George Jagodzinski (00:01):

Today, we discuss data, loyalty, and, most importantly, how you can truly understand and better serve your customers. We also plan an Italian art heist, but that's neither here nor there. I'm joined by Ian Dewar, who's had a fantastic career with brands like Specialized, North Face, VF, and now serves as the Senior Director of Global Strategy at Anthropologie. His perspective and approach are truly refreshing. Please, welcome Ian.

(00:21):

Welcome to Evolving Industry, a no-BS podcast about business leaders who are successfully weaving technology into their company's DNA to forge a better path forward. If you're looking to actually move the ball forward rather than spinning around in a tornado of buzzwords, you're in the right place. I'm your host, George Jagodzinski.

(00:59):

Ian, thanks so much for joining me.

Ian Dewar (01:01):

George, happy to be here. Nice to see you again.

George Jagodzinski (01:04):

Ian, what I was most excited to talk to you about is you and your teams have done a fantastic job of leveraging data to build great loyalty programs, great customer experience. But what I find when I'm out there in the wild talking to our customers and just hearing from people at conferences and roundtables, the majority of people just seem to be struggling with data. And they feel bad about it because they feel like, "Everyone must be doing a great job. What am I doing wrong?" And then, combined with that, different privacy policies putting in place, that data that they're not doing anything with is now becoming more of a burden, which makes it that much worse. I'm drawn to the human side, where I want to bring to them and our audience as much insights as possible. And so, I'd love to hear from you a little bit on your perspective on what do you think that you've been doing differently that allows you to actually truly leverage data for better experiences?

Ian Dewar (01:57):

Yeah, I mean, I think you're right that everyone feels a little bit of inferiority when they go to conferences, but conference presentations are like Instagram. People only show the good news. No one gets up and talks about something that didn't work. So there's just-

George Jagodzinski (02:11):

Just buy our software, click five things, and you can read your customer's brains, right?

Ian Dewar (02:17):

"We've got the perfect example of how it worked perfectly for us." But no one's perfect. But I'll say, from the data, and every time I've worked with the same thing like, "We're missing data here. We don't know this about our customers. What can we add? What can we add?" But I think what happens is, and brands that start on a data and analytics and especially consumer analytics program don't realize how much they already have. I started this process seven or eight years ago even... Yeah, eight, nine years ago at the North Face, we did a big data pilot back when big data was still the word everyone used instead of consumer insights analytics. But we did a big data pilot. We delayed it a little bit because we were scrambling to get budget. We were concerned we'd have to spend a lot of money to buy data. We thought, "God, we're going to have to buy data from a credit card. We're going to have to buy data from demographics, and we're going to have to buy data from some sort of behavioral consolidator."

(03:16):

What we found is, when we started in with our analytics partner, they were like, "Give us your CRM. Send us your email behavior. Send us your website. Send us your loyalty…" We had 90% of the data that we needed to start analyzing our customers, and that was not even with a super robust customer capture program. We had everyone's address, whoever orders from us online. We had everyone's email engagement, so what emails they opened, they clicked on, and what they bought from us. We had people's baskets when they logged into our website. We had their loyalty behavior. We had their loyalty redemption. Did they use a reward certificate? Did they buy something with the reward certificate? We had all this information that we hadn't pulled together. It was in a Salesforce database and a CRM database and a loyalty database, and we hadn't put it all into one place and said, "We're going to match Ian Dewar's record across seven different digital touchpoints and then look at what we know about him."

(04:12):

That was really eye-opening to us. I think any brand could do that. Any brand could take that point of saying, "Hey, we've got customer databases in multiple places." I still hear stories of brands whose POS retail doesn't match up to their e-com retail, which doesn't add up to their app checkout retail. And so, all of a sudden, they've got three separate transaction logs and three separate sets, but a lot of that data already exists. So I think the first hurdle towards this consumer shift to consumer analytics is just taking the time to look at what you have and starting there and recognizing that no brand knows everything about the customer.

