Description
A groundbreaking segmentation framework reveals how behavioral and emotional dimensions shape flavor preferences, going far beyond traditional demographic-based consumer insights.
In this episode of The Curiosity Current, hosts Matt and Stephanie speak with Kim Duncan, Head of Consumer Insights at Givaudan, about FlavorFinders—a revolutionary segmentation framework that examines how consumers approach and adopt new flavors across the food and beverage landscape.
Transcript
Kim - 00:00:01:
If I ask this question, how do I use this? How is this actionable? You know, so that is always how, what I keep in mind when I'm designing questions and almost more importantly, answers. You have all of the people represented in Flavor Finder, right? Every single one of them are eating food and beverages, but the way they interact with flavor is different. Keep the curiosity and always be critically thinking, I think.
Stephanie - 00:00:25:
Hello, fellow insight seekers. Welcome to The Curiosity Current, a podcast that's all about navigating the exciting world of market research. I'm Stephanie Vance.
Matt - 00:00:35:
And I'm Matt Mahan. Join us as we explore the ever-shifting landscape of consumer behavior and what it means for brands like yours.
Stephanie - 00:00:42:
Each episode will get swept up in the trends and challenges facing researchers today, riding the current of curiosity towards new discoveries and deeper understanding.
Matt - 00:00:53:
Along the way, we'll tap into the brains of industry leaders, decode real-world data, and explore the tech that's shaping the future of research.
Stephanie - 00:01:00:
So whether you're a seasoned pro or just getting your feet wet, we're excited to have you on board.
Matt - 00:01:05:
So with that, let's jump right in.
Stephanie - 00:01:09:
Today on The Curiosity Current, we're joined by Kim Duncan, Head of Consumer Insights at Givaudan, the global leader in flavor and fragrance innovation. Over the past decade, Kim has been instrumental in developing Flavor Finders, a groundbreaking segmentation framework that overlays traditional insights with behavioral, emotional, and even psychological dimensions of flavor adoption.
Matt - 00:01:31:
Think about the Rogers innovation curve, but for your taste buds. From the cautious Hesitators to the bold trailblazers, Flavor Finders helps brands understand not just what people like, but why they like it and how to meet them where they are in their flavor journey.
Stephanie - 00:01:46:
IMSS work isn't just redefining how we segment consumers. It's redefining how we innovate, message, and even name products in today's crowded, fast-moving food and beverage market. So let's dive in. Welcome, Kim.
Kim - 00:01:57:
Thank you for having me.
Matt - 00:01:59:
Thank you for being here. Stephanie and I are both research nerds, so we're excited to jump right in and learn all about this fantastic research endeavor you've undertaken with Flavor Finders. It's such a fresh take on segmentation. We know it's rooted in a decade of behavioral research. Can you take us back to that moment? What really made you realize that looking at flavor preferences through traditional demographics just wasn't really telling you the whole story that you wanted?
Kim - 00:02:33:
I think it probably went back all the way back to 2011, if I remember right. I think that's when the idea of like foodie versus non-foodie was really becoming a thing and things that were talked about all the time. And as I was thinking about that, I was also thinking about, well, that has to apply to flavor. Depending on how adventurous you are, if you're a foodie or a non-foodie, well, that's going to translate into how you are experiencing and choosing different flavors of products. So I started thinking there. And we have a long-term research partner, Bellamy, that we do a lot of our primary proactive research with. And at that point, we started adding in a series of 18 questions to all of our surveys. And had no idea what we were doing with it, other than we were going to try to get at this foodie versus non-foodie idea. So at the end of the research and the projects and the surveys and things like that, we would loosely be like, oh, if they're 8, 9, and 10, to these questions, they're a foodie. If they're a 1, 2, and 3, they're a non-foodie. So that was kind of the start of it, was that idea of foodie versus non-foodie.
Matt - 00:03:33:
Interesting. And it sounds like you didn't necessarily have a concrete idea of, you know, what the segmentation model was going to be or what your exact outputs were going to look like. You knew there were some data points you wanted to collect and you figured that would just be a good place to start.
Kim - 00:03:49:
Yeah. You know, it was funny. So like, I don't even know if segmentation necessarily was on the radar at that point. But as we, you know, as the years went on, you know, we're like, oh, everybody has segmentation. We want one too. But I was also really cautious about that because we work with our customers who know everything there is to know about their consumers. I didn't want to, I wanted to make sure it was not something that conflicted, maybe what they had decided about their consumers and what they knew about their consumers. So kind of how could we have something that was more complimentary to what they had? And Bellamy and I had lots of discussions over the years from 2011 on. And finally, in 2018, they were like, we have a lot of data we've been collecting. We might be able to just analyze this. So it took a while to get to that point. It was on our radar. But like I said, it was a big thing. We wanted to make sure that we were not, our customers know who their consumers are. We didn't need to tell them that. So we were trying to approach it from a little bit of a different angle.
