What the C-Suite Values in Insights with Wella’s Chris Chesebro

[00:00:00] MRII Announcer: Welcome Tori’s Insights and Innovators podcast, where we talk to top market research professionals to get their inside stories about innovative and enduring best practices. Today’s episode is sponsored by Full Circle, named the Panel Company of the Year. Full Circle is a leading provider of high quality online insight, leveraging survey experience, advanced tech, flexible community strategies, and unparalleled quality controls.

[00:00:27] MRII Announcer: We give you immediate access to. Proven data for better insights. Now, here’s your host for today’s episode. Welcome to today’s episode, 

[00:00:36] Katie Gross: what the C-Suite values in insights with Wellers, Chris Chesbro. I’m your host, Katie Gross, president of Suzy, and in today’s episode we’ll explore how insights and analytics shape decision making at the C-suite level.

[00:00:50] Katie Gross: From big picture brand strategy to day-to-day execution and what it takes for insights to truly make an impact in a fast changing digital first world. [00:01:00] Our guest is Chris Chesbro, global Chief Digital Officer at Weller Company, one of the world’s leading beauty companies with a family of brands that I use almost every day, including Claral, OPI, Nioxin, GHD, and Weller Professionals.

[00:01:17] Katie Gross: Chris leads the company’s one digital team overseeing digital brand building, e-commerce, data technology, and digital innovation, and he reports directly to the CEO as part of well as executive leadership team. Welcome Chris. 

[00:01:31] Chris Chesebro: Thanks, Katie. Very happy to be here. 

[00:01:33] Katie Gross: Awesome. Thanks for joining us. So let’s get started.

[00:01:37] Katie Gross: Can you talk a little bit about the role that insights and analytics plays in your day-to-day decision making as a member of the C-Suite? 

[00:01:45] Chris Chesebro: Absolutely. Um, so I think just to start off, uh, just to shape a little bit about what digital means for Wella, uh, and then how insights impact that, because digital really means something different for just about every company that has a digital function.

[00:01:59] Chris Chesebro: Um, within our [00:02:00] company, we really look at it as three distinct pillars. Uh, the first is our digital experience and technology. That’s everything that we put in front of our customers and our consumers. Uh, so all of our brand websites, all of the tools that support our salon partners, really anything that gets visualized in front of one of our, our B2B customers, like our salon partners and our nail nail technician partners.

[00:02:22] Chris Chesebro: And then everything that gets visualized in front of our consumers. Um, the second pillar is, is e-commerce. This is really our commercial activations framework for our e-commerce business. Um, and then the third pillar is data and, and ai. Um, and that covers everything from really, really straightforward master data management.

[00:02:43] Chris Chesebro: So, you know, how are we naming the products, what ingredients are in them, all the way up to the things that are more leading edge slash maybe shouldn’t be leading edge anymore. Like everything that’s happening in, in the AI world. Um. So just to kind of set the frame of what those three different areas are.

[00:02:58] Chris Chesebro: Um, and [00:03:00] the good thing about. All of those pillars and all three of those pillars is that the ability to glean insights about what activities are happening with our customers or our consumers in that digital experience ecosystem down to the financial reporting of the company. All of that sits in, in, in one overall place.

[00:03:19] Chris Chesebro: So our approach really is starting with what is the data saying? And then layering insights and, and, um, human intuition and experience intuition on top of those insights. So we really try to start with a data first decision making process. And then once we have that data in front of us, that’s where the experience that the different members of the team and different parts of the organization bring in that business intuition to help us get to something that’s going to be an even better.

[00:03:49] Chris Chesebro: Decision, uh, because sometimes the data is going to tell you one thing, but you understand that the reason it’s saying that is because of something due to seasonality or [00:04:00] because we had a product launch that was much more successful than we thought, or maybe not as successful as we thought. And if we use that information to forecast all of the future decisions, we would be using potentially an incorrect base.

[00:04:11] Chris Chesebro: Uh, so that’s where I think that. That, that interplay between what the data is saying and then what your business context and your, your human intuition on top of that data is really important to be able to make decisions that are going to take us in the right direction or keep us going in the right direction and not shift too far off course.