(04:56):

No brand knows what you're doing, where you're... Google knows where you're walking because they're trapping your phone. But no brand knows everything about where you are, knows everything about what you buy, knows everything about your behavior. And so, that starting point of looking at what you already know or already have to piece together to say what you already know is really something that I think any brand that has... And direct-to-consumer obviously is more relevant than a brand that sells primarily into wholesale. But any brand that has that direct-to-consumer component has a lot of their starting point data, they just need to put it together into one place.

George Jagodzinski (05:32):

That sounds easier said than done, I think, for most people, right? Even within your own organization, connecting it from the stores to the e-com, “Is this the same Ian?” Never mind if you have 10, 100 different products and brands, and how do you connect those? I can't tell you how many organizations we've gone in, and they've had some enterprise ID project that's been going on for a year where they're just trying to connect to everyone, and it doesn't seem to be going anywhere. I'm curious, your experience, how do you push that over the line to actually connect the dots?

Ian Dewar (06:05):

There's a combination of internal and external partners that really make that happen. And it costs money. I think the initial setup is going to be something that the brands need to really think about what the ROI component of that is and what the benefit is. But the ROI component is very easy to calculate when you look at future sales opportunity. If you look at increasing your frequency by one visit per year or increasing your basket size by 10% and start to extrapolate out what the benefit could be by being more relevant to your customers, it's pretty easy to cost-justify the work to do that. I think that the challenge is setting an expectation for what is correct. To some extent, that's a big hurdle for a lot of companies because they don't want to be wrong. I mean, we've all heard stories about Target sending emails about baby clothes to a teenager who's pregnant, "Oh no, we did the data wrong."

(07:07):

I think probably half of your listeners have probably received an email at some point from one of these photo books saying, "Celebrate your wedding. Celebrate your baby," and they're like, "I didn't get married. I didn't have a baby." So the risk of being wrong certainly exists. But more than that, understanding what's possible with clear connection and knowing that, in some cases, if Jane Smith gets married and moves from New York City to Philadelphia and changes her last name and gets a new phone and gets a new job, we might not be able to connect those two dots right away. And that's also okay. And so, being able to say, "This is how we want to understand our customers." We want to understand our customers that are engaging with us most, and the customers that are engaging with us most are giving us the most data. And at some point at the bottom, we're not going to match every single person to every single record, but that's actually okay because what we want to do is understand the people that want to engage with us most.

(08:10):

I liken this sometimes to how you have personal relationships. You want to be friends with the people who want to be friends with you, and you like to have conversations with the people that are interested in what you're talking about. Our businesses are the same. The customers that engage with us the most give us the most data. Therefore, we understand them the most. And they're already raising their hand to say, "I like your brand. I like your brand. I open your emails. I go to your website. I log into your app. I like you." Now the onus is on us as brands to say, "You've given us that input into your life, shopping behavior. Now we should take advantage of that to show you the type of products we believe you like."

George Jagodzinski (08:55):

Yeah, and those users are easier to connect the dots across all those different channels because you have more information. Man, it's funny, it reminds me even just internally of, and this happens everywhere… From a people management perspective, you always fall into the pitfall of just focusing on the people who aren't performing rather than focusing on the people who are the high performers. It's just such a human thing it seems that we all fall into.

(09:15):

One thing that we've experienced at our customers when we're talking about that, how do we connect the dots, a lot of times, we go in, and it's a side project rather than a really important project. Maybe part of that's the ROI hasn't been mapped to it, but my observation is each group's just trying to hit their own number. The stores want to hit their number, e-com wants to hit their number, and everyone's marching to their own thing. That's why it becomes a side project, is they just need to do their thing and they're like, "Yeah, yeah, we should get to that." It's almost like, "Yeah, I should floss more." I'm curious if you have any insights or stories from the trenches on how do you get those groups who sometimes view themselves as competitive marching to the same drum.

