Retail Relates
Welcome to Retail Relates — where commerce gets personal.
Each episode brings you inside the world of global commerce — across retail, consumer services, hospitality, and brand marketing — through powerful human stories and the ever-evolving forces shaping what we buy, why we buy, and how we connect.
From entrepreneurs and icons to industry veterans and rising changemakers, we spotlight those redefining how people lead, create, and connect in a fast-moving world.
Hosted by our roundtable of industry experts, we offer a 360° view of the marketplace through honest conversations, lived experience, and practical insights that resonate.
Let’s get started — this is where the story of modern commerce comes to life.
Retail Relates
Data, Decisions & Discovery: Katherine Black on Turning Insight into Impact
What happens when data becomes more than a tool and starts to shape how we lead, learn, and listen?
In this episode of Retail Relates, Rich Honiball and Guy Courtin sit down with Katherine Black, Partner at Kearney and one of RETHINK Retail’s Top Retail Experts for 2025. Katherine’s career has taken her from Capital One to dunnhumby, KPMG, and now Kearney - helping global retailers turn customer data into meaningful loyalty and long-term growth.
She explains why curiosity beats coding, how the best loyalty programs are built on trust - not transactions - and why AI is most powerful when guided by human judgment. Katherine also reflects on lessons from her work with Tesco, Goodwill, and other global organizations, and what students and emerging leaders can learn from the next wave of “agent commerce.”
Insightful, practical, and refreshingly human - this episode is a masterclass in transforming data into impact.
Katherine Black Bio
Katherine P. Black is a data-driven strategist and Partner at Kearney, where she helps global retail and consumer companies transform how they grow, compete, and create value through data. With more than twenty years of experience leading commercial and technical teams, she specializes in converting data assets into strategic advantage—building loyalty ecosystems, designing data-driven pricing and personalization, and launching large-scale monetization programs that unlock new revenue streams. Her work consistently delivers measurable results, driving mature businesses to 3–5-point sales growth and launching new lines that achieve double-digit gains in year one.
Prior to Kearney, Katherine held leadership roles at KPMG and dunnhumby, where she led customer analytics partnerships with retailers including Tesco, Kroger, and Macy’s. She is a member of Chief, serves on the Board of Directors for Goodwill NY/NJ, and has been recognized among Retail Leader’s “Top Women to Watch in Retail” and DM News’ “40 Under 40.” Most recently, she was named one of RETHINK Retail’s Top Retail Experts for 2025. A lifelong believer that “data gives a voice to every customer,” Katherine is passionate about helping companies listen better, act smarter, and grow with purpose.
Have you ever thought about what happens when data becomes more than a tool and it starts to tell a story? For Katherine Black, the real advantage isn't in how much data you have, it's in how you listen. Hi, I'm Rich Honiball, and I'm joined today by one of our retail relates co-hosts, Guy Courtin, as we sit down with Katherine to explore how curiosity, empathy, and purpose can transform analytics into action. She has spent her career helping retailers and consumer brands unlock the potential of data, from building loyalty ecosystems to driving growth through smarter pricing, personalization, and experiential design. Our guest today, Katherine Black, is a data-driven strategist and partner at Kearney, where she helps global retail and consumer companies transform how they grow, compete, and create value through data. With more than 20 years of experience leading commercial and technical teams, Katherine specializes in converting data assets into strategic advantages, building loyalty ecosystems, designing data-driven pricing and personalization, and launching large-scale monetization programs that unlock new revenue streams. Prior to Kearney, Katherine held leadership roles at KPMG and Dunhumbey, where she led consumer analytics and partnerships with retailers like Tesco, Kroger, and Macy's. She is a member of Chief. She serves on the board of directors for Goodwill New York, New Jersey, and has been recognized by RETHINK Retail as the top retail expert for 2025. In this episode, we talk about how loyalty is built on trust, not transactions, why curiosity beats coding, and how AI can enhance rather than replace human creativity. Katherine also shares what the next generation of retail leaders can learn from Goodwill's purpose-driven circular model, and how agent commerce will soon reshape how consumers shop and connect. This is an episode we know that you'll enjoy. Let's welcome Katherine Black to Welcome to another episode of Retail Relace.
Rich:Today I am joined by my co-host Guy Courtin. How are you doing today, Guy? I'm doing great, Rich. How about yourself? Doing great. And then as mentioned in the preamble, excited to be joined by Katherine Black, who is a partner at Kearney. Katherine, welcome to the program.
Katherine:Thank you. Great to be here. Thanks for having me.
Rich:Looking forward to jumping right in. So we do jump right in. And since we have had the chance to introduce you to our guests, rather than have you go through the same chronology of events, we take a little bit of a different twist. Think about the top three most pivotal moments from a personal or from a business perspective that have shaped your path and brought you to where you are today with us.
Katherine:Well, I guess I'll stick mostly to professional, although interesting, if if you bring in personal, that's a whole different, that's a whole different ballgame. Maybe we'll do a mix. I mean, I would say one was early in my career, long before I was in retail, I was in banking for a while. And one of the places I worked was Capital One. And I really like Capital One. It was very data-driven. It was a lot of the same stuff that that I do today in terms of understanding how customers behave and whatnot, but it wasn't a bank. And I got the feedback that I wasn't very clear and concise in my communications. Hopefully that's not the case today. Hopefully, I've improved. But one of the things someone recommended to me is that I go and work in this internal consulting group that we had. And the internal consulting group was primarily made up of outside consultants who were coming into the company. So I went there and it was fantastic because I got to learn from all these consultants from all these different firms. They all gave me their training decks. So I learned every single firm's training method and got tons of advice. And it was a huge leap forward. So that was one pivotal moment because it opened me up to different ways of thinking. I got new skill sets and I just learned a ton. I'd say the other big pivot point was uh maybe when I went to Dunhambi. Again, I'd been a banker, and then that was really my shift into pure retail. And people would always say, Hey, how did you go from banking to retail? That's really weird. I was like, well, the thing is the customers that have checking accounts also buy groceries and clothing and all that good stuff. So that's how that makes sense is I was always studying customer behavior, but it was a pivot point in terms of industry. And retail is so data rich. And that was such a big piece of my career that that was a great pivot. And then I guess that there would be professional, I mean, personally, um, you know, when you have kids, it's a life changer, as you know. And so I that has that has to factor in there. It forced me to be more efficient, trust my teams more, uh, let go of control a lot more than maybe I would naturally do. And so, yeah, that's a that's a massive pivot point.