[00:04:31] Katie Gross: That’s a great point that you raised. I think that’s, you know, it’s, it’s critical that what I see a lot of mistakes on our kind of correlation and causation, um, when people Yes, exactly. Data and data only. Um, and that intuition of being in market, utilizing those products, um, is, is so key. 

[00:04:47] Chris Chesebro: Absolutely. And, 

[00:04:48] Katie Gross: and that particular types of decisions that the, kinda the C-suite your company find, you know, being indispensable.

[00:04:55] Katie Gross: So you have to have the data first in certain decisions. 

[00:04:59] Chris Chesebro: [00:05:00] Um. I would say there’s always going to need to be some level of data to inform a decision. Mm-hmm. Um, and that data doesn’t always need to be empirical. That data doesn’t always need to be quantitative or statistical. Sometimes that data is the intuition that you understand what’s happened in the past through previous life cycles of a, of a process.

[00:05:23] Chris Chesebro: Um, but. I like to say that there are no decisions that are 100% guaranteed other than flipping the light switch on or flipping the light switch off. But even then you’re not sure because power might be out. Um, so, um, there always needs to be some level of educated guess. And I think the role of data plus intuition is making that education.

[00:05:45] Chris Chesebro: As concrete as possible and as complete as possible for the specific decision that you’re trying to make now for a decision about when you should launch a product or where you should locate a new team to build out a new [00:06:00] capability. Those are big decisions. There’s heavy amounts of investment behind them.

[00:06:04] Chris Chesebro: There’s a long-term nature to them. Those are decisions that I would want to have A lot more data points. Yeah. But whether or not I’m AB testing an ad and I put the logo in the bottom left or in the middle left. That’s a much lower burden of decision making. I don’t need as much data to make, make that type of decision.

[00:06:22] Chris Chesebro: Mm-hmm. Um, so I think it’s very important that you treat every, every decision as an educated decision, not a, a 100% empirical decision. And then you put the burden of proof at different levels, depending on the importance of the decision that you’re making. 

[00:06:38] Katie Gross: Mm-hmm. That makes a lot of sense. Do you have any kind of real world examples of where insights did play a pivotal role in shaping a major decision?

[00:06:47] Chris Chesebro: Yeah, I can give a couple of, uh, a couple of good examples. You know, I, I would say one would be from several years ago, and it’s gonna be an older one, so it might sound a little basic in today’s world. Um, but I think it’s a good, [00:07:00] a really good example of that, um, for our, our B2B customers. So again, for our salon partners, hair salon partners, there’s a mix of people who are salon owners, and then there’s a mix of people who are specific hairdressers and.

[00:07:14] Chris Chesebro: Um, up until about two and a half, three years ago, uh, the experience that we gave to them from a digital perspective was purely via a website. There was no dedicated mobile experience. Obviously, you could access the experience, the website experience through the mobile browser on Safari Chrome or what have you.

[00:07:31] Chris Chesebro: Um, but we didn’t have a dedicated mobile experience. But what we saw was that. As customers were building their carts throughout the course of the week, over multiple days, they were adding things to the cart via their mobile phone. Through their smartphone because they were doing it throughout the course of the day as they finish a tube of color or they finish up a bottle of shampoo.

[00:07:52] Chris Chesebro: Yeah. And then they were reviewing the cart on their computer or on their iPad before they went to go and check out. [00:08:00] So that’s an area where the actual user experience data directly informed the. User experience that we put in front of those customers through the, the, the way that we designed our mobile application that we’ve now had in place for a few years, um, for, for those customers.

[00:08:17] Chris Chesebro: Um. That’s why we’ve introduced features that make it very easy for somebody who is just using their phone throughout the course of the day to quickly snap a photo or quickly write a message. The entire experience around building a cart is designed around that. Um, so that’s a, I would say. One really good concrete example of, of where we, um, where we’ve used that type of data to directly impact user experience.