Matt - 00:04:48:
Really looking for something that was complimentary.
Kim - 00:04:50:
Mm-hmm. Yep.
Stephanie - 00:04:51:
That's so interesting that it's something that came out of then having these years of data that you could mine to build this segmentation rather than starting with this a priori idea that you're going to build a segmentation. You don't see that very often. That's really cool.
Kim - 00:05:05:
Yeah. I mean, it was definitely exciting after we'd already spent all the money on this other research. It's like, oh, there's an additional value we can get out of this research. So, you know, everybody always wants that crystal ball. I would like to say that I had that crystal ball in 2011, but I didn't. I just knew that, you know, we wanted to do something and then we were kind of able to go back and repurpose that and get to where we are today.
Matt - 00:05:29:
Very cool.
Stephanie - 00:05:30:
So one of the things that's super interesting to me about Flavor Finders is that it doesn't just categorize consumers, you know, certainly not by demographics, not even by what they consume. It looks at how they approach consumption overall, right? Both emotionally, behaviorally. What led your team to consider this sort of notion of a flavor adoption curve as a viable segmentation model when you got to that point? And then kind of related to that, how did you end up validating it as something that was meaningful and ultimately scalable for your partners?
Kim - 00:06:02:
So we've always kind of looked at the product adoption curve, right? And then flavor kind of mirrors that. So we have always looked at that for inspiration. We share that with our customers. But, you know, things that are like at inception and fall on the flavor curve are way different than things that fall on the other end of the spectrum. And, you know, we knew that there was something there to be able to try to understand. Not everybody is going to be playing at inception. You know, there are some people that aren't going to join it until it gets to the mainstream. So we wanted to kind of have that in mind as we were creating this as well. And, you know, we didn't want to just ask. I'm all about trying to figure out how to ask questions to get true answers from consumers. You know, we all know in the research industry, there's all the aspirational and socially acceptable answers that everybody gives. So whenever we're designing questions, including for this, you know, we're always trying to figure out, like, how easy is it for them to answer aspirationally? So we really try to make them ask questions that it would be very tough for them to answer that way. And then by the fact that we had these 18 questions that ranged on all those different things, kind of like how they approached flavor, how they approached shopping, how they approached going to restaurants and all of those things. It'd be very hard to answer all of those questions socially aspirationally or, you know, socially acceptable or whatever. So that was kind of the way we wanted to make sure that we approached it so that we weren't just focused just on flavor. It was kind of taking into that broader context.
Matt - 00:07:30:
So it sounds like, you know, a lot of strategic thought was put in right at the jump for how to mitigate some of the challenges that appear when you're asking respondents to report their behavior or report how open they are to trying something new and exciting. You know, from the research side, I think all that makes a lot of sense. Can you walk us through how this changes? How this actually changes the business decisions that companies were making, like in their innovation departments or to their go-to-market strategy. You know, this Flavor Finders sort of represented a shift from, you know, thinking about basic demographics to adoption behaviors. How did that go over with the business units themselves?
Kim - 00:08:17:
I think it's still something hard for people to grasp. So you mentioned demographics, and that was one really big moment for us at the end of doing all the analytics of this data and creating the segmentation, is that the Flavor Finder Segments are truly demographic agnostic. You know, we get asked all the time, what are flavors for females? What are flavors for Gen Z? What are flavors for millennials? You know, all of the traditional asks that we get. And the assumption is, is that everybody's the same. Well, at the end of our, at the end of our research, and when we created the segmentation, we discovered that we'll use millennials because at the time that was the big generation that everybody cared about. Everybody thought millennials were adventurous, right? We need adventurous flavors for millennials. And what we found out at the end of our research is that there are just as many adventurous millennials, so flavor trailblazers, as there are non-adventurous millennials, so flavor Hesitators. So this assumption that a demographic is all the same is very misleading and probably leads to that, you know, 80% of new product failure. It probably plays into that a little bit. So, you know, we wanted to make sure that we kind of understood that. And then when you start looking at the data and you overlay Flavor Finders with that, you know, like I think about all the years I've looked at data and you look at the total column and you're like, oh, what flavors come to the top? What flavors don't do well? And then when I started overlaying Flavor Finders with that, it was a completely different story. Sure, there were some flavors that if they did well overall, all of the segments like that, but of 40 flavors, there might be three flavors that are like that. And then you really start seeing some nuances. So if you're really trying to target that trailblazer and it didn't show up in the total, you're probably missing your opportunity or vice versa. It showed up in the total, but it really leaned towards a trailblazer, not a hesitator. So you're really going to miss your target on that. So I think it's really trying to help bring in that perspective early on in the product development process about where flavor plays in and what direction you should be going.
Matt - 00:10:18:
Sort of a challenging approach or was it difficult to kind of affect that mindset change in your clients or your business partners? Or did you find it was received with open arms, like a fresh take, were people really looking for something new in this innovation space to get excited about?