Rich:Kids definitely count as a pivot point.
Katherine:Yeah, absolutely. They might be the biggest one. You know, I tell I tell young professionals who struggle with time management that the best solution is to have kids. I was like, okay, but if you but if you don't want to have kids, there's some other tips and tricks, but that'll do it.
Guy:Yeah, you get a dog too, that will be a good time management.
Katherine:That's a great, great idea.
Guy:Kathy, it's interesting you say that too, because you talk a lot about the the one of the impacts with data and all this, but then you talk about sort of having kids and letting go of some control. And isn't that sort of counterintuitive? Like you you talk about a pivot point about learning and appreciate data in retail. Then you say, but with when you have the pivot with children, you have to learn to let go. Like, how do you consolidate that sort of as a as a learning you've had with regards to when do you need to rely on the data and be married to it and when do you need to sort of see control and sort of let things flow as they should?
Katherine:Yeah, I think there's an interesting, I'll have two answers to that. The first one is I don't see them as totally um discontinuous because in some ways when you uh allow your decision making to be data driven, you do give up sort of your personal preference. You have to let go of kind of your personal preference and and hopefully your biases and whatnot as much as possible. Um, so there's there is some continuity in that. But you're right, you cannot data drive your kids. I mean, God bless if you can figure out the algorithm to manage, you know, a child of any age, you know, five years old, teenager, infant, what have you. Uh, it's not quite it. So you learn to observe patterns, I think, in both cases. And and that can absolutely be seen in children. But uh yeah, the sooner you can realize that sometimes the behavior you're observing has nothing to do with the direct thing that's happening, the the better off you are.
Rich:Yeah, absolutely. So is this what you imagined you were gonna do?
Katherine:I mean, who imagines what they were? I I think that's such a funny question when people ask at any stage of your career, you know, where do you see yourself in five years or 10 years? I mean, short answer, not really. I did always consider consulting, which is what I'm doing at the moment. But if you had said to me when I was, you know, 21 years old and I never left the state of North Carolina and you know, I grew up in a really small town that I would live in London or I would work in these types of businesses or do these types of things. They didn't even really exist in that way back then. So no, I definitely would not have imagined, you know, all those rich experiences. And so, you know, maybe that's a point of advice is to not get overly planned on things. So there may be some vague notions that are still the same, but a lot of the specifics, no, I wouldn't have imagined. I don't know if I would have dreamed that big, to tell you the truth.
Rich:Did you have a dream?
Katherine:No, not really. No, not really. I was sort of, I you know, I was sort of the type of young person that was like, okay, I just want to get out. I don't want to be, I want to sort of be successful. I want to, you know, self-sustain. You know, I don't want to go home and live with my parents and you know that. I just want to have a job and you know be moderately uh successful and have some fun and move on with life. Yeah, I don't know. I'm sure, I'm sure if you asked my 21-year-old self, I would have had a better answer than that.
Rich:But no, that's actually that's a good answer. And it's actually one that uh I I try to encourage people with. And I got caught because I think it was a couple of years ago we had an intern group that came in, and I was giving the advice of look for the first three to five years of your career, don't get so wrapped up into title or marching down a specific path. Explore, discover. And then somebody turned to me and said, Then why do you ask the question, where do you imagine yourself in five years? I have not asked that question again since getting called on it.
Katherine:That's funny.
Guy:Well, Catherine's interesting because I I like your story about, you know, you 21-year-old, you would never imagine living in London, things like that. But can you talk a little bit on what Rich has said too, sort of being open to these types of experiences? Can you talk a little about that? Because when I looked at your CV, it was really interesting. Like you, I'd love to talk to you more about this, like working for Tesco and things like that, which I think are fascinating, especially in your path to consulting and retail, right? Those are great experiences. But how did you get there? Like, how did you make the leap? I mean, obviously, moving from not having left North Carolina until you're 21, then all of a sudden you move to London. Like, that's not a small jump.
Katherine:No, I mean, obviously there was a progression, a progression along the way. And there were some comforts. I think you hear about people saying, like, don't make two hard pivots, like, don't change your industry and your location at once or what have you. And I didn't do that. I was with the same company I'd been working with, doing the same sorts of things I'd been doing. And I had some colleagues in common. And so there were some comfort zones within that for sure. But it was just a great opportunity. I I got really good at being able to do tooth in one work with data. And I was super passionate about, you know, formalizing customer experiences and and loyalty for retailers. But I also was really good at going in and working with clients who maybe needed some new relationship help, needed new, new um ways of the team interacting with them and that sort of thing. And so the blend of those two skills is kind of how I ended up in in London, being able to forge some good relationships as well as make an impact on the business, hopefully. And uh, and it was a great opportunity. It was a lot of fun.
Guy:What would you say, like if if you're talking, if you're talking to the 21-year-old Catherine, like what would you tell her to make that leap? What is the on the other side of that bridge, like what are you gonna gain out of it? What are the what are the big positives? And also maybe more what's on the negatives uh in making that leap.
Katherine:Yeah, I would say for that one in particular, some of the big positives were just getting to experience a different culture, getting to actually do something that I was familiar with, but in a new place to see how it worked differently. There's real value in that. Living there, honestly, was fantastic. It was a fantastic experience for my kids. Uh, I loved seeing how they uh saw countries as associated with people versus foreign lands. And that really, I think, can only come from being in a really internationally rich experience, which they were. We traveled a lot, got to see a lot of the world and just hear and see day to day how things operated in ways that on the surface look fairly similar, but but down deep were were pretty different, was an incredible experience. And I think in terms of being open to that, yeah, there's uh I I love Ina Garden. I think she's a great, I don't know if you know her, she's a cookback, and she has this book, Be Ready When the Luck Happens. I think there's some real wisdom in that. Sometimes you can't engineer your way into an opportunity. Sometimes you can, but sometimes you can't. And I'm not sure I've engineered my way into a lot of opportunities, but I think that idea of being ready and being willing to take new opportunities when they come up is super important.