[00:08:42] Chris Chesebro: Um, and another one I would say would be the way that we looked at where the majority of our growth is going to be coming from. Mm-hmm. Um. Again, without giving away anything that’s too proprietary. We had a, a benchmark of how large our business was [00:09:00] in our e-commerce channels for consumers, and we had based that on information that we had historically.

[00:09:06] Chris Chesebro: Um. And, and, uh, about a year and a half, two years ago now, we took another pass of that using a couple of different data sets. Um, so we brought in data that we had not previously purchased, and brought in some data that we had not previously used in the past. Um, and we applied that to the weight of our business relative to total, uh, total.

[00:09:26] Chris Chesebro: Online and offline to just looking at the online channels. And, um, it helped us get a, a clearer understanding of where the vast majority of our growth is going to come from. And where we had previously banked on it, coming from one set of retailers, uh, we realized that our relative penetration with those retailers was actually quite strong.

[00:09:47] Chris Chesebro: Um, and places where we thought that we had stronger positions. We actually had a lot more opportunity to grow and that completely changed the way that we approached, um, our business and completely changed the way that we structured our [00:10:00] team to deliver against that growth. So obviously we still put a lot of emphasis on the retailer that is already substantial for us, but we allocated more resource to the channels and the retailers where we didn’t have as much, um, uh, penetration yet.

[00:10:13] Chris Chesebro: Um. So that sounds relatively straightforward, but it’s one of those things where you need to check that confirmation bias on a regular basis because just because something was quote unquote true when you made the decision, the, the data, especially when it comes to things like, um, e-commerce channels where there really is not a great syndicated data source.

[00:10:34] Chris Chesebro: Yeah. Um. Uh, you need to be checking that on a very regular basis to make sure that you’re not putting more eggs in a basket than are necessary and not enough eggs in the basket where you have a greater opportunity. 

[00:10:47] Katie Gross: Yeah, those are two such, you know, great examples. Um, the first one I, I really like in particular because, you know, we often sit behind desks and so we’re such exactly designing surveys and designing research, et cetera.

[00:10:59] Katie Gross: We forget [00:11:00] that often a lot of B2B um, audiences such as hairdressers and such as teachers, are actually not sat at the desk in front of a laptop all day. And so that, that, um, their kind of day to day is very, very different from ours. It’s, it’s tricky to, to have that kind of empathy and think about what they’re Exactly, you’re right.

[00:11:17] Katie Gross: She’s finishing that tube and then needs to order product while stood up whilst waiting for her client to, to have her hair exactly kind of cure. So from your perspective as a, as a senior executive, what makes for a good insights professional or a good insights team and what makes them effective do you think?

[00:11:36] Chris Chesebro: I think a baseline is always curiosity. Mm-hmm. Uh, to me that is one of the most important professional, quote unquote soft skills that just about everybody needs to have. But I think that someone who works in an insights function, absolutely. That’s a mandatory for them. Um, there’s always another reason.

[00:11:56] Chris Chesebro: There’s always a piece of context that needs to be considered. And [00:12:00] uh, and I think that that baseline level of curiosity is, is really important. And that comes not just to the way that data is then represented, or insights or analytics are then represented, but it comes also in terms of. A willingness to learn new capabilities and a willingness to learn new tools.

[00:12:18] Chris Chesebro: Um, and, and I think that if there’s any one single skill, I would say it’s curiosity. And I do believe that that’s something that can be trained. Um, you know, you obviously need to have an inherent sense of curiosity, uh, but I do believe that. Once you see the benefits of learning something new and you see what that does for your ability to do your work and, and, and the, the ability to get recognition for that work, it then fuels an, in an increase, in an increase in desire to be even more curious.

[00:12:50] Chris Chesebro: Uh, so that to me is the most important. Single skill, most important single desire that I think insights professionals need to have. Now, obviously, you need to check your [00:13:00] work. You need to make sure your numbers are correct. You need to make sure that your, your insights tie to those, uh, to those, um, to those numbers and to that research.

[00:13:08] Chris Chesebro: Uh, but I think that curiosity is incredibly, incredibly important. 

