – 00:41:36
Yeah. A and the other thing that I think that A I brings to actually the creativity boost and amplification is as humans, we have been raised in a family where there were certain ways of thinking that we were raised in cultures, there were certain ways of thinking. Uh We also go to schools that have a certain way of thinking and we end up being this sort of nice little fixed box. It doesn’t change much, right? Cos we, trying to escape your own thinking is actually really bloody hard. So what I love about A I is you can ask it a question or give you a list or whatever and it recombines the data and the information in ways that you’re going. That’s interesting.
Monika Rogers
00:41:36 – 00:41:57
Yeah. Yeah. Ask A I to write a questionnaire for you. I mean, it’s really interesting because it asks questions you haven’t thought of, right? And then you can look at that versus the questions that you would ask and you can kind of triangulate into what, what makes the most sense. But, um, it does, it absolutely is another sounding board for getting ideas.
Jeff Bullas
00:41:58 – 00:42:16
Yeah. So what, and that leads us into areas like A I agents. In other words, you gotta have to look at A I as almost like your copilot, which is interesting because that’s what Microsoft named one of their products. And I, I really like that approach actually. And for me, it’s like, I don’t feel threatened by A I, I’m excited by A I,
Jeff Bullas
00:42:17 – 00:42:48
I think I can make me more human by breaking the bonds of my own fixed thinking, which has been generated by decades of sitting in a dark corner, you know, eating a sandwich and looking at my screen. So the reality is, and I go to cook and I’m going, oh, I’ve done this like this for the last 20 years. It’s like, you know, chicken Sade and I’m going, oh, my partner sits next to me and going, oh, you could put some capsicum in, you could do this, you can do that. I’m going all right. So are human friends and partners actually breaking those ways of thinking. A I also helps us do that.
Monika Rogers
00:42:49 – 00:43:27
Yeah, I um I actually had the good fortune of doing an interview with uh casually who is the director of Insights at Microsoft. And she talked about um uh copilot being, being particularly named because humans still need to be the pilot. And then she also brought up the idea of like, you know, this is A I is not meant to be on autopilot. Uh So I thought that that was a clever little twist of words there. But I think there is a lot to be said of A I agents that really fascinates me. And it’s an area that I see a lot of potential for as well in market research
Monika Rogers
00:43:27 – 00:43:54
because right now imagine some of the sophisticated analysis that we do. And I’ll just go back to the very beginning of our conversation when I talked about asking the similarity of cars and then creating a map and segmentation, right, of different types of cars. And there we do a lot of types of advanced analysis, right? So say we’ll have we’ll survey of 3000 people and we’ll start to create segments of the market, right? Um
Monika Rogers
00:43:54 – 00:44:22
We don’t just run that through one algorithm, we might run that through 345 algorithms and then we’ll interpret OK. This came up with a five segment solution. This came up with a six segment solution. This is based on more behavioral data. This is based on more attitudinal data and we’ll start to triangulate to say which is most useful, which is gonna help the company make better decisions, which is gonna actually help drive market penetration or whatever the objectives of the segmentation are. Imagine if you have an agent
Monika Rogers
00:44:22 – 00:44:50
helping you iterate through that, right? I mean, there are things that could drive efficiency. Um it could help uh pos new possibilities, new ways of thinking in combination with traditional advanced analytic models. So there’s just so many interesting applications I think for um for A I and for uh these A I agents as we start to train them up to have them do particular tasks for us.
Jeff Bullas
00:44:50 – 00:44:57
Yeah. It’s almost like we’ve got, we’ve, it’s like going to a smorgasbord and it’s so overwhelming. You don’t know where to start sometimes.
Monika Rogers
00:44:58 – 00:45:41
II, I agree. I would say that there are more ideas not only in my head but, but kind of like in our repository at CMB, then we have time to, to go after. Right. So we’re having to choose like, where do we start? Where do we go next? Um And it’s, it’s, it’s a blast. I mean, in, in my mind, I guess I could have a dis be in view of my job somehow going away. But II, I don’t, I just have the perspective of um insights, needs to adjust and your job is gonna go away if you don’t adjust. And, and that’s the reality is we have to be learners and it used to be, we could go to school and then we could
Monika Rogers
00:45:41 – 00:46:02
work and apply uh and have a career doing the same thing. I don’t think that’s the case anymore. I really do think you’re gonna have to re-invent your skill set. Um, and I don’t think that’s gonna stop. I don’t think that’s just this moment in our history. I think that that’s a change and it’s a change for the next generation to contend with.