Rich:So I'm gonna dive into your background a little bit with um, and I'm trying to decide whether I want to dive into the data part of it or the loyalty part of it. Obviously they both connect, but yeah, what role has data played and and how is it kind of reshaped the retail environment over the last 10 or 20 years from your experience?
Katherine:Yeah, you know, it's interesting. When I first started in in my career and really working with data, I really felt empowering because data was like the dr the great democratizer. Suddenly, like the loudest voice in the room used to make all the decisions, and suddenly there was a way to sort of democratize that. I would say over the last decade or so, data has gone from being a real differentiator to kind of table stakes. Now, if you think about it, I can't think of many businesses who aren't using uh at least some of their data. I'm also always surprised sometimes at things that I did maybe 20 years ago that are still new to some companies and whatnot. So everything old is new again, I suppose, from time to time, but it's become much more commonplace and much more table stakes in how businesses are being run today. And I think that's that's a win for businesses and the customer.
Rich:So I'll jump in from a loyalty perspective without divulging anybody that you've worked with or putting anybody on the spot. You've got a wide range of experience, both from a global perspective, from the uh from the the client side and the retailer side. What has separated those that truly get loyalty and invest in it versus those that are just checking the box because they know they have to have it and they feel like it's table stakes?
Katherine:I would say the biggest differentiator and what would drive return on using your customer data, loyalty, et cetera, is how much you're talking and caring about building loyalty with a customer versus driving sales. And what I mean by that is in the first case, I've seen, I'll give you a great example. Rich, I've probably shared this with you before, but I once worked with two retailers. They used the exact same systems, the exact same analysis, the exact same types of data. It was their own data, but it's the same types of data. They got dramatically different results. And it really came down to one of them kind of had religion around using that data and really putting the customer first and their thinking. And they were kind of willing to make trade-offs that analytically, if you were only worried about the short-term bottom line, you might not make. But like I say, they kind of had religion around it. They really believed that if you did the right thing for the customer and you saw that in the data, it was going to pay out in the long term. And it and it really did. They had phenomenal, very sustained results. In another case, I would say the company's actually far more sophisticated in how they operated. But they were sort of super concerned about the short-term bottom line. And that then becomes a sales driving technique, not really a loyalty technique. And you get short-term bumps that are hard to sustain in the long term. And then the longer term you operate, the longer term you operate that play, the more difficult it is to get results. And I think that's a real difference maker that's hard to stomach, particularly for analytical people, because you want there to be a very, you know, sort of data-driven, but it is the art and the science. It's data driven, but you you do sort of have to believe it and have some conviction around doing the right thing for the customer in the end and thinking in a more long-term fashion and not just the short-term metric, which can really throw people off.
Guy:I really like that answer, Catherine, but can you expound without obviously really names? But from the retail perspective, are there different kind of categories of retailers that are more open to what you just said, which is have that long-term view of building loyalty versus just transactional? So, for example, you know, if I'm a fast fashion retailer, I'm just looking for the quick sale, and maybe I'm not as concerned as your long-term relationship, but if I'm a luxury brand, you know what? I want to nurture that customer loyalty for the lifetime of the customer, for lack of a better term. Do you see that, or does it does it not matter what the subvertical retail is that can apply these techniques?
Katherine:I would say where folks tend to be more short-term oriented is when they're a public company with a difficult new competitive environment and they're trying to make their short-term earnings. They're in a low margin business. You know, it's easier in for in your example of the luxury uh company. I think when you are of a private company that is higher margin, it's easier to take a long-term view candidly. And you have a lot of executives who are under very real pressure to deliver results on a quarterly basis. And so being able to navigate that and do the right thing for the customer in the long term while also managing your short-term commitments is really doable, but it is very difficult. And that's where I tend to see people fall down. You know, when the environment is particularly challenging, people just sort of fall back on, well, geez, there's been a strategic shift or a market shift or a big difference here, but I got to make my number. That's when things start falling apart.
Rich:You've had the art, the science, you've been involved with clients that have had the art and science. How do you make sure when you're leading a project that you get both sides at the table?
Katherine:Yeah, interesting. Well, look, today is super interesting because we can train bots to act like different people, and you can have literally thousands of personas at the at a given table. So that's sort of a fun new place where we're doing some experimentation. But I think even with even without the fancy technology, let's rewind two years ago. How did we do that? I think you always have to be grounded in the data. But I will say common curiosity and common sense will trump technical acumen any day of the week. And, you know, Rich, we've worked together in the past. You teams know how to technically do what they do, but you do need that experience set to go in and sort of say, like, that doesn't, that doesn't make sense with all the context that I know. Or, you know, when it let me share it with this other part of the business and understand how they're thinking about this because it really can make a difference. And you can spot some obvious issues that are nuances to the data or connections that need to be made between the data that you'd otherwise miss. So there's always a little bit of science and art.
Guy:So I I'm gonna jump on this because I love what you just said. So talk a little bit. I'm gonna bring up the two-letter word that we all have to talk about because you talk about data, and now you talk about the experience, and then people are saying, Well, now we have AI engines and they'll do all that. And can you shed some light on this? I think I'm with you 100%, where there has to be the human element that understands the nuances, understands the context, understands from from experience. Is AI gonna take over that? Or is the human where is the human AI data play in this?
Katherine:Yeah, I mean, it's interesting because I'm sure you guys have experienced this. I feel like uh AI is an enormous accelerator. I mean, it's really incredible. Uh, but it's certainly not perfect. Uh, and I do think the ability to shape the right prompts, the right thinking, the right uh analysis still requires some human intervention. And certainly evaluating the outputs uh requires some gut checks and some some common sense real-world applications to things. So yeah, it's uh I do think it's a massive game changer. Absolutely. But is it a hundred percent AI? No, I don't I don't see that world in the near future. Maybe we'll get there uh at some point, but I don't see that as immediate for a variety of reasons, but but predominantly because we still need you still need to kind of guide and shape the thinking and bring in other perspectives that aren't necessarily gonna be thought of and and gut check it.
