Empathy, Humility, Action: Driving Change

In this episode of the Consumer Insights Podcast, Thor is joined by Deepa Iyer, Sr. Director of Market Research and Data Science at Fossil Group.

You can access all episodes of the Consumer Insights Podcast on Apple, Spotify, or Spreaker. Below, you'll find a lightly edited transcript of this episode.

Thor:
Hello, everyone, and welcome to the Consumer Insights Podcast. Today, I'm excited to have a brilliant insights leader joining me for what I know will be a riveting conversation. I'm thrilled to introduce today's guest, Deepa Iyer, Head of Market Research and Data Science at Fossil Group, where her primary focus is to bring the voice of the customer into product development, strategy, and marketing. She also seeks to leverage emerging technologies to understand the deeper "why" behind customers' actions. With nearly 20 years of experience driving actionable solutions across multiple industries, Deepa is an award-winning insights leader, having previously won the Marketer of the Year Award in Market Research from the American Marketing Association and the Genius Award for Data and Analytics Growth from the Association of National Advertisers. Thank you so much for joining me, Deepa.

Deepa:
It's a pleasure to be here. Thank you for having me.

Meet Deepa

Thor:
Now, Deepa, we really want to get to know you. So maybe we could kick things off with you taking a couple of minutes to tell us about yourself, your role, and how you got to where you are today? How did it all start?

Deepa:
Thank you for such a warm introduction. I am the Senior Director of Market Research and Data Science at Fossil Group. Many of you know Fossil Group for our traditional watches, but we are really a global lifestyle brand that specializes in watches, jewelry, and leather goods.

We are designers, manufacturers, marketers, and distributors for various fashion lifestyle brands, that includes many of our own brands like Fossil, Zodiac, and Michelle. We also partner with several licensed brands like Michael Kors, Armani, and Diesel.

My background is actually in engineering. That's where it all started. But what has always fascinated me is exploring the complexity of human purchase behavior. As humans, we tend to believe that our shopping decisions are rational. But in reality, they are not. Our emotions have a significant influence on our choices. And these emotions are often reflected in our experiences, either with a brand or a product and our perceptions of them, rather than the tangible factors like price and product, and product features, etc. That being said, the tangible factors are still very crucial in shaping the customer experiences and perception. And that's what I wanted to measure. How does this emotional side of the consumer purchase behavior ties well, with the tangible factors of the actual purchase decisions? So it's always about striking the right balance between the rational thinking and the emotional aspect.

Defining insight

Thor:
I absolutely love that, Deepa. And with such an interesting background, I’m always fascinated to see how you define an insight. And tell us has that definition changed over the course of your career?

Deepa:

A simple definition of insight is summarizing what the data is, you can take it a step further. And you can summarize the data in a way that your recommendations would enable a company to take actions based on their current situation. And many of us call these as "actionable insights". And you will hear a lot of that in the industry that I'm here to deliver actionable insights. But for me, what is even more critical is developing the actionable insights that actually can be operationalized and implemented in the organization. That's the key. Managing Change can be a challenging task, especially when you don't have the processes in place to put your insights into action. So for me, when I'm thinking about developing insights, I always keep in the back of my mind in terms of what is possible now, and what can I plan for the future or what the long term implications could be? And whenever I talk to the teams, I always present the insights as a living and breathing solution, which makes it appealing for that. It also opens up the conversations because the teams are more eager to work with you and implement the recommendations.

Thor:
I absolutely love that. And when we were preparing for this episode, you told me that you think it’s important for insights teams to go beyond just serving as project managers. Can you tell us how you’ve come to that belief? And do you have any specific stories you can share on this?

Deepa:
Absolutely. We as insight teams, on the brand side specifically, wear multiple hats. I mean, we not only design and develop research, but we also have to manage the project from start to finish. And then we have to then summarize the findings and the recommendations. But the insight teams hold the key to unlock the voice of the consumer for the company. That means we need to go beyond what the stakeholders are asking for. That extra mile that you take is what makes a difference.  Let me give you an example. We were approached by the product designers to test different variations of a particular product. It was more of a gut check, you know, to understand which SKU is going to have the highest probability to be successful in the market. In our industry, product development actually starts almost two years before it's actually launched in the market. And only about 2 out of 10 products are successful. So having any insight that's going to increase the odds of success is incredibly valuable, as it helps the ROI and also helps the long term health of the brand itself. Now, back to the test. It was a very simple test from a research perspective, right? We asked the consumers to rank the SKUs based on your preferences, we then asked open ends to delve deeper into what they liked and what they didn't like, nothing fancy. We analyzed the data, shared the insights with the product team, and they loved it. But soon enough, we realized we were getting a lot of requests very, very similar. And you could call these as “the last mile test”. And that's when we paused and we said, “Wait, let's start having conversation with the team.” And we asked them, “How did they decide which SKU variations or SKU types they should test and why?” And the response we got is that, “We think consumers will like it; we are trying something new.” So that was their business issue. It was not about which SKU color variation or type that consumers would like, but rather, they wanted to find a curated collection that was reflective of the consumer preferences. So we went back to the drawing board to devise then a series of tasks that's going to help answer this question. So as a first step, we say, let's open up the vault and test all the past designs that we have created. And we know that have been successful. So you could think of this as conducting a meta analyses that can identify the color and feature combinations that the consumer responded to the most. And that was phenomenal, actually. So we were able to now communicate back to our product designers, the right combinations, or the right features that they should think about when they are curating a collection. Now, because of this process, the insight team today is an integral part of the product development process, we are no longer an afterthought, but rather strategic partners that influence the design process. This collaboration has resulted in several breakthrough products that have been successful in the market. And not only that, we were able to also reduce costs by not producing a SKU that we knew had a very high chance of a failure in the market. 