Kim - 00:10:37:
I would say yes, but it still is, you know, an uphill, I don't want to say battle, but an uphill journey. We'll say an uphill journey. Everybody likes it, it's kind of like a moment for a lot of people when they hear it. Yet they still want to default to what you've always done. Right.
Matt - 00:10:52:
Well, it's just easy to quantify.
Kim - 00:10:54:
Yeah. And, you know, and kind of biases and all of the things and all of the history that people have thinking about flavor and that sort of thing. It's really a mind shift. So, you know, we just keep kind of saying the same thing over and over and over again. You know, all of our research that we do, you know, we partner with you guys for a lot of our research. And we have our segments identified. You know, we have a panel that we specifically created so that we could know who our Flavor Finders were. And we can go out and know who they are straight out of the gate versus screening for them every single time. And by having that, we bring that element into everything that we do from a primary perspective and share that with our customers to kind of start continuing to always say there's more to the story. There's more to the story. There's more to the story. Every time we can, we incorporate that.
Stephanie - 00:11:45:
So that kind of makes me think that, you know, you were just talking about, you know, being able to kind of target these segments in the research that you do, like on our platform. And I'm curious, like, I just want to use like a very hypothetical example. But like, let's say that there is a company that is making lab-grown meat. That's just the first thing that's talking into my mind. But that's something that's new, right? Like, that's very new. So would your like, sort of suggestion or orientation be like, on the flavor adoption curve, that's, you know, or maybe that's not flavor per se. But like, this is new, this is something where our Givaudan's perspective would be that you need to be targeting the trailblazers in this case. And that's sort of the audience that you're going to want to focus your early innovations on and your early sort of marketing in the way that you frame the value proposition and all that, because that's the audience that's most open to that, this category, this sort of new innovation in this new category of food. Is that how you kind of think about it in practice?
Kim - 00:12:51:
Yeah, 100%. You know, one of the kinds of the tagline that we say here, it's, it's about creating the right flavor or product for everyone, not everyone. And, you know, everybody wants to create something for everyone, because gosh, that's going to get 85% of the population to buy your product or whatever. In my opinion, you know, those products already exist. Those flavors already exist and they do great. As, you know, choices become more abundant to consumers, you're never going to have everyone again. Like it's going to be very, very hard to get 85% of the population straight out of the gate, especially with a new product, because they're getting further and further and further out there, right? Like your lab-based meat is a good example. Think back to plant-based, like when Impossible Burger and Beyond Meat and the plant-based burgers came out, people that were buying those to start were your trailblazers and your investigators, which is like 29% of the population. And they took off like crazy because they were marketed and targeted to the right consumer. Hesitators, they may still have not tried any of that stuff yet, but if they did, it was years down the road when Burger King brought the Impossible Whopper to the table, right? And they would like, all right, I'll try it. It's low risk. You know, that's the thing you have to think about too, is risk means something different to every single person, every single segment. And, you know, what's risky to a trailblazer is a lot different than what's risky to a hesitator. And kind of along those, something else we've learned over the years too is the idea of adventurous is different to a trailblazer versus a follower. You know, they both are adventurous people, but oh my gosh, the way a trailblazer thinks of adventure versus the way a follower thinks of adventure are two completely different things. So understanding all of those nuances is really, really important. And having just these broad buckets and how we've thought about it for all these years is, it's very misleading, I think.
Stephanie - 00:14:45:
That makes a lot of sense. So you kind of spoke to this a little bit earlier, but you've described Flavor Finders as complementary to, you know, other segmentation models, specifically because of what your business model is, right? You work with brands who often have their own segmentation models for their products. How does the overlay of Flavor Finders to an existing segmentation that a client's using for their, you know, product roadmap and product development, how does it work in practice?
Kim - 00:15:15:
So, you know, when our customers have shared their segmentations with us before and when we see how they've defined their segmentations, we can kind of say there are some times where it's almost verbatim about how they will describe one of their segments and how we've described one of the Flavor Finders.
Stephanie - 00:15:29:
That's cool.
Kim - 00:15:30:
So we can easily say, like, you know, we think that this segment would be more trailblazers investigators where this one over here would be more Hesitators. And then when we're working with them on a project and we're, you know, bringing flavor recommendations and talking about flavor with our customers, we can then kind of steer them down the right direction. So we can say, like, okay, this segment is trailblazers and investigators. If that's truly your target, then these are the flavor profiles and the flavor directions you can go down versus a hesitator. You would want to go this way. So it really kind of brings in that complementary aspect of it and can really give them another layer that they don't have access to.
Stephanie - 00:16:10:
Yeah, like a very rich data append almost, right? It's like you have a ton more data that you can attach to their existing segmentation when they kind of line up.