Guy:No, I I I was leading the witness of things. I think that's I'm spot on with you on that. I I think it's when I look at your, you know, you just touched a little bit about your experience in London and working for Tesco as I saw in all this, and it's like you can't replicate that, right? That's experience you have, and when you see data that I'm sure in your consultant with a customer now, you can call upon that. And yeah, use AI as a tool and data. But I think I guess the next for me, it's it's interesting you also mentioned talking about talking to different parties. Let's go back again just quickly, like the 21-year-old Catherine, like what would you suggest to her? How do you develop that tribal knowledge, that experience? Right. And and for you know, I have a 17-year-old son, like, what do I tell him? Like, as he goes in the world where he's using AI, and that's AI to him is you know, like what writing a turn paper was to me in college, right? Like using a word processor of dating myself. But what would you tell them in terms of how do you build some of that those calluses, that experience that then you can apply the tools, but your brain, your experience is is is what's valuable that can't be replicated.
Katherine:Yeah, I think I think particularly for younger folks who may not have as much many years of experience, I do think there's a certain amount of curiosity. I I think curiosity is one of the most critical skill sets, particularly when working with data, but just in general. And so I think that ability to be curious and not just take a pat answer and continue to shape thinking and wonder about where things can go and sort of experiment with it, and then to borrow experience. So by that I mean build build the network of people who do have more credible experience and make sure that as you're thinking through, you know, using AI, you're being curious about it, you're really drilling down and asking them like, well, what's the downside of that and what's the other perspective on it? But then also using someone else's gut to gut check things, I think is important. Absolutely. The experience will come. I don't think there's any way to shortcut experience. You almost have to borrow it in the in the in the short term.
Guy:That but I love the the notion of curiosity, right? Because I think that's that's the part I think at least I see when I when I get to talk to students like college students, grad students, it's always like be curious. Like there's nothing that something that might seem unrelevant to your work potentially could be super relevant because you're gonna learn something from it. Take a class in you know, ancient philosophy, even if you want to be an account. Maybe you'll there's something you'll learn from it. And if you enjoy it, then even better. Yeah. So I think that's I love that point about curiosity.
Katherine:Yeah, and I think making those connections to your point, I think the most interesting insights come from making connections that other people aren't seeing. And so, yeah, the more curious, the more diverse your inquiries are, whether that's a class or just reading an article or studying something, I think that'll make everyone everyone's perspective richer.
Guy:So following that to think back to what Rich was asking earlier about your work and the space you're seeing with data, like how do you talk to your customers who potentially, well, the data tells me to do this and that's what I'm gonna do? And the AI engine told me this because I put it through Grok and it told me blah, blah, blah. How do you force them to say, well, wait a minute, have you thought about this? Have you thought from this perspective? Have you looked at a different data set maybe? Or have you maybe looked at the data and said, you know what? I don't trust, I'm gonna look over here. Like, how do you train? And I know it's an art of science, but from your perspective, how do you get the people to see the vision or the light to get there?
Katherine:Yeah, I think um, I mean, I haven't had a lot of those interactions with clients. They're still pretty sober, honestly. About I say I will say with teams, I've sometimes I've more frequently over the years have gotten you know data or information back, and I'm like, that doesn't, that doesn't check. And I can always then sort of say, well, here's what here's why it doesn't check for me. I need you to go back and research that. And it is always some perspective that they were missing. So yeah, I think the best thing to do is just be really thorough in testing ideas with different people. And obviously, testing in general, I think is incredibly underutilized and underrated. I would hope that's something that AI will bring about is much more robust testing, uh, either through synthetic means like digital twins or it actually in market, but in more limited uh basis, because very few retailers do real testing. Um, they do a lot of pilots, but in in my experience, not true testing.
Rich:And in doing the testing, you can fall prey to the dystopian novels that say we're all going to just give into the machine and and go about our business. But it is also, I think, about accepting imperfection. I I I sometimes wonder, would you have Formula 409 if AI was creating it? And you weren't going through the 408 mistakes if if you buy that. And that oftentimes it's the mistake, testing it, learning from it, that never say never will artificial intelligence get there, but it is curiosity, but being able to be okay with making mistakes and imperfection.
Katherine:Yeah, that's a real skill. Uh that that being being not afraid to fail. And honestly, I'm not very good at that, but what I'm okay at is breaking it down to be a small failure. I can be okay with that. That's why I like testing so much. You never really have a massive fail if you've constructed a good test. You're only going to have a small fail, and then then you can kind of move on. That's easier to accept.
Rich:So, from a retail perspective, I want to lean on two experiences that you've had and how that would shape your advice for US retail. Again, without putting anybody under the microscope. And you've had this rich experience from a global perspective and seeing the way retail operates differently. And you also are part of the Board of Goodwill, which is retail, but a completely different perspective. What are lessons that you've taken from a global perspective of retail and the goodwill aspect of retail that US retailers should be looking at?
Katherine:That's a good question. Those are very different universes. I'll start with international and the global players. I think global retailers are second to none on private label on a very specific thing, and US is very underpenetrated in that. And I've never quite under there's some very obvious things that they're doing really well in Europe that I'm surprised that more US retailers haven't experimented with over the years. They're not, they're not brand new ideas. So that's one. I would also say the European retailers are very efficient and and frankly, I'd say willing to give the consumer what they want. If you think about something like e-com, and I'm I'm thinking specifically in grocery because that's where I spend a lot of time. Europe had a well-developed, sort of 20-year head start on grocery e-com ahead of US retailers. US retailers sort of said, no, thanks. That's looks super unprofitable to us. And they said that until Amazon acquired Whole Foods. And then they were sort of like, oh, geez, I guess we better do it now because losing market share is more detrimental to us than the e-com, you know, lack of profitability. We'll do that. And all good news. They've also figured out retail media will do that too. But, you know, Europe sort of leaned in on it and just said, well, this is a better experience for the customer. Of course, this is where the value proposition is going. We'll innovate ahead of that. And it forced them to have much more efficient supply chains, much more efficient operations. And so I think there's some lessons to be learned there for US retailers. I think goodwill is interesting because it's super dependent on two things. One is donations in. So they literally need the community to donate items in. There's no sort of picking shoe, there's no merchant prints. It's a donation based business. And so much of that business revolves around how much donation volume is coming in. And so making sure people really understand and thrive on the purpose of the organization and what that organization is going from, which is in a lot of cases widely misunderstood, is so important for building loyalty, not just for sales, but also for donations. So they're incredibly dependent on the donor base. And it's an incredibly price-sensitive business. I don't think I've, it's the most price-sensitive business I've ever seen. I mean, down to the penny. I think if you can measure it in fractions of a penny, you would. So it's incredibly price sensitive. And so I think there's a lot to learn about cultivating real brand loyalty around purpose and community that a lot of retailers, many retailers do some aspect of, but their business actually lives and breathes on it. So I think there's some interesting dimensions to that. And figuring out how you create circularity in that business is uh isn't interesting and could become more relevant for more retailers going forward.