Thor:

I think that's such an inspiring story. And I think there's so many follow up questions. I want to ask you on this. But if we dig a bit deeper into this, when it comes to working with insights from a more strategic perspective, what are the steps to take, you know, what, what's step one? What's step two?

Deepa:

Yeah. So when you typically start a project, we always ask, what's the objective of the process? I would switch the narrative and ask, how do you plan to use the outcome of this project? Now, this allows you to open up the conversation and almost in fact, look under the hood and trying to see what are the complexities that are associated from the team perspective in terms of what they're trying to address? What is that business issue that we are trying to solve as a company? Second, the other thing to remember is that you may not be able to implement all the changes, because you may not have the processes in place, but that's okay. I would discuss that with the stateholder's and see what's possible. And think about that to teach it long term plan. And the other thing to also keep in mind is that change always is driven from the top, you need to get the buy in from the executives within the organization to make this possible. So find a sponsor, build a proof of concept on how the process can be changed, and then that it can help the organization overall, and most importantly, also showcase examples on how it can impact the bottom line.

Thor:

And is there anything you think that people can easily get wrong When taking on this endeavor? Is there anything you think people should watch out for?

Deepa:
Absolutely, I will never forget this. But it's like, nobody likes to be told that their baby is ugly, you can come in there and share your insights, however thorough they may be with the team that has been working on it for a while, and expect them to say oh my gosh your insights are awesome. Thank you for telling me that. This was one of the profound learning experience for me. No matter how thorough you are with your models, with your assessments and your insights, you need to share those insights, those great findings with utmost humility and empathy. And remember that you and your team are working towards a common goal that's going to help the company make smarter decisions.

Consulting lessons for brand leaders

Thor:
I think that's so inspiring. And something that I've heard come up a lot recently, when speaking to insights leaders, is the desire to act as internal consultants, as someone who started their career in the world of consulting. Are there any learnings you take with you when you join the brand side?

Deepa:
Certainly. When you work as a consultant, you have to operate at a very, very high speed, almost like running at 250 miles per hour. But that's what makes a job so thrilling. The fast pace makes you curious, and gives you the opportunity to learn new technology, and apply what you have learned from the previous experience in a new setting. It allows you to be agile and scrappy without losing insights of the overall goal. I have worked in several different industries from technology to CPG, to oil and gas. And every time I worked on a new case, I gained more knowledge and added those new ideas and methods to my toolkits. I've approached my current job with the same mindset. We work very closely with product with pricing, supply chain, demand planning, CRM, marketing brands, UX, e-commerce teams, store teams. And the way I see ourselves is that we are in-house consultants, and our mission is to increase the ROI by providing honest and scientifically sound recommendations that aid the company in making smarter decisions. In every initiative we work on..

our Northstar has always been to inject consumer preferences and behavior and the needs to unlock for the company so that you can offer the right product at the right price in the right channels at the right time.  And most importantly, advertise it in the most effective way to the customer. I transitioned to the client side, because I wanted to learn how companies operationalized solutions, that was the most important thing for me.

So when I started at Fossil Group, nearly nine years ago, I was a one person team. The market research function was pretty much outsourced. And I came in and slowly brought the Insight function in-house.  That was a challenging task. But it's my consulting experience that helped me to think creatively and find solutions with the resources I had at hand. I prioritized agility, and I was willing to fail quickly, iterate, and then improve upon what we have already accomplished. Rather than sticking to a rigid process. You know, I may not be running at 250 miles per hour, because the processes are not in place. But I started small and I focused on delivering these bite-sized insights and gradually built credibility within the organizations. And we've come a long way since then. I want to give you an example here. I always have wanted to bring the voice of the customer closer to the business so that we can hear what customers have got to say and most importantly having the opportunity to co-create with our customers and consumers. So I wanted to build a consumer panel. I didn't have any budget. So I started small. And I implemented it just in one country. And I had a sponsor within the company. And I had to prove its potential by piloting it in one country. And it took about six months. And today, we have expanded that consumer panel to six countries. And we now inject customer feedback in almost everything that we do that's gone beyond just product development, which was my original intention. We now use it for concept testing. We also have done mystery shopping experience, we have run diaries with the same panel.