Jeff Bullas
00:46:03 – 00:46:53
And the thing is, no quotes done is better than perfect. And that’s where we’re going to start from and have some fun along the way and continue to be curious. Absolutely. Yeah. So just a quick thing. Can you take us through quickly? And then I’m gonna ask you a question about what brings you deep joy and happiness. In other words, what would you do, if you had all the money in the world, what would you do every day? But I’m that, that’s gonna be the last question. So I’ll let you just let that just, you know, circulate in your brain. Um What’s just take us through if someone’s gonna use your A I plus H I um process, if you’re taking a client on how does the process work? Just, I’ll be just a quick thumbnail sketch of how you are using this.
Monika Rogers
00:46:54 – 00:47:28
Yeah. So the process works. Um I mean, in many ways similar to traditional research in that we talk to the client about what they’re trying to accomplish, right? What impact are they trying to make in the marketplace? And based on that, what types of decisions might they be trying to make, um, we’re also gonna look at the time frame with which they have to, to make these decisions. And we’re gonna look at that and we’re gonna say, OK, how might we approach this research? And I would say maybe two years ago that would have been, I’m gonna do
Monika Rogers
00:47:29 – 00:47:53
set of qualitative interviews and then I’m gonna follow it up with the survey and now it might look like we’re gonna run these things simultaneously. Um And some of it’s gonna be A I and some of it’s gonna be human and it’s gonna get done, you know, probably a little bit faster. Um And by the way, now we’re gonna have all of a sudden some more insights that came out of this because we were able to talk to say
Monika Rogers
00:47:53 – 00:48:32
twice as many people in these little sub, sub segments to supplement what I can get us. And now we’re at this new place. So the client isn’t really having to do anything different. I say the other part that’s different is the analysis phase. So it used to be, we collect the data, we’d analyze it and then we put a report, we put it for the client and say, here you go. Um Now it’s more like you’re collecting the data and you’re synthesizing it at the same time, right? So by the time you’re out of the field, you already can sit down with a client and not only look at things but explore the data, ask it questions, see what you’re learning and start to think ahead a little bit. So you may not,
Monika Rogers
00:48:33 – 00:48:52
you may be thinking more about activating the insights and how you can translate and teach in the organization and move forward a little bit less about how do I analyze the data? Right? Because that could happen a little bit more instantaneously. And then I think the other part that’s changing is the storytelling that goes along with it. As I said,
Monika Rogers
00:48:53 – 00:49:22
what it comes down to is how do we learn? We don’t learn by seeing a lot of data backs, we learn by seeing it interpreted. And ja I give us the capability of saying what are the imp insight implications of this in new ways and visualizing that in a new way? So I think there’s also um what we’re seeing is a change in our organizational culture to saying we’re delivering insights to saying we’re delivering activation of insights, right? So we’re helping the teams figure out how to use the data
Monika Rogers
00:49:22 – 00:49:47
and make decisions and do things rather than here is a report. Now you go think about what it means. And I think that intersection between insights and strategy is gonna completely blur as we continue to move forward, that’s gonna, that’s, that’s kind of gonna go away. And that’s definitely a huge implication of A I plus H I. But I think we’re still in the early stages of making that all a reality.
Jeff Bullas
00:49:48 – 00:49:53
So how much time do you think you’re saving to get maybe a better result
Monika Rogers
00:49:55 – 00:50:31
at this point? It feels like, um, in some cases we’re saving that, you know, 2030 40% time. In some cases, it’s zero time because we’re spending a lot of time validating or spending a lot of time, um doing things in a redundant way. So, it’ll get better as we go, but it almost feels like it’s just a shift like you’re investing your time later in the process or at different points in the process. Um And you’re getting to a different outcome than it is. Hey, this is just faster and cheaper.
Jeff Bullas
00:50:31 – 00:50:33
You feel like you’re getting better insights.