Guy:You talked about European retailers, Kathy. I want to, and you just talk about circularity. Can you talk a little bit about, you know, because I've seen this right where European retailers seem so far ahead of American retailers when it comes to sustainability, you know, being more green, more environmentally friendly, and circularity. And then you talk about goodwill. Can you talk a little bit about that, like what your experience is, you know, comparing the two sides of the pond?
Katherine:Yeah, I mean, I think it's exactly what you've seen. And honestly, I think it's really driven by legislation. You know, Europe legislates differently on that topic. They legislate differently on privacy. And uh that may happen without legislation, but I think at the moment uh it's largely the legislation driving it and big differences in in how companies are operating there. I have seen some instances more recently where US-based companies who are not driven by legislation are sort of being more forward-thinking on that. And I think that will that will really only come from the consumer. There's certainly segments of the consumer that are increasingly, uh, even in the US, increasingly more interested in that. Certainly in Europe, that's a predominant population. Um, but I think we'll see a rise that's consumer and market driven, uh, maybe even efficiency driven, not necessarily legislative driven in in the US. And that's been the primary driver to date.
Guy:Do you think that some of this Consumer drive driven on the US side? I mean, I I always cite the example of like made wealth, right? With their genes and they recycle and create linings inside houses, right, for for uh insulation. Do you think that you would go back to customer loyalty? Like, do you think that's a a sort of a hidden way of driving more customer loyalty? That hey, if consumers are more sensitive to sustainability, to be more aware of as a retailer, to then drive more customer loyalty. And back to your earlier point, right? It's not just transactional, it's about the long-term brand loyalty. Do you think we're seeing more of that in the US? Like those it those things intertwine?
Katherine:I definitely think there's more and more um experimentation going on. I mean, the brilliant part about that is it drives a trip. And so it's it is actually in some ways even a short-term play because returning the item to a store. And um, if you look at, for instance, Lulu Lemon's resale business, uh, you can't do that through the mail. You have to go into a store. So it's driving a physical trip as well, which is an interesting, um, you know, as you know, a key sales driver and sometimes difficult to do in certain environments. And so it's a great, great short-term strategy as well.
Rich:So I don't know whether I want to ask you your insights on how the Gen Z consumer may impact retail from a long-term perspective, or for or if I want to ask you how economic uncertainty may challenge the retail environment. I'll I'll let you pick which one.
Katherine:Okay. I'll maybe be talking about economic and uncertainty and try and touch the other in the process, but because we're spending a lot of time on that right now. And I think the consumer today is interesting. I was talking to a colleague of mine earlier today, um, KD Thomas, who runs our consumer institute, and we were talking about how consumers will say they're batting down. They absolutely do. They're comparing more prices. They tell us that they're holding off on purchasing, they're changing stores, they're changing brands that they buy, they're waiting for coupons and sales. But consumers also get fatigued and reach, you can never forget retail therapy. I think, particularly when it comes to, you know, apparel and certain items, uh, maybe less so in groceries and whatnot. But I do think consumers are still looking for a little bit of a release valve on the chaos, and they do that through shopping. So the patterns that we're seeing in the environment are kind of all over the board. I did an interview last week, and and the guy asked, you know, he's like, I can't make sense of this. The, you know, the economic numbers say this, but then consumers say that. And I'm like, yeah, it's really confusing. And I think you always have to talk about to a particular consumer on a particular day about a particular item to get clarity because they're thinking about it in different ways uh on at different points in time and in different categories. I think medium to long term, there's gonna be a lot of economic impact on the consumer. And I think if you couple that with how shopping will change with agenda commerce, how the job market is gonna change for younger consumers and the fact that they grew up in a sort of 30-second sound bite mentality, I think that could create a really interesting shopping experience of the future that is very price-driven, is very optimized. And that optimization may change, you know, day to day, week to week, category to category. But I think the consumer is gonna be looking to optimize. And so companies are gonna need to be able to cater and be the best in certain ways for certain consumers at the time when they need it. I think that's gonna be a really big shift. And they'll I don't know the exact timing of how that's gonna happen. But if I had to guess, I would say it's over the next three to five years.
Guy:So, do you think, Ketherin, that we're gonna have, you know, the holy grail of you know, variable pricing? So, like, you know, we always hear example Coca-Cola machine. You know, if it's super hot, I'm gonna raise the price of a Coke bottle from three bucks to five bucks. Then it gets cold, I'm gonna drop my price. And we're we're seeing things right where Delta's come out with this. They're gonna use AI to determine the price of a seat based on what you can pay, which kind of makes me feel weird. But do you think we're gonna get to that? Is that where you think we're getting to?