[00:13:12] Katie Gross: For sure it’s asking why, but why, but why. Again, I remember my nephews when they were little, um, and one of them was definitely in that kind of three. He was three years old and just asked why to everything, and I, mm-hmm. It made me think as why we were driving to Cadbury’s World in the uk.

[00:13:28] Katie Gross: Right. And I really had to think and answer him, you know, and I’m like, wow, this, over the course of this 30 minute drive, this. Child has definitely learned a lot more from me than I would just because he just kept saying why. 

[00:13:39] Chris Chesebro: Exactly. And I think one of the, one of the questions that I’ve seen be very effective in the past is what about what you saw helped you draw that conclusion?

[00:13:51] Katie Gross: Yeah. 

[00:13:52] Chris Chesebro: Because then it really starts to break down the different components of the thought process. Mm-hmm. And if you’re asking people. [00:14:00] That type of question, they are then required to think through it for themselves. And it’s a little bit like prompt engineering in a certain respect of if you, if you treat an AI tool like Google, you’re gonna get a Google-esque response.

[00:14:14] Chris Chesebro: Yeah. If you treat it like something you’re gonna have a conversation with, you’re gonna get a better response. You’re gonna get a higher quality output from it. And um, there’s a region reason why it’s called. Natural language processing. Yeah. Um, because you, you, you need to think about that even in the way that you’re asking questions of the human beings who are in, in front of you.

[00:14:35] Katie Gross: Mm-hmm. For sure. We’ll come on to everything, AI shortly, but, um, one question I had around, uh, so we have, you know, curious people who. You ask them how did they come to that conclusion? But is there a particular way that the insights are delivered, um, that make a real difference to whether it is influencer decision or not?

[00:14:54] Katie Gross: I can imagine charts and graphs are not necessarily everybody’s favorite. Mm-hmm. 

[00:14:58] Chris Chesebro: No, I, I, I think [00:15:00] everything is contextual there. Mm-hmm. You know, insights just like, just about everything else. In a business, they serve a purpose to drive a business outcome, so. What business challenge am I trying to solve?

[00:15:10] Chris Chesebro: And I think that’s where starting with that context of here is a problem I need to fix, or here is an opportunity I need to frame, or here is a process that I need to inform. And always starting with that problem to be solved or issue to be addressed, or opportunity to be ameliorated, you know, what is starting with that and then linking the way that the insight.

[00:15:35] Chris Chesebro: Delivers against that business challenge or business opportunity is I think, the most important. And then from there, every organization is different. You know, uh, some organizations are huge on memos. Some organizations are huge on beautiful PowerPoints. Some organizations are huge on very detailed, ugly PowerPoints.

[00:15:56] Chris Chesebro: Um, you know, it’s, it, to me that’s where the organizational context [00:16:00] comes in on the way that the company processes information. You know, in my. In my previous experience, I worked for a company where the presentation happened. In the meeting. There were no pre-reads, there were no pre-discussion, everything, everyone came into the room blind except for the person who was presenting.

[00:16:18] Chris Chesebro: Um, and and I now work in an organization where pre-reads are paramount. And, and the discussion in the room is not about walking through the presentation nine times outta 10. It’s about having a discussion about the options that we put on the table, uh, and then having a debate about which of those options are the, are the best for our organization.

[00:16:38] Chris Chesebro: So, um, if I applied my rule book from my current organization and my previous organization, I would not have been successful and vice versa. Mm-hmm. Yeah. So that’s where I think it’s really important to understand the. The vernacular of the organization and the way that it processes information. 

[00:16:54] Katie Gross: That makes a lot of sense.

[00:16:55] Katie Gross: The company culture, we’ve, uh, we’ve, uh, Susie have adopted pre-reads, but we do it at the [00:17:00] beginning of the meeting, so we share it out. Everybody has the same 10 minutes to read through, because often when we try to do pre-reads before it’s like, oh shoot, I haven’t had time to read it yet. 

[00:17:09] Chris Chesebro: Exactly. Exactly.

[00:17:10] Chris Chesebro: Who 

[00:17:11] Katie Gross: wants to double check? People have the time in the meeting to do the reading as well. 