Kim - 00:16:19:
Yeah. And, you know, and we are a flavor company, so we sell flavors. So we focus all of our research on flavor. And I know our customers, gosh, when they're doing their research, flavor is a very small part of it. They have to worry about so many other things, pricing, branding, packaging, messaging, all of these things. Flavor is just this, like, little dot on the radar of all the things they have to consider. So we can, you know, we want to be their partners and bring in that flavor perspective early on to where kind of like they have confidence in the flavor. Then by the time they get to really digging into their research and validating their products and all the things with their customers or their consumers, it's not so much about the flavor's good. But, you know, they're trying to figure out everything else.
Matt - 00:17:04:
Such great thought all along by way of ensuring that the results are, that the outputs can actually drive decision-making and, and, and, you know, the implications from the work are meaningful. There's another success story that I want to shine a light on with Flavor Finders as it pertains to just the sheer scale of what you pulled off. Right. So some folks, some listeners might not know Givaudan, as you said, it's a flavor company, massive flavor company. Right. So I have some hard numbers just to explain what we're talking about here. The initial study was something like 9,000 plus. Respondents across 86 distinct food and beverage categories. How the heck did you pull that off? Because those of us who have done segmentation, it's a struggle just to get alignment on how to approach the work when you're talking about a single product in a single somewhat narrowly defined market. There's a lot more ocean to boil, I'm sure. But with this work, you've really captured a, you've boiled a significant portion of the ocean already. How did you achieve that from an alignment standpoint and an analytical standpoint? How did you pull all of that together?
Kim - 00:18:24:
For sure is where our partner Bellamy comes into play. You know, they work the magic behind the scenes kind of thing, right? And by, you know, we got our 9,000 respondents by looking at seven studies over the course of, from 2011 to 2018. We had one study in there that was a little bit, 3,000 consumers, around 3,000 consumers. So that was kind of where our basis was for them to start with the analysis. And, you know, they were able to work their magic and do all the things and be able to create hundreds of potential different data sets using different approaches to kind of see what would work. And then where the other about 6,000 respondents came into play was then they were able to kind of go back and kind of validate that a little bit because we already had all of that data. And then at the end of that, you know, the larger sample size actually was like a good thing for them because they could have a lot more confidence and a lot more direction in what they had. And then at the end of all of that that we were able to do, we actually had a seven-segment solution to start. There were four segments that were pretty similar. So we were able to lump those into one to get us down to a more reasonable four-segment solution. You know, not as fragmented. That fourth segment is pretty similar. So we didn't need to split them out quite that much. But then at the end of the day, really what we were able to get, you know, was something that was differentiated. It was meaningful. It was actionable. And more importantly, it was reproducible. We knew that it didn't matter what we did. And, you know, it's very consistent with what I see since I've been looking at the data since we've started implementing this layer. It's very consistent no matter what study I look at, no matter what category I look at. So, like, in those 9,000 respondents, they were users of lots of different foods and beverages and brands and all the things. So we had a really good robust representation of all of that in this. So it doesn't really matter what it is. It's always very consistent with the results that we see.
Matt - 00:20:21:
That's like the holy grail of segmentation, right? It's like you're chasing this framework, this set of heuristics that drives the ability to distinguish and differentiate between groups. But at the same time, it has to have this, like, universal applicability that makes it work, right? And I feel like it's kind of rare that you hit something successfully at that scale.
Kim - 00:20:43:
Yeah, I think, you know, and it goes back to the fact that we are a different kind of company, right? We have to know lots of things about a lot of categories. And we don't have just one thing to focus on. So we're able to kind of look at this higher level kind of thing. We don't have to get into the nitty gritty for the consumers because that's not what we do. We're not selling anything, any one thing specifically. So it really allows us to be able to kind of have that broader approach and be able to just think about it differently compared to what our customers have to think about just based on, you know, the way their companies work and what their goals are.
Stephanie - 00:21:21:
But what I like about that, your process and the way that you talk about it, it really also just speaks to the fact that segmentation truly is both a science and an art. You know what I mean? Like, it's both. And when you talk about, like, you know, we started with seven, you know, that's what the data gave you. That's the science part, right? But your business brain got in there and was like, yeah, but there's similarity here. And there's a lot of value in kind of reducing this down to something a little bit more consumable, right? And actionable. And so I always love it when people can talk about the segmentation process and really highlight how much of it is just bringing both of those aspects of things to the table. The sort of the business acumen or just more the art side and then just the hard data and science of it as well.
Kim - 00:22:06:
Yeah, that's one thing I love about my role here is that it's truly about the insights. We don't get hung up on data because we're not making those important decisions as to whether to go or not go on our product. So it's really, it allows me to have that flexibility and that fun, I guess. I mean, I still think it's fun after all these years.
Stephanie - 00:22:25:
Yeah.
Kim - 00:22:26:
But it allows me to be able to really, you know, really see what the data is saying, what story it's creating versus getting all hung up in the numbers. And I think that allows us to have a little bit of a different perspective about how we approach research in general, but then how we were able to kind of get to this point with a segmentation.