Ian Dewar (09:56):

I mean, that's absolutely, absolutely a problem. I'll tell you, where I work today at Anthropologie, we are very cognizant of our customer's behavior with us is the reaction to where they want to be. So if they shop online, if they come to the store, if they order off the app, if they buy from TikTok Shop, I mean, all of those things are fine with us. We have a retail goal, we have an e-commerce goal within e-commerce, we have an app expectation, but we're not fighting each other.

(10:30):

I mean, I'll give you a good example. I worked for a brand years ago where I got pulled into the head of store's office because she was upset that we were sending emails out with a retail focus saying, "Come to the store near you," and we showed product in the email. I said, "Well, what's the problem? We have the link at the bottom with the picture of the store and the click to the map, but we're showcasing our most exciting product." She goes, "What if they click on it and buy it?" And I said, "Great." She's like, "No, then you are stealing our customer." We had to really walk through the idea that a customer who starts in a store, who then receives an email, who clicks on the email, and buys something from the website is not bad for the business.

(11:17):

And so you-

George Jagodzinski (11:18):

There's a CEO or CRO somewhere that just died a small death when they heard that.

Ian Dewar (11:24):

Or says, "Oh, I did that too."

George Jagodzinski (11:25):

Yep.

Ian Dewar (11:26):

But I think the thing today is that we are recognizing at Anthropologie, and we have relatively high frequency of repeat purchase with our best customers, but we're recognizing today that it's not on us to tell our customer where to shop. It's on us to make that shopping experience easier no matter where they want to shop. To that end, actually, COVID accelerated that with buy online, pick up in-store, curbside delivery, ship from store, all these different operations. But one of the biggest things that we shifted in the last two years was we've made it easier to return more products to our stores. We used to only allow returns to stores of products we sold in stores. So footwear, some of our kitchen, other items like that that the stores didn't sell, the stores wouldn't take back. We've completely shifted that. We've revamped the whole return to DC process to say, "Hey, we want to be where they are. And if they want to order online and return to store and try it in store, but order from an iPad or have it shipped to a different store or send it to a friend, all of those are possible."

(12:29):

I think that shift in mentality of counting customers and counting customers and revenue as a roll-up first and then dividing it by channel, product category, accessory edition, et cetera, is the way to start to look at it because that customer that shops with you once, if you can get them to shop with you twice, you can get them back for a third purchase no matter where that is, you're starting to create a sticky behavior, and that's what you want. It's not you want sticky store, sticky web, sticky app, you want sticky brand.

George Jagodzinski (13:03):

Evolving Industry is brought to you by Intevity. We bring order to chaos wherever people, process, and technology converge. Our culture drives our solutions, and we are solutions-obsessed. We see every challenge as an opportunity, every partner as a collaborator, and every project as a chance to share our values and commitment to excellence. Give us a shout. We'd love to hear your challenges and turn them into opportunities. Find out more at intevity.com. Now, back to the show.

(13:35):

I love that. Something that we talked about before that really drives that is that you focus on what will the customers actually use versus what can we sell them or what will they buy. I'm curious what that philosophy, what does that do for you? How does that impact the way that you're building experiences? How does that impact the way you're leveraging data for products? Tell me a little bit about that, about products people use.

Ian Dewar (14:00):

I mean, for me, that's been our philosophy on consumer analytics from the time we launched this big data pilot with North Face years ago. Our big learning there was that customers buy product in the same category on a pretty regular basis. If you are buying a ski jacket from the North Face, you're probably more likely to buy ski pants from the North Face than you are a backpack. But they also buy in the category of product that they will use. And so, what we did is we really started to focus on what customers do with the product, not what they bought from us. And what you do with the product, and this is true for North Face, it's true for us at Anthropologie, it's true for other brands that work that way, what you do with the product really helps us shape what the next best product for you could be or should be.