[00:17:14] Chris Chesebro: Exactly. 

[00:17:15] Katie Gross: So thinking about the kind of wave of innovation in recent years, everything from predictive analytics, real time data platforms, everything, AI and more recently, voice and video and conversational insights, which of these newer developments have you found to be most exciting or most valuable as you’ve seen them so far?

[00:17:36] Chris Chesebro: I think it’s most likely the latter. It’s the conversational component. Um, the ability, the ability to query something and dive deeper into it is, I would say the, the thing that’s been most valuable for me. Um, and I’ll give you a cheeky personal example. Um, you know, I’m very passionate about wine and [00:18:00] food and travel.

[00:18:01] Chris Chesebro: Um, so I’ve, I’ve, uh, I’ve created my, my own assistant, um, in chat GPT on my personal chat, GPT. That’s basically my AI summit. Um, and it, it’s something where I’ve used previous visits to wineries or restaurants, previous wines that I really liked and things like this. Um, and built, um, a very simple model off of that that I now use to help me plan future travel.

[00:18:29] Chris Chesebro: Um, and that’s where I can actually have a conversation with it about, you know, I really like this, this is why I really like this. Can you help me find something that’s similar to that in Munich as an examples, I have to go to Munich. Um, and I think that’s where the, the conversational aspect has been, I would say the most valuable thing for me.

[00:18:49] Chris Chesebro: Um, I’ve not been able to replicate that professionally yet. Um, uh, that’s something that is still. Work in progress, I would say, on a number of different fronts for us. Um, but [00:19:00] if I can do it personally, I know at a certain point in time we’ll be able to do it from a professional perspective, um, as well. Um, so yeah, I think this is a question for me of just a total change in interfaces, um, and that conversational interface is.

[00:19:18] Chris Chesebro: My personal opinion not gonna go anywhere for a while. Whether or not that conversation happens like this, or it happens via text message or WhatsApp, or the direct interface on chat GPT or copilot or whatever it might be. That’s probably gonna evolve and probably will be different country, over country.

[00:19:35] Chris Chesebro: Um, but, uh, I think that conversational interface is, is here to stay. 

[00:19:41] Katie Gross: For sure I chat to my chat GBT daily. I gave her a name, Cleo gave her a British accent accent obviously as well. And I ask her for everything from interior design questions to what should I be eating today, et cetera. So, yeah, exactly.

[00:19:54] Katie Gross: Great. But in in the research world, we, we had launched Sui Speaks, um, recently and [00:20:00] what I think has been fascinating about it is I spent a lot of my early twenties. Going through code frames and coding open ends. And so I’m like, Ugh. The less open ends the better in a survey. Now it’s like the complete opposite.

[00:20:11] Katie Gross: It’s the more conversation the better because we can easily exactly quantify the results. Um, which is great. Exactly to change the game there. Thinking about your consumers. So consumers of course, are engaging with brands more digitally than ever. And now of course, searching, not through Google, but through, um, interfaces like chat, GPT and shopping online, interacting with social platforms, shifting so quickly.

[00:20:35] Katie Gross: Has that shift really changed the way that you gather insights or the types of demographics that you are researching? 

[00:20:42] Chris Chesebro: Um. I think the short answer would be not yet. Mm-hmm. Um, because to me, a lot of these tools and these interfaces are accessing the same data in a new way. Mm-hmm. So it’s not necessarily that there’s been a [00:21:00] fundamental shift in the demographic makeup of our consumers just because chat GPT and Microsoft Copilot and Claude, et cetera, exists now.

[00:21:07] Chris Chesebro: Um, they’re, to me a, a more direct route. To having a conversation or a more direct route to gathering insights in certain respects. But the data is still there. I mean, they’re still, they’re still accessing the same data that. Many, many other sources were accessing. It’s just greatly simplified the way to access it.

[00:21:28] Chris Chesebro: Um, so I would say it hasn’t really fundamentally changed yet, and I’ll give a really good example. I think, at least I think it’s a good example of this is, um, there’s been a whole influx of, uh, cold calls about. Winning an ai, SEO and how do we win an ai SEO? Right? And there are these now companies that say that they’re ai, SEO agencies.