Monika Rogers
00:50:34 – 00:50:59
I do, I think that and not only better insights but better insights at scale. So sometimes things that we would only be able to, to do among a small audience, we’re able to kind of get a larger audience response to. And so um that example of that event, right, that you want to go inside and ask people questions. Now of a sudden, you’re able to go to executive leadership and say, yeah, we’re able to talk to 2000 people and two hours
Monika Rogers
00:50:59 – 00:51:26
and, and you know, here’s the ro i of what you’re doing at this event is way different than we pulled aside. And we did all these one on one conversations and we have 15 people and here’s what we found, like a complete night and day difference, right? In the, in the validation and accuracy of what we’re able to get. So I think there’s just big differences in, in the deliverables that come out of doing this kind of work
Jeff Bullas
00:51:27 – 00:51:29
exciting times, isn’t it?
Monika Rogers
00:51:29 – 00:51:31
It is flopping.
Jeff Bullas
00:51:32 – 00:51:41
So, my last question, which I ask people if you had all the money in the world, what would you do every day? Even if you went and paid for it?
Monika Rogers
00:51:44 – 00:52:32
You know, this is a really hard question for me. And I say that because, um, my husband says you love what you do and you love what you do so much that work is your hobby. And it’s not intended to be my hobby. But honestly, like, I love getting up in the morning and reading linkedin and finding that nugget of, I love reading a wall street journal every day. Um, but I also love to bike and hike and draw and play cello and I have other interests as well. But I don’t know that I’ll ever wanna stop thinking critically. Um, being curious about business, seeing where the world is going right and being a part of the change, I guess for me that is just, it’s part of what makes me feel alive.
Jeff Bullas
00:52:32 – 00:52:48
Ok. So, let me sum that up hopefully. And you can tell me if I’m right or wrong or close. So, you’re a curious cat. You love learning and you want to keep growing and that’s what you find exciting and not bring you up in the morning. Is that correct?
Monika Rogers
00:52:49 – 00:52:52
Yeah, that is pretty much it.
Jeff Bullas
00:52:52 – 00:53:21
Well, I think curiosity is actually a word that’s not used enough and not explored enough. Uh, I think being curious that’s what gets me up is, um, just reading and learning and then trying to make sense of it, I think for me is the, like I’ve had, you know, the morning, I’m only feeling a little bit flat or something from the day before whatever and you, and you read something going, but then when I start writing and then trying to make sense of it, it’s sort of like, it just dissipates.
Monika Rogers
00:53:22 – 00:53:54
Yeah. Well, there’s something about the space between two, you know, like, I like getting on an airplane to travel. Um, because usually by the end of the flight, whether I’ve watched a movie or distracted myself, like, all of a sudden the light bulb goes off. Right. Like, you get in the shower when you wake up in the morning. I love those moments when your brain isn’t focused on work. Right. It’s focused somewhere completely different. Or I’m off on a bike ride, whatever. And you, and all of a sudden all the dots just fire. Right. And you have that, like, ah, that’s just, that just makes money.
Jeff Bullas
00:53:54 – 00:54:38
Yeah. Well, that’s how symphonies are created. It’s the space between the notes. I love it. Monika. It’s been an absolute joy to have a chat with you. And I am fascinated by A I plus H I, because that’s where I’m curious about and I think we’re in the most exciting time of history. Um And we really don’t know where we’re going, which actually is one sense is good. Um And I think we’re just gonna lean in with, I think, you know, some, I think positive and optimistic, you know, curiosity and, but with their eyes a little bit wide open to make sure that we don’t take the world down
Jeff Bullas
00:54:39 – 00:55:24
a polarization and a fake news, you know, that’s been done by social media, not having the guard rails and it needs to be put in place, this needs to be put in place should be, we should learn from history and realize that, you know, the Kumbaya of social media that started in, you know, 2007, 8, whatever started human consciousness needed a few little guard rails to keep us happy. Um So I think I need the same thing and uh because we’ve got a great tool, we need to make sure that we use a tool instead of being used by it. And that’s what social media has done and it’s great. Um So, but there’s also, if any technology can be used for evil, it can be used for good. And that’s what we’re gonna make sure we continue to use it with. So
Jeff Bullas
00:55:25 – 00:55:39
Monika. Thank you very much for your insights. And um I look forward to hearing more about A I and H I plus H I and C and maybe chat in a year’s time and see what you’ve learned along the way. Um the intersection of humanity and the machine. So, thank you.
Monika Rogers
00:55:40 – 00:55:42
Sounds great. It was really great chatting with you, Jeff.
Jeff Bullas
00:55:43 – 00:55:44
Thank you, Monika.
Monika Rogers
00:55:44 – 00:55:45
Thanks.