Stephanie - 00:22:42:
For sure. Well, to switch gears a little bit, we talk a lot on the show about the evolution of agile approaches and research. I'm curious, how does Flavor Finder's model enable faster iteration and product development cycles? And where do you see opportunities to kind of further accelerate this process using either AI or predictive analytics? Do you have thoughts in those sorts of realms?
Kim - 00:23:05:
Yeah, I mean, I think, you know, going back to what I said earlier about bringing us early on into the innovation or the product process and the innovation process helps kind of have a better direction on that flavor. So that's always been the case. But then with the addition of Flavor Finders, like you can hopefully zero in even more on what flavor is going to be most relevant to your consumer. So, you know, hopefully that again, like at the end of the process and when you decide whether you're going to launch a product or not and the feedback that our customers get when they do their research, you know, hopefully it's not the flavor that's holding them up. So you don't have to go back to the drawing board there. There might have to be something else that has to be changed, but hopefully it's not flavor. So hopefully that can kind of give a lot more confidence early on in the product development process to help speed that part up at least, at least that one piece of the product. Oh, gosh, predictive analytics and AI, you know, I wish I had a crystal ball. If I had a crystal ball, I probably would not be sitting here with you today.
Stephanie - 00:24:02:
Right.
Kim - 00:24:02:
I don't know how it plays into the predictive part. I think where I think the AI part could be interesting is how Flavor Finders overlay with things that we already know or already exist. There's lots of information out in the world that you can get. You know, there's secondary research suppliers. There's articles that are written. There's all the things. There's so much information. And when you see those things, there's always great insights in there and some really good foundation, but there's always more to the story. And it would be interesting to know, like, some stat is published in an article somewhere. And it's like, well, okay, is it 65% of the general population or is it 65% of trailblazers, which is a much much different story. Right. So I think that one way I think could be interesting with AI is kind of how you can incorporate Flavor Finders into what you're doing with AI. And when you're looking at all of your insights together or when you're trying to pull in secondary and primary, like, how does that all work together?
Matt - 00:25:07:
Super interesting. I wanted to offer a quick plug. You have a great white paper all about Flavor Finders available on your website. We were geeking out over that before the call. And in there, it sort of talks about a lot of the things that we've already covered, the importance of driving the segmentation from a... A behavioral perspective versus a demographic perspective, that got us thinking, okay, behaviors, well, behaviors shift over time, of course, right? Depending on the person in question's lifestyle, their life phase, people change. How do you see Flavor Finders capturing that dynamic, that variable? Or if it's more of a point in time type of thing, what is the next iteration of Flavor Finders going to do to sort of capture this dynamic of changing behaviors?
Kim - 00:26:02:
Absolutely. Some people's preferences can change. Like a good example would be somebody whose, you know, parents are Hesitators. They go off to college, they meet new friends and they get out and they do their thing and they find this whole new world that they've never been exposed to, right? But there's still going to be plenty of people that still stay on that hesitator. So I think you might have people that shift here and there, but a hesitator is not all the, like, My colleague, I'm a trailblazer. My colleague is a hesitator. She is never going to move from a hesitator to a trailblazer. Never going to happen. Like, she is just never going to change her behaviors so much that it's going to make her jump from one segment to another. I think the younger generations, you know, possibly could change. But at the end of the day, you're still going to have people that fall into each one of those segments for all of the demographics. I don't think, like, you know, our percentages, like our, you know, 14% is trailblazers. I don't think that's going to change, you know. And I think the only time you really run into the issue is, like, with the panel, you know, that we've profiled. But we'll refresh that and we'll update that. But when you're doing your research and you think about applying this to every single thing that goes down the road, I think that break is still going to always be the same. I don't think all of a sudden you're going to have 50% trailblazers one day and 14% Hesitators. Like, it's never going to change like that. So that is a little bit different from a lot of other segments where life stage and all those things really do come into play. Be a little bit of that, but I don't think people will change a whole lot. Once they've kind of established their adult life, which is just based on 18 plus at this point, once they've established their adult life, they're probably not going to change a whole lot.
Matt - 00:27:42:
So it's more about identifying these longer term positions on adventurousness and innovation and less about sort of evaluating where people are today specific to their openness to new flavors. It's more about really identifying what type of person they are when it comes to trying new things because those larger scale truths are less likely to change over time.
Kim - 00:28:06:
Correct. Correct.
Stephanie - 00:28:08:
Yeah, that makes a lot of sense. I think the one area where as if we were all just had infinite time and resources where I was like, oh, it would be so cool. And we were academic researchers that the sort of developmental aspect of it with kids would be so interesting because kid flavor tolerance is quite different, right? Like they start with Matt and I are both parents. We're thinking about our kids right now. And I'm, you know, I'm absolutely in the chicken nuggets and pizza phase, which I feel like will last like 10 years. Right. But like, but those kids grow up to be many of them like trailblazers and investigators and followers and such. And I'm very curious how they get there. Do you guys think about that kind of stuff or do you really try to stick to sort of adult flavor profiles?