(14:52):

What we found, and it's even more true now at Anthropologie, is that people have personal style, and there's regional style. And so, we sell a medium-length and full-length dress called Somerset at Anthropologie. It's one of our best-selling dresses. It comes in multiple styles, multiple fabrics, multiple prints, and what we find is, depending on where the customer lives, New York City, San Francisco, Denver, Colorado, where I live, they style it completely different. And so, this whole idea that 60% of people who buy a Somerset would like a “insert blazer or jacket here,” it's not relevant for the whole country. And so, for us, what we really needed to look at was all this additional data.

(15:38):

When I worked at the North Face, we focused on activity data like, are you a runner? Are you a hiker? Are you a skier? Do you use North Face product for hanging out with your family, or do you use it for your own more hardcore adventures? Same thing at Anthropologie. Are you buying our product for yourself to go to work, to go to a party, for your everyday life? And then, what else do you do in your everyday life? And that helps us not just complete the look, but really complete the closet. And that part of your “in real-life” behavior becomes that much more important to us and helps us as we start to think about building customer profiles. It's not just what you bought and how much you spent. It's what we actually think you're going to do with it.

George Jagodzinski (16:28):

Interesting. And then that probably helps you build, I'm assuming, just models to find similarities, overlaps between different groups, and all that.

Ian Dewar (16:36):

Yeah, absolutely. And what we find is that there's product category similarities, there's style similarities, and there's end-use similarities. What I mean by that is that, again, Anthropologie, there's some correlation between certain prints and styles of home decor items and certain prints and styles of fashion items. They're not in the same group. It's not the same fabric, but customers who like a set of prints over here on apparel like a set of prints over here on home decor because it carries over in that style.

(17:15):

And so, starting to look at some of these similarities because our goal with data and analytics, you said it earlier, we're not trying to trick people into buying something they don't need. I started my career in consumer analytics and marketing in cycling. This is going to sound super obvious when I say this, but if you sell someone a bike they don't ride, they do not buy another bike. Right?

George Jagodzinski (17:40):

Yeah.

Ian Dewar (17:41):

And so, the way you get someone to buy another bike or to upgrade their bike is to provide them opportunity to have a fun cycling experience. I worked for Specialized Bicycles, but the company I worked for made a big investment in bike fit technology because what we realized was if a customer was more comfortable on their bicycle, they were more likely to ride that bike, and then they were more likely to buy another bike. And so while this sounds super obvious when I say that, it's true as we transfer over to outdoor equipment apparel at North Face or apparel and decor items at Anthropologie, if you don't like what you bought and you don't use what you bought, you're not going to come back and buy more. And so, for us, this whole idea of quick sale, quick sale, that's not as nearly as relevant as us thinking about how do we help our customers build either their home decor or their closet so that they start to come back and say, "Oh, I can use this item again and again, it has more value to me, and now I feel a stronger affinity towards the brand."

George Jagodzinski (18:48):

That makes so much sense. I like to dig into the cycling thing. Just myself as an avid cyclist, and my friends and I not just talk about our bikes, but having an entire stable of bikes, man, if there's one customer base out of any that I've experienced in my life that is willing to just spend a tremendous amount of money like, "Hey, I could lose five pounds or I could get this super awesome carbon fiber component for God knows how much money. I'm going to buy that thing." I'm curious, in that world, did that group have a name? Would you focus on that group, that super high performer?

Ian Dewar (19:26):

It's interesting because there's two levels of that super-high performer. There's the team racer, club racer, and then there's the super enthusiast. The team racer, club racer wants new product every year, and they're generally sponsored by a shop, and there's some level of price benefit for being associated with a shop, and they're looking to get new technology every year. But the real opportunity is in the high enthusiast, the hardcore rider. That hardcore rider, you're exactly right, that's the opportunity to build the repeat purchase, not upgrade purchase, because what happens in the upgrade purchase is the customer sells their bike into the secondary market and buys a new bike, buy a new road bike, buy a new mountain bike. But the person who buys the used road bike is now not going to buy a new bike. So in the total scheme of bike sales, you're one out, one in. Therefore, it's a missed opportunity for the bike company to sell a bike to the customer who bought the used one, they're only selling into the new, but the opportunity is to get that customer into a new category of product.