Tips for internal consulting

Thor:
There's so much good stuff here. If we were to summarize, what three tips would you give to listeners who want to act more as consultants within their organizations?

Deepa:

The three main things that I would recommend is: be curious, don't forget your entrepreneurial spirit. This allows you to think outside of the box and come up with a creative solution. And second in this is the most important thing, the brand side experience is a marathon and not a sprint. Progress may at times feel extremely slow. But that's okay. Think of yourself as if you're steering a very large ship. And that cannot be done overnight, I would focus on bite-sized recommendations that can be implemented, because those small bite-sized solutions can go a long way.

And lastly, always approach insights with humility and empathy to drive change within the organizations. Have a dialogue with your stakeholders so that you can get them as excited as you are about the incredible work that you have done.

Thor:
In preparation for this episode, you also shared that you're curious about how AI can be an ROI engine? Can you tell us a bit more what you mean here?

Deepa:
Everyone is talking about GenAI these days, and everyone is racing towards identifying and implementing use cases that can be best served by the power of GenAI. When assessing these use cases, I would put it into perspective to see is this use case nice-to-have, or does it really have the potential to impact the ROI? Can the upfront costs associated with developing and absorbing GenAI solutions be justified by the impact that it can have on the bottom line? Companies are still figuring it out. It's very novel at the moment. And some of the most popular use cases that you hear today is about how GenAI can improve productivity for the teams. It can take mundane tasks and free up the team's time to focus on some of the hard stuff. And so when I think about GenAI, I think of it as looking for cases that's going to improve the productivity of my team. Does it improve the efficiency of my team? Can I use it as an engine to upskill the team members at a faster pace? 

Thor:
And if we double click on that, have you seen any such use cases where you think AI can be beneficial to insights work? And conversely, are there any applications of this technology that you're particularly skeptical about?

Deepa:
GenAI today, from an insights perspective has really opened up the prospect of how analyses can be done. On one side, it can help with mundane tasks, like it can write a survey for you. So you can have a junior analyst and the junior analyst can ask GenAI to write a survey, and the story's pretty decent, and you can build over it. It can be a canvas to start and fine tune your surveys.

But where we have been using it is to analyze a lot of open ended responses. We have a consumer panel that's in six countries. And in every survey that goes out or a every study that goes out, we ask a lot of open ended responses. And because we want to uncover what consumers have got to say.

IDC has predicted that by 2025, 80% of what consumers are going to say, will be buried under open ended responses. We as an industry have always used structured data or structured survey to analyze and assess what consumers are saying. But the industry is now moving towards more open ended responses. And we can use GenAI as a way to harness that information. And that's where I see the power of how easy it is that it can go in and read through 25,000 comments and kind of give you top three things that have emerged that in the past would take hours or days to even codify.

On the flip side, though, just how we are using GenAI because we are curious, and we want to learn more, and we want to make it useful for us, the consumers are also starting to use it to answer those open ended questions. And it is much harder now for the insights industry to identify those fake responses. We can no longer rely on speed checks, or straight liner checks, or, you know, identifying if I'm a bot or a human, all those old methodologies are not going to be enough to identify a fake response. We now have to figure out new ways to identify a GenAI created response and what is a true human response? And that's the part that scares me the most.

Thor:
Now in your current role, you lead both market research and data science teams. Do you take different approaches when leading these two areas? Or would you say that there are a lot of similarities?

Deepa:
I am incredibly lucky to have the opportunity to lead the data science and market research teams. It's like best of both worlds. You asked me about are there different approaches when leaving the two? Absolutely.

When I talk to the data science team, it's very technical, we go deeper into the methodologies we go deeper into the technology that's available. We are always searching for what is the best model or the best methodology to answer the business question.

And when I'm talking to the market research team, it's about more of a holistic approach. I'm not answering one question, but rather, I am answering several questions. And I am trying to curate more storytelling. So that's where the differences are.

But when I think about similarities, both teams are having one common goal. Both teams are trying to identify more about the consumers, learn about what the consumers are saying, and unlock those opportunities. So in that way, there's a lot of similarities between the two teams.