Kim - 00:28:53:
I mean, we have talked about it, but, you know, there's always that lovely budget that falls.
Stephanie - 00:28:58:
Of course. Yeah.
Kim - 00:28:59:
Yeah, we for sure. Like, obviously, if parents are Hesitators, they're not introducing their kids to anything new. Where like, you know, I'm a trailblazer. And with our daughter, we've always been like, here, try this. And she has always like we've always like forced her to take a bite of something. She's now 18. So I will add that in there. So those first few years were very painful. And, you know, she would take a bite of something and immediately take a drink. And then I mean, and I would be like, no, no, no. Chew it up, swallow it. Then you can have a drink. And that was it. Like we didn't make her continue to eat it. We never made her order anything weird, but it was always like you just have to try it. And at 18 and probably not even at 18, like 12, we're going to a restaurant and she's ordering the chargrilled oysters for her entree.
Stephanie - 00:29:44:
I love it.
Kim - 00:29:45:
Because, you know, like but that was because we exposed her to that. Like Debbie's kids would never do that because they're just they've never grown up doing any of that kind of stuff. So, yes, for sure. I kind of went off on a tangent, but it just kind of kind of illustrates it a little bit better. Yeah, I would love to get into that to where we can kind of understand kids preferences and then how that overlays what their parents are and the things that you expose them to. And all, you know, parents only have so much influence. I mean, you could be a trailblazer and your kid could be hard, fast chicken nuggets only. Who knows?
Stephanie - 00:30:19:
Totally.
Kim - 00:30:19:
But, you know, I did. That is definitely an avenue that would be very interesting to explore further. It's just time and, you know, time and money. Always the thing, right?
Stephanie - 00:30:28:
Always the limiters. Absolutely. Your point about exposure is so well taken, though. I've read that it takes an average of 30 exposures before a child is accepting of a food, which is a lot of exposure.
Kim - 00:30:40:
And I think the other thing my daughter told me is I think it's every seven years. I think your taste buds change.
Stephanie - 00:30:46:
I've heard that too, yeah.
Kim - 00:30:46:
So, like, that's, you know, that's that's another factor. So it's all of these things why, you know, looking at these high level generalizations just really start to derail the success of a product, whether it's from flavor perspective or just willingness to embark on something new.
Stephanie - 00:31:03:
Yeah. You talked a little bit earlier about risk, and I wanted to dive into that a little bit more because I think that's really interesting. One of the most compelling insights from Flavor Finders is how segments differ in their willingness to take risk with flavor and what risk means to them, like you said. In a market where novelty is both an asset for product companies and a liability, how should brands be thinking about and calibrating risk when they're launching to different Flavor Finder Profiles?
Kim - 00:31:32:
I think I understand that, right? Like the trailblazer, their risk level's extremely low. If they go to the grocery store and see something and it's $10 and it's brand new or it intrigues them or whatever, they're going to buy it. They don't care how much it is. They're going to try the new restaurant. And, you know, that doesn't really matter on income. Like somebody could be lower income and still be willing to do that because it's not a risk to them. It's worth spending that money on it. Where a hesitator is like, oh, if I buy this and I don't like it, I've lost this money and I could have used it someplace else or I could have done something else with it. And it doesn't mean that Hesitators are cheap or that they're low income. It's just where they place their value on something.
Stephanie - 00:32:24:
Yeah.
Kim - 00:32:25:
I mean, I'm pretty much going to consume whatever it is. It's not going to turn me off that much. But a hesitator would be like, oh, my gosh, I just spent $10 on this drink and I don't like it. And I am not going to drink it because it tastes so bad or whatever.
Stephanie - 00:32:40:
Right.
Kim - 00:32:40:
So it's really it's, you know, it's just one more element of understanding about Flavor Finders and where their risk tolerance is. Very low risk for a trailblazer, Hesitators have a very high risk tolerance.
Stephanie - 00:32:53:
Gotcha.
Kim - 00:32:53:
And that's also could be something from a food perspective, but someplace else they might be willing to risk, you know, like maybe they will go by the new technology thing, even though they're a hesitator when it comes to food.
Stephanie - 00:33:06:
It's very specific to food. Got it.
Matt - 00:33:09:
That actually brings up one of the questions we had for you, which was like, we talked to folks from a lot of different industries. We love when we can find ideas or concepts that have legs for cross-pollination, right? So when you think about Flavor Finders, do you see potential for this framework to be applied beyond food and beverage, say in wellness or supplements or? You know, beauty, anything. Are there universal truths here that might apply outside of the category?