(20:37):

In the last 10 years, a lot of that was triathlon. Starting five years ago, a lot of is gravel today. And so this whole idea that if you're an avid mountain biker and you want to expand your riding opportunity, gravel's here for you now, so now here's a new type of bike for you. I mean, the bike companies recognize that there's only so many riders. Yes, COVID caused a huge increase in that rider base. When you couldn't go to the gym and you couldn't go to work, and you had more free time, people all went and bought bikes. Now we're back to normal, so this bike build opportunity is category extension. How do we get someone who mountain bikes or road bikes to buy a gravel bike? How do we get someone who rides a gravel bike to try cycle cross racing and buy a racing bike? All of this, so that's your growth opportunity for sure in cycling, is to take that high enthusiast and expand their field of vision of riding opportunities.

George Jagodzinski (21:35):

Yeah, I love that. I'm curious to pick your brain a little bit on maybe some techniques or examples. Then how do you lean into the whole human? This applies to everything, but I'm going to stick on the bike thing just for a second because as someone with a triathlon bike and a road bike and a city bike, a lot of those then once I had my daughter and moved out to the burbs started collecting a lot of dust, I'm a little bit more fearful on the road. And now I am a gravel bike guy, and there are these life milestones even at Anthropologie, so just bringing it to the future, my little brother lived in LA. When he would come out and visit me in Boston, he would have just fashion shell shock. He'd be like, "What the heck is going on in here?" Boston versus LA. I would imagine after someone does move and once they're getting into that area style a little bit more, then their likes might change. Long way to ask, how do you focus on the whole human and where they are and where they're going?

Ian Dewar (22:33):

I mean, I think that's true. All three of the brands I referenced, whether you're talking about bike business or outdoor like North Face or even Anthropologie, this is part of the opportunity for brand extension that direct-to-consumer companies realized 10 years ago. Your Anthropologie, we are expanding into non-core traditional things that we wouldn't have sold 10 years ago, sneakers, swim, getaway, sunscreen. We have a huge sunscreen business. Who knew, but we have a huge sunscreen business. But what we've recognized is that if a customer trusts us for core categories, they're going to trust us for other categories. If they look at us as fashion-forward for women's apparel, then they're going to acknowledge that we're also... And we are trying to be fashion-forward for sneakers and all of this additional accessories, but they see that from us, and there's a level of trust that already exists.

(23:32):

I think some brands sometimes get too... How should I put this? Get too excited about it, and they slap their brand label on everything possible. You know what I mean? I think that as you think about what your brand is really good at and known for and what other things your customers care about, that's where your opportunity for brand extension really exists. Specialized moved into shoes pretty aggressively about 15 years ago and is now one of the absolute premium cycling shoe components across North America. They made a substantial investment in both improving the riders' experience through the shoe and understanding the technology that went into a cycling shoe. What shoes need a carbon soul? What angle does the foot that need to lead at? Do different people have different footbed components and necessity in there, and how do they understand? They ended up mapping thousands of people's feet to then understand what's the starting point for a shoe that will fit most people and what can be done in foot bed technology to then make that shoe comfortable for the outliers on both sides.

(24:45):

And that's a substantial investment in a new category, and I think that's something that sometimes brands think, "Hey, we're popular in category A. Let's just jump into B and C." There was North Face Sunglasses for a while. Bad idea, and it went away. I think as brands think about how they increase their relevance with their customers, this is where the other side of consumer analytics fits in, and this is more on the consumer insights, but talk to your customers, find out what they care about, and find out where else they're shopping, what else they're buying. You don't need to know where every single one of your customers is shopping. A survey, customer intercepts, focus groups, et cetera, will give you a starting point. But if you understand more about what your customers care about, then the brands can really think about what the right brand extension or the next brand evolution should be to increase your relevance and increase relevance in the customer's closet or home overall.