Katherine:I don't think that's gonna work. I think I think where we're gonna get to, though, is optimized pricing with ceilings on it. I actually think it's you see a lot of press about how, you know, oh, there's this fear that grocers are gonna use digital shelf tags to raise prices. That's not really how that works. They're mostly working to lower prices to move inventory to prevent spoilage and waste. That would be the first lever that you would pull. You know, they're trying to move through as many goods as possible. And in price-sensitive businesses, like let's just take grocery as an example, that traffic and the repeat traffic and the price perception is so much more important than the single margin on a single product at a given time. So I think people are misreading that signal, to be honest with you. I think mostly it will be price declines and price offers for more price-sensitive customers at particular times or to move inventory or to manage, you know, supply, that type of thing. Would there be surge pricing? I if it happened, I would hope there would be a ceiling on it. Certainly you can imagine managing demand where you say, hey, uh, if there was like a run on toilet paper, let's use that, that, uh, that odd example. You know, maybe the first product is a certain price point and it goes up to manage supply for a given consumer, but uh, or smart techniques, but I I can't imagine that being an unfettered, primarily price raising technique for most retailers unless it's in a luxury category or a very obsolete, you know, um scarce, scarce good.
Guy:That's interesting. I I because I give you an example. Like I was I took my son to San Francisco, we went to a baseball game, and you go out, and there's all these hot dog vendors, there's no price. So they're just charging you, you know, oh, you're gonna pay five bucks, ten bucks, twelve bucks, six bucks. It's all you know, I know the game, but I was just curious to see like I think it's a great point. It's like, yeah, it's a moving inventory, not necessarily catching, capturing another two percent of margin on an item. Yeah, I think that's that's a good point.
Katherine:Because if you think about it, a lot of shopping will move to a gentic. Okay, well, if I have my own agent, I might train it to say, hey, I really want to buy product A, but I never want to spend more than you know $5 for product A. And by the way, if you can get product A at another retailer for cheap, you know, I like retailer, you know, B, but if you can get it somewhere for cheaper and I get it at the same time, you know, it's if it's this much cheaper, I think that's the kind of dialogue we're headed towards. And so retailers are only going to be incentive to be competitive. This was probably 10 or 15 years ago. There was a CIO who said he really wanted to build an eBay like marketplace basically to get rid of inventory. So they would sell seasonal inventory and whatnot. So he was like, I wish at the end of the season we could just create like a bidding system to let consumers bidded. Well, I think that's the world we're moving to, is more like bidding to see what they can get for things, you know, more like define rule engines and to play consumer-driven rule engines, to play in that world, retailers have to be really sharp. It's not gonna generally be a price gouging mechanism.
Rich:Well, to take that, so if you're left with product at the end of the at the end of the season, rather than having pre-programmed set dates that you're gonna mark down by location, you're looking at the sales velocity, and there's a trigger that says when the velocity falls below a certain amount, lower the price. So you're managing your downside rather than trying to escalate your upside.
Katherine:That's right.
Rich:I think that's absolutely right. I can't say that I've heard a lot of conversation from that perspective. So it'll be, I think that's in it's a very interesting perspective. I want to go a little bit more general and then start to pivot into you've given some great advice, but I want to pivot a little bit more into advice for students. But with all of the experience that you've had, are there a couple of core beliefs or approaches that have served you well throughout your career that you either had from the beginning or that you've developed over time?
Katherine:I'm not sure I had any from the beginning. No, just kidding. I think over time. You know what? A really pivotal one for me. I read a book that someone recommended. I'm a big reader, and uh and a nerd and whatnot. And uh there were two, I think it's by the same author, uh, Leadership and the Art of Self-Deception. And the other one was called um something about war. Oh, I can't remember now. Anyway, the essence of this book really was about how conflict happens. And if you think about in the workplace, there are lots of you know, conflicts all the time. They're competing points of view, they're competing priorities. Organizations, large organizations are just set up that way. Sometimes they're competition between internal teams and external consulting teams. And it really changed my view on how to evaluate those situations. Um, and the essence of this book basically said a couple of things. One is when conflict happens, is that you dehumanize, you know, it's instead of being, you know, rich, it's uh it's Macy's or it's a you know, it's a big organization. And then the other being uh just not empathizing with a group and not taking accountability for what you own. That was another big piece of advice I got that really changed the game on how I manage my own time and energy on things is if a situation is not going well or there is conflict, is recognizing what you can do to make it better. And you don't have to own a hundred percent of the problem. You know, in any relationship, there are two people, organization relationships, et cetera. You don't have to own 100% of it, but you have to own 100% of your 50%. And so you have to really own what you can own in it and make sure you're doing what you can to de-escalate things, to lean in where you need to, to smooth over, to understand more perspectives, all that good stuff. That really was a pivot point for me. And it probably sounds simple and super obvious, but I think it made a big difference in how I approached some teams, how we approach clients, how I how I empowered teams to do some things differently that have massive impact on results. It really did turn around a few client relationships in a big way within weeks, honestly, just adapting some of that and building it into how the teams operated.
Rich:Do you find that there's an abdication of owned responsibility at times, either in the people that you may work with or in the projects or in who you come up with? Are we abdicating decisions to data or AI and not taking ownership in the results?
Katherine:I haven't seen a lot of that. I've seen more finger pointing uh across particularly large organizations than I've seen saying, well, the data said this. Geez, what's what's happening? I've definitely seen more of sort of the like, well, you know, I would do this, but you know, this organization, this silo, this person is doing something different. So I guess, you know, we'll have to see how that goes. See, more of that type of dialogue than abdicating to the data. And a very, I guess a good health check when that does happen with data is to add, you know, the data's never really wrong. The decisions we might make from the data might be wrong. We might not have looked at the full picture of data, the right set of data. But so I think that's then the question is like, okay, well, if we we end up in a bad result, it's not so much the data was right. It's like, how what do we miss in our data set and how we thought about it and learn from it? And honestly, if you're learning from that, then it's it's still generally recoverable.
Rich:So take that from a student perspective as we as we talk a little bit more about the advice. How do students take more ownership in their development? Because they're one of the things that when when we were in school and we were growing up, I think we were told that many of the jobs that we were going to be going for hadn't been created yet. Well, if we were told that, I can just imagine what it's like to be in college today. Yeah. And many of the companies that they may go work for haven't even been started yet, or they haven't yet started them. To what extent do you see this generation having to take more ownership and control over their path?