Kim - 00:33:43:
I think so. I mean, you know, we'll ask in our surveys, we will ask different usage and attitude questions and you can see differences and that sort of thing. We actually do have another segmentation that we put together around health and wellness finders. So it's kind of exploring that health and wellness space. And we've overlaid Flavor Finders with it. And there's a lot of similarities, you know, there's a lot of similarities with the people who are really active and engaged in the space versus people who are not. But, you know, I think the one thing is, I think the difference is in some of these things where you have all of the people represented in Flavor Finders, right? Every single one of them are eating food and beverages. And but the way they interact with flavor is different. Where with something like the health and wellness space, we found out like 50% of the population does not care about any of that stuff.
Stephanie - 00:34:33:
Right.
Matt - 00:34:34:
Right.
Kim - 00:34:34:
So that was like, okay, that's a big aha moment. Because, again, everybody thinks like, oh, everybody wants it. No, 50% is like they don't even care. But within those other segments, sure, like our, you know, our more active people are definitely falling more into that trailblazers and that investigators spot. But then like the third one, which is more of our like our reactors, that could be trailblazers and investigators just because they just it's not as much on their radar or whatever. So I think you see a lot of tendencies that kind of mirror what Flavor Finders is. But there can definitely be some exceptions to it. But, you know, I definitely think there are overlaps with other segments and kind of how they interact with other things in their lives. Not everything, but definitely some, some categories. You could see some similarities.
Stephanie - 00:35:21:
Something that I was wondering about and it's especially in the context of reading. I love that you guys do this, but reading the blog posts, people from within your org who identify as a segment and then they write a blog post. That's like a day in the life of a hesitator or whatever really brings it to life in such a compelling way. And it made me, you know, really think about the role of storytelling in Flavor Finders. Do you have an example where the segmentation uncovered maybe a counterintuitive insight that reframed a story a client was telling themselves or a brand that you work with about their target audience?
Kim - 00:35:59:
I can't think of any, you know, I can't think of anything super specific. Like I said, they've shared segmentation before and I think being able to overlay some of what we know about Flavor Finders and how that really overlaps and really complements what they have can really get them focused. Like they can sit here and say like, oh, this consumer is really adventurous, but they still think that the consumer is adventurous. They think it's broader, you know, reach or whatever. And then we could say, okay, but yes, this is adventurous, but that is also what that means. It's only 14 percent of the population when it comes to flavor. I really think that, you know, where we've seen such a shift is when you look at, like, for instance, we do a fit and appeal study. We have a fit and appeal program that we've been running since 2011. We refresh it every couple of years. And we do it in the non-alcoholic space. And for years, like I've looked at the data and it's like, oh, we kind of bucket the flavors. We kind of have our mainstream flavors. We have our emerging flavors and we have our niche flavors. And that's looking at how appealing it is and how well it fits with a category. And that's kind of what we've, you know, used a lot of our foundational flavor inspiration for. And then when we overlaid Flavor Finders with that, the story just completely started to change. So when you looked at like those, that mainstream bucket, for instance, and there might have been 20 flavors in that, when you overlaid Flavor Finders, there were only like six flavors that showed up for hesitators. And if you just stopped at that mainstream, you and your target's a hesitator and, it wasn't one of those six that you launched, and it failed. That's probably why. Because you think it's mainstream, but it's not mainstream for Hesitators. So I think that has been, you know, we've seen that happen a lot where a flavor or a flavor doesn't do well. Maybe it falls into a niche and your target's a trailblazer, but it shows up as one of their top flavors. And you would miss that if you were targeting a trailblazer. Like that would be how you would pull that trailblazer in. So I really think that that's probably the best example that I have of how we've seen just how the data has shifted over the years by incorporating Flavor Finders into our surveys.
Stephanie - 00:38:04:
Yeah, that makes a lot of sense.
Matt - 00:38:06:
Do you have any plans for a Flavor Finders 2.0? Are there any planned iterations bringing in different data sources, changing the approach up at all? Or is the next rendition of Flavor Finders just going to be kind of staying steady, Eddie, and getting that longitudinal view?
Kim - 00:38:28:
I think it's still continuing to figure out how, where else we can incorporate it. I think that as far as the segmentation itself goes, you know, I think we're pretty confident in that. And that's going to kind of be like our framework that we're going to continue to use. I think continuing to explore those segments definitely would be interesting. Like we did a deep dive into followers because I considered them very noisy when I was looking at the data. They're, you know, they're right. They're just a little bit more or less risk adverse than Hesitators, but they're kind of along that line. And I would start seeing like they liked they either liked everything or they were neutral to everything. And I'm like, this is just weird. Like they would like a weird flavor that a trailblazer wouldn't like. And I'm like, yeah, I don't think that's going to line up. So we actually did a deep dive into them a little bit more with some journaling and ideas. And we, you know, we found out that they're noisy. That is that noisy group that everybody worries about. And they're the ones that say one thing on paper, but what they actually do is completely different. So by digging deeper into them, like that really helped us get a little bit more perspective on that. You know, I'd love to do that with all of our segments. I'd love to explore the kids' things. I'd love to explore, you know, how we can incorporate this into other data points and secondary pieces of information that we find and that sort of thing. So I think there's definitely ways to make it bigger and broader and, you know, more, more ways that it can apply. But I think the framework, I think we're pretty, we're pretty, pretty confident in that framework. And I think that'll kind of continue to stay as is.