George Jagodzinski (25:48):

And if you have the great kind of mechanism set up to continually learn from those customers, I don't think it's a bad idea to try these new things. You want to try new categories. You want to try licensing deals, partnerships. But where everyone falls flat is where they just let that run too long, and they're not listening and shutting it down quickly. And so, that makes a lot of sense to me.

(26:07):

In that, to make that work, you really need to be connected across the various functional groups within the organization. You had talked earlier about working across the different channels, but where I see organizations really struggle is you got your analytics group, you got your e-com group, you got marketing, you got brand. I'm seeing a lot more organizations really focus around brand more recently than they have ever. But I'm curious, some of your lessons from the trenches on how do you get that cooperation across those functional groups.

Ian Dewar (26:40):

I think it's a challenge because, especially in emotionally led organizations, there is generally a strong point of view on communication strategy and a strong point of view on product strategy. Those are both driven by people who, generally, have had years of experience and understand what they think that customer wants to see. And to have someone from data analytics come in and go, "Well, actually, our customer's average age is four to six years old, and our customer's average home value is $730,000, and our average customer drives a BMW," that's not necessarily what they're looking to understand. I think threading that needle of art and science, that's the future of where data analytics professionals are going to excel, is being able to say your company might not be entirely, but it is data-informed, and we are using both our customer's known behavior, what did they buy. There's no ambiguity there. We sold X units of product Y, and we sold them in these regions, and the average age of the customer who bought them was this. That's irrefutable.

(27:48):

But to flip it around, and this is where insights and qualitative research become super important, is start to find out why, and then start to find out what's missing. I think that's one of the things that gets lost sometimes in straight-up quantitative analytics around customer behavior is you're analyzing what the customer did, not what they wanted to do. And so, it's hard to judge missed sales opportunity when you run out of a certain size of a product. It's hard to judge sales opportunity when you don't sell certain products in certain stores. Our shoe sales are obviously higher in the stores where we have a broader collection of shoes. It's not necessarily because customers in St. Louis don't want to buy shoes from Anthropologie. It's maybe because we don't have shoes in our St. Louis store.

(28:40):

And so, if you start to look at this and start to look at this level of customer behavior, understanding the motivation and being able to then look at missed opportunity in addition to what the sales data shows you is going to help way better size that future opportunity. That's where I think the partnership on doing this research, it really needs to include the end users of the data. And so, one of the things that we do, this is the same as work we did when I worked with North Face, but at Anthropologie, we very much include our product partners and our marketing partners as we develop our research hypotheses way before we go out into the field or way before we go out and start to talk to our customers because we don't want to do research they don't want to use.

George Jagodzinski (29:27):

And even if it is the same research they were going to do, now, at least, they feel invested in it as you're going out there, right?

Ian Dewar (29:33):

Yeah, absolutely. Yeah, no, absolutely. Also, we reserve space in our calendar for questions that come up, unknowns that maybe we didn't initially plan around. But we recently did a pretty extensive customer census at Anthropologie, for example, in that we surveyed a million of our customers, we got a pretty high percentage of them to reply to. We asked them about their shopping behavior, the brands that they like, where else they shop, where they live, what they do, what they do with their families, and really to just better understand overall lifestyle behavior. But there were a bunch of questions that came out of that as we worked with our head of merchant or head of product for home and the apparel business that prompted us to, "Hey, we need to do a deeper dive into some specific components here," because we've seen opportunities, now we want to size that opportunity, so how do we see and size that opportunity?

(30:27):

But because we were attached to the business from the very beginning, the research feels a lot more appropriate to what the business feels is possible. I think sometimes, and again, in data especially, analysts get focused on what they see the data saying and not necessarily how the business can use that data. And so, having that partnership with the business and on the marketing side, having that partnership with the creative side of it, that's where the art and science need to work together. We're a very emotional brand. North Face is a very emotional brand. We're not going to let AI pick the pictures for an Instagram post, for example. And that's very, very considered, as truthfully it should be. I think there's definitely opportunities to inject AI into product recommendations, into merchandising, into outfitting. But at the whole, we're still working together with how do we tell a story and how do we tell a story and understand what story our customers are most likely to respond to.