[00:21:50] Chris Chesebro: Mm-hmm. Um, and from what we’ve seen, what that’s showing is that what’s winning in regular SEO is winning in ai, SEO. [00:22:00] So it’s another way of looking at how, it’s just a different way of accessing data that’s already there. Mm-hmm. Um, and, and, um, I think that’s a good example of just having access to a piece of technology, like a generative AI tool or.

[00:22:17] Chris Chesebro: Anything, Microsoft PowerPoint as an example, it’s only as good as how you use it, um, and, and how well you train yourself and how capable you or your team or your, your coworkers are in using that capability. Um, and I think the AI SEO conversation is a good example of that. Because what’s ranking in in chat GPT, if you ask it for the best smoothing shampoo solution is exactly what’s ranking on Amazon, which is exactly what’s ranking on Google and Bing.

[00:22:47] Chris Chesebro: Um. There’s just more rich snippets associated with it when you ask chat, pt. Um, uh, and it includes emoji emojis where the Google results or the Amazon results don’t include [00:23:00] emojis. Um, so I’m oversimplifying it a little bit, um, and I’m sure there’s probably people who are far more expert in it than me who will be screaming about this in the comments.

[00:23:09] Chris Chesebro: Um, but, uh, that’s from what, what I’ve seen so far that. That’s really the case. What shows in regular SEO shows in in ai, SEO, um, and to me that’s just a reflection more broadly of it’s the internet and it’s the access to the information on the internet. 

[00:23:25] Katie Gross: Yeah, that makes a lot of sense. Just a different format, but the underlying data and behaviors are the same.

[00:23:31] Chris Chesebro: Correct. 

[00:23:32] Katie Gross: My last question for you. So for insights professionals, of which there are many who will listen, um, if they want to have a greater impact on the leadership level and on the C-suite, um, outside of curiosity, what other advice would you give to them for today? 

[00:23:47] Chris Chesebro: Um, the one thing in addition to curiosity that I would say is put yourself.

[00:23:58] Chris Chesebro: As best as possible in the [00:24:00] shoes of a leader who’s responsible for many functions, not just one function. Um, I think people who have detailed expertise in a single area of focus, it can be easy for them to look at it from almost a blinder’s perspective. Say, this is what makes sense from a research perspective.

[00:24:24] Chris Chesebro: That’s great, but. The research perspective isn’t what drives the business decision, it’s how that research perspective impacts the overall business decision. That is what is going to be a good leader is going to make a decision based on that. And, and I think always remembering that, yeah, take, let’s take a, you know, maybe a, a product tagline as an example, just to use a really simple example, research might say, to use a product tagline that makes perfect sense.

[00:24:56] Chris Chesebro: Purely from a, an empirical research perspective, but [00:25:00] that tagline is the one that your competitor’s using. Yes. Now, of course, you’re not gonna use that, you’re not gonna make that recommendation. And so of course I, I use a little bit of a black and white example there. Um, but I think the, the ability, the ability to understand the role that.

[00:25:16] Chris Chesebro: An insight or that research plays in driving an overall business decision is critical and, and I think that’s what’s gonna separate people who are gonna be leaders versus people who are going to not be leaders in that type of field. 

[00:25:33] Katie Gross: Yeah, that makes a lot of sense. The real world application of how that insight can be utilized and connecting that to you.

[00:25:38] Katie Gross: Exactly. 

[00:25:40] Chris Chesebro: Exactly. 

[00:25:41] Katie Gross: Chris, thank you so much for such a thoughtful and engaging conversation. It’s been a really great window into how insights, my pleasure to drive decision making at the exec level. 

[00:25:50] MRII Announcer: Thank you so much. 

[00:25:51] Chris Chesebro: Thanks, Katie, I appreciate it. Thank you very much. 

[00:25:53] MRII Announcer: Thanks for joining the Insights and Innovators podcast for Market Research Institute International.

 

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