Matt - 00:39:59:
I love that. That's like the beauty when you get a good segmentation framework to stick to, right? Is that then you can just focus on that deep learning and really developing your understanding. I think that's really, really exciting.
Kim - 00:40:09:
Thanks.
Stephanie - 00:40:10:
Absolutely. Well, Kim, to kind of wrap us up here, there are a couple of questions that we always like to ask our guests. The first is around sharing some of your wisdom with the next generation. Do you have a piece of advice that you'd offer to someone who's kind of just starting out in the world of consumer insights?
Kim - 00:40:28:
Keep the curiosity and always be critically thinking, I think. You know, I mentioned earlier about how I'm constantly trying to figure out how to ask a question that is not just being able to somebody give a socially acceptable or an aspirational answer. I also always try to think, like, what is this going to give me? Like, if I ask this question, how do I use this? How is this actionable? You know, so that is always what I keep in mind when I'm designing questions and almost more importantly, answers. You know, if you use a scale for your answer or it's a yes or no or whatever, like, how does that, what story can you tell with that data? If you can't tell a compelling story with whatever result you're going to get back, then that probably is not the right scale or question or combination, you know, whatever. But that's always kind of the lens that I'm looking at is to really try to, and my marketing team is constantly like, I'm always pushing back on that. I'm like, well, what are you going to do with the data? Like, so you find out that nobody's consuming a certain category because they don't like the flavors. Well, okay, but all right. But what specifically, you know, what's specific about that? So it's just, I think that would be my biggest piece of advice.
Stephanie - 00:41:38:
Yeah, I love it.
Matt - 00:41:38:
I think it's great advice. Like, yeah, starting with the end in mind and driving towards, you know, a particular goal in your data structure is just like spot on. I think that that nails it. My question, the question I always ask, you've mentioned a couple of times that you do not have a crystal ball. I'm sorry, but I need to ask you to look into your crystal ball and see, you know, from your perspective. And it's interesting, too, from your perspective at Givaudan in this very front end innovation space. What do you see changing in the consumer insights world over the next few years and how brands are using insights to drive strategy in the face of everything that's changing in our industry right now? What concrete things do you think are coming our way?
Kim - 00:42:26:
I mean, it just keeps getting faster and faster and faster, right? We need to be able to make decisions quicker. We need to be able to get insights quicker and all of the things. And I think with AI and that sort of thing, that's going to be even more of the expectation. I think that AI is going to maybe help us be able to come up with ideas, whether it's survey ideas or question ideas or concepts, you know, in the case of our customers, to kind of start getting like a framework and like a good foundation. But I think you're always going to still need to figure out how to incorporate the actual consumer plug for research so that it doesn't go away. But, you know, there's still something to be said for having somebody to like think of all of the things. Like when we're looking at data, we're not just looking at this data point. We're considering a multitude of data points and how they interact with each other. So I think having that human element is still going to be there. But I think that the AI is just going to be able to help that happen quicker and also find themes that you just don't, you can't find because there's just no way that you can look at the data and all the different options. But you still have to have somebody thinking about how I want to look at the data and typing in that question. And then it spits out the answer really quick versus you looking at all the tables and creating new tables and all of the things.
Stephanie - 00:43:41:
Yeah, yeah, yeah.
Kim - 00:43:42:
Yeah.
Matt - 00:43:43:
Yeah, no, I think that's a great call out. We've noticed sort of a theme of more openness to embracing, you know, what we're calling today AI tools for that generative thinking, like using it as inspiration for coming up with new ideas, new concepts, answer options, as long as you are using your critical brain in the background. Like there's, I definitely see things moving in that direction.
Kim - 00:44:09:
Yeah, I don't think it's going anywhere. So we've got to figure it out. I'm a little slower on that adoption curve, but I'm getting there.
Stephanie - 00:44:15:
It's a journey for sure. Well, Kim, this has been an excellent conversation. And I have to tell you, I'm going to go type myself using the Flavor Finder typing tool and find out what I am. So I will keep you posted.
Kim - 00:44:29:
I will let you know.
Stephanie - 00:44:31:
Yeah. Thanks so much.
Kim - 00:44:32:
Thank you for having me.
Matt - 00:44:34:
Thank you.
Stephanie - 00:44:36:
Curiosity Current is brought to you by AYTM.
Matt - 00:44:40:
To find out how AYTM helps brands connect with consumers and bring insights to life, visit aytm.com.
Stephanie - 00:44:47:
And to make sure you never miss an episode, subscribe to The Curiosity Current in Apple, Spotify, or wherever you get your podcasts.
Matt - 00:44:55:
Thanks for joining us and we'll see you next time.
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