Katherine:Yeah, that's an interesting question. So I have a daughter, as you know, Rich, a daughter in college, and I was chatting with her the other day, and she she sort of has this idea in mind of going to grad school. And I was like, look, my best advice to you right now is to have a lot of options on the table because not only is your market changing really rapidly, but that's gonna have a knock-on impact. So she was interested in applying to grad school. I was like, she and she in her mind at the time, she's like, I don't think that's gonna be impacted as much. I'm like, no, but you know what, it's gonna be impacted. I would expect applications to triple or quadruple because all those folks who thought they had a career path that's a little bit soft now are gonna apply to grad school. That's sort of a well-worn cycle. That's my best advice is yeah, you do have to take ownership. Nobody owes you a job and it's on you to be curious and kind of scrappy, I think, and have a lot of alternatives. You know, I think that idea we were we started out with of um not having such a set path is really important right now because that path could change, it could go away, it could become oversaturated, I feel like in the blink of an eye these days. And so, you know, building enduring skills and being flexible is going to be super important.
Guy:And to that light too, Kathleen, do you would you advise college students? So, like I mentioned, I have a 17-year-old to be a college student in over in over a year, so it's kind of frightening, but is it important like to obviously be curious, but is there an undertone where you need to have at least some rudimentary AI or data knowledge, regardless of what industry you want to go into? Or how would you advise someone who asks you that? Like, oh, I do I need to take AI classes, even if I want to be a you know philosopher?
Katherine:Yeah, that's good. That's an interesting question. My brother actually is a philosopher, a philosophy professor. I think that's good. You definitely do not need I AI. No, I'm just kidding. Maybe you do. Um it's hard to imagine. I I don't know what an AI course looks like, if I'm honest with you, because in my mind, the thing about AI is that it it is sort of a great democratizer. You know, it's sort of like uh sort of making it less technical. I've always thought actually, this is I would say one of the big misconceptions about um the field of data and analytics historically. A lot of people think it's all about technical acumen. I I think five or ten years ago that question would have been do I need to know how to code in R or Python or something? And yes, that that in that day, that was a great advantage. But I honestly think beyond entry level, the most important skills are kind of curiosity, the ability to structure thinking, the ability to find connections and have hypotheses, the ability to try things that I think is a big differentiator. The ability to hear something that sounds a little impossible and think about and think, yeah, I know how I could do that. I I'm gonna go try that. That's a big differentiator, I think, in the marketplace and any data environment. So uh, do I think they need to double down on AI courses? Probably not. It's probably gonna change a ton. I mean, if they want to, that's great. But uh is it a requirement? Probably not, as long as you're able to do some of those other things. Connect dots, be curious, leverage technology. I think it's it'd be silly not to be leveraging technology, but I don't know that you have to be, you know, coding LLMs to do that.
Guy:No, it's good because it's it's I was just on a couple of college tours with my son, and some of the questions from the other kids on the tour was always like, well, what's the AI classes here? Well, what are you? And I I don't mean to be, I don't mean to be snarky, but I heard the question. I was like, you you don't understand what AI is, you just you know you just gravitate toward this. But I was interested, I think it's a really good answer about this curiosity. And I it sounds like in a way it's what we all did when we went to college, which is learn to think, learn to make connections and hypotheses and and push your boundaries. Don't worry about the tools because you'll use those. And I think that's interesting. That's that to me is is refreshing to hear because otherwise it's just it feels like to AI. And it's like, what does that mean?
Katherine:Yeah, the tools will change.
Rich:And I was having a conversation with somebody close to me who was talking about the cheating that's going on with AI, because there's obviously somebody who's saying, Hey, I need to do a two-page essay on Catcher in the Rye, and and they they get something spit out. But that was happening in the 1960s. You were just paying someone to write it for you, or you were just copying cliff notes or whatever they had back then. But I'm fascinated with the example that you have where students will go into a classroom, will record the lecture, transcribe it, use AI, notebook LM, whatever to turn it into a podcast so they have an audio version of it to create a quiz, a tutor that is teaching you. I think that's fascinating. And it's it's basically democratizing information.
Katherine:Yeah, it's innovative, it's basically personalizing a learning style. You know, that is taking agency over your own learning and personalizing the learning style to something that works for you. So I think it's great.
Rich:You mentioned earlier about the democratization of data and that it's table stakes. And I've heard you throughout our conversation. You mentioned earlier about the democratization of data and that it's table stakes. And I've heard you throughout our conversation go back to curiosity and and digging through it. Are we entering an age where it will make data available to everybody who, in a way, that they don't have to know how to connect the dots between systems, they don't have to learn how to code, they just have to be curious. And does that free up more people to think creatively and innovatively and push the envelope?
Katherine:Yeah, I mean, absolutely. I think the curious will win in the future. Because if you can, if you can sort of create the right uh connections, if you can ask the right questions, well, how does this relate to this? How does, you know, how do I think about you know this in the context of that? It's amazing. Plus, I think there will be a whole population of people that today don't have access to a lot of data or information or tools or techniques that this is fairly inexpensive and widely available. And so there are whole parts of our world that are gonna participate in innovation that haven't in the past. So yeah, I think it's gonna be a real game changer.
Rich:So as we get ready for the rapid fire round, that's my cue, Gee, to uh I'll let you take first and third so you can you can start thinking about it. Nice. Yep. I was having a conversation with somebody today, and this is the first time that I've asked this question on the podcast. If you could ask students today a question, what question would you ask?
Katherine:Gosh, that's a that's a fascinating question. Just full stop. I don't know. I would ask them maybe because I'm a parent, I'm always kind of curious about parenting and whatnot. I'd probably ask them what part of their childhood was uh sort of the most positive in their mind? Like, you know, what was the inflection point for them that was the most positive? And maybe the flip side of that, what do they think they did that they wish they hadn't done, or what do their parents do um they wish they hadn't done? That's probably what I'd ask. But that's just pure personal curiosity.
Rich:I'm not gonna turn that question on you. Um I'll I'll be fair. But how about in terms of if you have somebody in front of you who is a who's emerging talent, a college student, maybe not a college student, but is emerging talent. What question would you ask them to kind of challenge their thought process and get them thinking about the future?