And let me give you an example. I was talking earlier about how GenAI has enabled us to harness more open ended responses, both market research team and the data science team collaborate on several projects to uncover those findings within Fossil Group. We also are looking into ways on how we can be creative with our quality controls so we can isolate those bad responses, but not take away from some of those really good responses that that we received. 

Thor:
Would you say that there are any general learnings or any areas from which you think market research and data science teams can learn from each other? More generally speaking?

Deepa:
Yes. There's a lot that they can learn from each other. I have seen that the data science teams sometimes can get very technical, and understandably so, they should be technical. But what the market research kind of brings in is that consumer lens, that empathy lens that allows the teams to soften their approach, and rather than communicating an insight, you're now telling a story about what your data is telling.

It also allows you to unlock and tell what the long term impacts would look like. So, within our teams, if we're doing a huge segmentation project, the market research team would develop the survey, they would field the survey, and be the point person to manage the study while the data science team would take over the segmentation exercise. And then they have a conversation about what type of segments or which segmentation solution is best suited for the business issue, or the business question that we are trying to solve. And they start to bounce off ideas. So any results that we produce, we produce in a very united front. It's not about what market research is saying. It's not about what data science is saying. It's really about what are some of those stories that we uncovered by looking into the data.

Thor:
I absolutely love that answer. And because you said, so I really have to ask you, if we look ahead, how do you see these two areas evolving? 

Deepa:

It's really not about what the individual teams can produce. Both teams have got immense strengths, both teams have got immense opportunities. So when I think about the market research and data science teams, there's a lot of convergence in the sense on how the data is currently analyzed, and how, or what type of insights are identified, looking at the data. And both the teams benefit from having the conversation. 

Thor:
Now I think you've shared some really insightful learnings with us today. If you had to summarize, what's the one big takeaway you want listeners to get from this episode?

Deepa:
The one big thing that I want listeners to take away is that when you're working on the client side, you have to see yourself as someone who is influencing change, or driving change, and that change management are driving change is incredibly difficult. You may be the smartest person in the room, you may know the data inside out, you may have a perfect model. But if you're not able to communicate that, or if you're not able to extend across a table and have a conversation with the other team members, you're not going to be able to drive change. So anytime you are sharing your insights, my one piece of advice is to approach it with humility, approach it with empathy, and have a dialogue. It's not about the other person, the other team is wrong and you're right. But it's really about how can your analyses, help the business make a better decision, and you are in it together.

An insightful lunch

Thor:
That's brilliant. Thank you so much. Deepa, it really saddens me because I would really have liked to go on for a longer period of time asking you questions, but we've come to the end of this podcast. And I have one final question for you. Which is who in the world of insights would you love to have lunch with?

Deepa Iyer:
It's a very personal question. And as I said, I came from engineering, I had no experience with market research. I did feel that I was like if I was just sitting behind the computer and be coding I really would be not enjoying my work. When I was at the university, Jerry Thomas, who is a local insight leader, having conversation with him, he was the one I would say why I'm here today. And he really got me excited. He recruited me into the market research program. He really pushed me to do what I'm doing right now today.

So I would love for to have continued to have lunch. He is my mentor. So that's one answer.

The other answer I had is one piece of analysis that I love doing, or one of my favorite piece of analysis that I love doing is conjoint analysis, and many people would have heard that too, where it's you are looking into people's willingness to pay. Because if you were to ask someone, how much are you going to pay for a product? They're gonna say, absolutely, I want it for free, but it was professor Paul E. Green from the Wharton School of Business who came up with the idea, or came up with the mathematical models for running conjoint analyses. And I would love to have lunch with him.

Thor:
This has been such a fantastic conversation Deepa. Your perspective on Insights is truly unique, and I think we can all learn from it. But before we end today's episode, I'd like to return to some of the moments of our conversation that really stuck with me. To start off, you told us that a basic definition of an insight would be summarizing what the data is saying. But taking it a step further. It is the notion of actionable insights. The definition you highlighted, however, as the more complete was developing the actionable insight that can be operationalized and implementing it into the organization.

When talking about insights as a part of the strategic long term plan you told us to "Don't limit yourself to asking, what is the objective of this project" Make sure to complement it with how do you plan to use the outcome of this project. Make sure to secure executive sponsorship for your project and never lose sight on how your work will impact the bottom line. Lastly, when we spoke about Generative AI, you reminded us that from an insights perspective, it opens up a lot of possibilities. It can solve mundane tasks such as writing, and fine tuning surveys. But more interestingly, you've told us that you've used it successfully for analyzing open ended responses. Imagine getting on the top three learnings from 25,000 responses instantly. On the flip side, however, the consumer starts using Generative AI to answer these open ended questions. I know that I've learned a lot from talking to you today. And I'm sure our audience has as well. Thank you so much for joining me.

Deepa:
Thank you for having me. It was a pleasure.