Katherine:Yeah, I'd probably come up with some sort of look, I cheat a lot in interviews. I'll ask people about problems I'm noodling on at the moment to see how they think. And if they come come, frankly, if they can come up with a better answer, uh, you know, what they would do. But I think I would ask something that would get to their nature of creativity and curiosity and uh, you know, ask them maybe how they think agenda commerce will change how consumers behave and why, you know, what that would mean for their generation, how is being raised on kind of digital short sound bites, how does that impact their decision making? How do they think that will change commerce of the future and just see how the thinking progresses? So it's not really like a um a behavioral question, it's just a a little bit of a case, but I like to see how people think and how they structure problems and walk through them more than you know, set the answer. You can kind of say anything you want about how you are, but how you think is really interesting.
Rich:I think sometimes the reason I teach is because it gives me a semester-long focus group, and I learn how to communicate with very divergent personalities.
Katherine:Yeah, how people are thinking.
Rich:And so whether they paid me or not, those two things are very valuable to me. I bet.
Katherine:I mean, it's fascinating because every generation grows up in a slightly different context that influences how they think and how they perceive the world and move through it. And so, I mean, that's a super valuable input, Rich. It's a whole new data set.
Rich:All right, so rapid fire. We gave you a few questions. We're probably gonna pull one out of the air. If I know Ghee, he's going to. Why don't you go ahead and uh first thing that pops into the mind no science needed, just pure art? Gee, go for it.
Katherine:I'm awful at these, by the way. One time I was doing I'm really bad. One time I was nominated for an award and they did one of these things, and then and their question was if you were a cheese, what cheese would you be? And I swear to God, I couldn't think of a single cheese. And you know what I said was Velveeta. And I went back and I told my team, and they're like, Have you even eaten Velveeta? I was like, No, I don't, I don't know why I said that.
Guy:Velveeta cheese is delicious. I as Richard, I'm gonna pull one out of the air. And and since you mentioned you lived in London, I want to ask you this question. Are you blue or are you red? And see if you get the question.
Katherine:Oh my gosh, I don't know what that means. Is that a soccer team or something?
Guy:Yeah, are you Arsenal or are you Chelsea?
Katherine:Oh, I don't know. I didn't, I didn't take up soccer while I was there.
Rich:Oh, dude, I'm gonna I'm you're gonna have to ask another one because I'm Fulham, I'm black and white. So seriously, I came from London and that's just in the Premier League. You got um uh I'm gonna leave this in just to just uh you know follow your reputation.
Guy:I've been to Craven, I don't yeah, I've been to Craven Cottage. It's a great it's a great state. It is all right. Um, if you could pick one city you've never been to, which would it be and why?
Katherine:Probably a city in well, actually, you know, this is embarrassing. I've never been to Hong Kong. And so I would I definitely would love to go. I would definitely love to go to Hong Kong. I don't know why I haven't been yet. It feels that everyone in my orbit has been and raves about it, and it's their favorite city, and I've never been.
Rich:So it's a great city. One of my best experiences in Hong Kong, and I may cut this out depending on how it comes out, but was with uh our sourcing and design team in Hong Kong in an Italian restaurant with a Mexican mariachi band made up of Filipinos singing Madonna's like a virgin.
Katherine:That sounds amazing. Sounds about right for Hong Kong.
Rich:And it was just absolutely, yeah, and and and I know one of the persons listening to this is gonna laugh right now. I I have to ask, you've you've done a lot of speaking. Do you have a hype song or a walk-on song that you default to?
Katherine:I really don't. I really don't, but I do like hype songs, and there'd probably be things like I love soundtracks, I like um like the greatest showman, you know, kind of like real hype hype you up kind of stuff. Is that yours, Rich? Do you have one?
Rich:So no, I I listen to all kinds of music, but I will say, and I was gonna memorialize the fact that my daughter just got her first A plus in her collegiate career. And no guesses, the course was principles of marketing. So dad's really proud, and no, dad didn't do the work for her, this was on her own. But the greatest showman for her, and I'm a huge, huge Ackman fan. The greatest showman for her is that's her lift up. If she's having a bad day or mom's having a bad day, you listen to the you watch and listen to the greatest showman from now on.
Katherine:You just I mean that's it. I'm getting like imaginable. Oh, and I'm also a big Swifty. I I still I mean it's like a couple years since her tour and all, but it's that's fun.
Guy:All right. I want to ask one more question. So I had the first so this one is also a little bit off training. If you could time travel, would you go to the future or to the past?
Katherine:I might. Oh, that's a tough one. I think I might. I there was a time where I'd say to the future. I think now we'd say to the past. I had this bizarre obsession when I was a child with Little House on the prairie. I just thought it was an interesting time period. It was something about people exploring and you know, uncharted territory and pushing through all the you know quite physical challenges there that I found fascinating. I don't know if I would choose to go back, but I think I might go back. I also think the future it feels, you know, not to be a daunting, but it feels very uncertain at the moment. So the past.
Rich:I would go to the past, yeah. I think we have to ask that. I think we have to add that question.
Guy:It's actually a really I've never heard that question asked, and it's uh kind of a perfect question to I've spent many hours debating this with people about well, which what why would you go the in like how far in the past or how far in the future? Would you go like in your lifetime future, like or would you go like a thousand years in the future? Or would you go now? You can't impact history. You know, you can't do the back to the future, go back in time, give your you, you, you as a 20-year-old the the sports almanac and then come back. No, but you can observe.
Rich:Yeah, and Catherine, I think I I would, I don't I would have struggled whether I would have said past or future, but I'm with you. I don't know that I would want to see the future right now.
Katherine:Plus, then you see all the impacts of things you've done, which in the context you did them in made sense. But you just kind of know when if you think of all the things that have happened before us that at the time made complete sense, but now you're like, well, geez. Now we're here because of that. I don't know if I want to live with that uh burden.
Rich:Well, and the reverse is I'd like to go back and understand what truly happened in history because it's always told in different ways. Yeah.
Guy:Yeah.
Rich:All right. Well, Catherine, thank you very much. This is fantastic. We will have to have you on again. We'll we'll pick a topic and have a round table, but love the uh love the discovery of your journey and the advice for our audience and and emerging talent. Uh, thank you very much for today.
Katherine:Thank you guys. Always fun.