George Jagodzinski (31:34):

That's great. Maybe you just answered this, but I do want to poke into it. I'm curious if you could share how you got such a high response rate. Was it just because it was corroboration between product and creative and data, or was there something else you could tell me without killing me?

Ian Dewar (31:50):

In terms of our customers, our customers love talking about our brand. Part of that is, again, we have a pretty high frequency of purchase from customers who come to Anthropologie, especially customers who come back year over year. Big component of our business is our core active best customer. But I think there's two things. One, our customers really look at the uniqueness of Anthropologie and see it as a store that's different from everywhere else they shop. And as such, they like to tell us about why they like it. But secondly, they've also seen over time, especially customers that have replied to previous surveys or have been involved in other research we've done, that we really try to act on what our customers tell us. And so, there's a level of investment in providing feedback because our customers actually believe that we will respond to that and that they will, ultimately... I'm extrapolating a little bit... but that they will ultimately have a better shopping experience to see more product that they like if they tell us their opinion.

George Jagodzinski (32:55):

That's a great lesson in there, Ian, because I think it applies even just internally to our own organizations. We do our own employee surveys and things like that, and I think anytime that anyone with customers or employees you're not getting a response rate, you're looking for some sort of quick fix, but really, it's the hard work and loyalty and engagement and then listening and actually acting on that, right?

Ian Dewar (33:16):

Yeah, No, I agree, absolutely. I think the idea of a brand evolving both the products they sell, also how their loyalty program runs, also how they engage with customers based on customer feedback and then saying that out loud tells the customers, "We care about your opinion. We're not just trying to get you to buy more from us."

George Jagodzinski (33:38):

That's fantastic. Another couple of questions, Ian. One is, and a little bit of a shift here, is you've been doing some interesting work with Drexel, leveraging interns. I think a lot of organizations out there aren't tapping into some truly untapped talent that's out there. I'm curious if you could talk about that a little bit and how you've been able to lean into that.

Ian Dewar (33:59):

Yeah, actually, I love our co-op program. Drexel has most students in their business school do a five-year program where they have two or three six-month internships over their five years before they get their degree. We typically bring two of them into my org every year, a more consumer insights-focused and a more analytics-focused intern. The insights isn't always out of school business. They may be from psychology. They may be from fashion. The analytics side is generally from school of business, someone who's studying statistics, math, business analytics.

(34:34):

They come in, they have a desk for them, we have real projects for them. Literally, we're switching interns every six months, so there's generally about a week gap. So it's effectively a permanent position for us, just a new body every six months in that, but we're having them work on real projects and deliver things that get presented all the way up to the president of our business and even our CEO. And so, it's not a make-work project. It's truly someone who adds to our team. But our opinion is, if we can provide some direction, yes, we get a benefit because we get work done that we would ordinarily have to hire someone else out of, but we can also use that as an opportunity to look for future employees. We've hired three people, I think, in the last four years out of Drexel co-op with us or potentially with one of the other brands. Our parent company also owns Urban Outfitters and Free People. And it gives us not just a tryout per se, but it's an opportunity for a future graduate to get real business experience and understand is this the type of place they want to work and are they the type of person that we would like to hire. And so, I think it's a huge benefit there.

(35:48):

In addition to that, I think you're sort of alluding to this, I love having younger employees, current college students, or sometimes we've hired MBA interns in the past to tell us how they shop. You know what I mean? I think there's a big gap between what we see. I can go to the store, and I can talk to the customers, and I can look at their data, but to ask someone, "How do you and your friends shop? What stores do you go to? When you go to the mall, what's your behavior?" it's really interesting for us to have people who are now interested in helping Anthropologie but have a completely different perspective than someone like me who's worked in direct-to-consumer businesses for 25 years.

George Jagodzinski (36:33):

I feel like a lot of people, they just feel like this is going to be a burden on top of their day job when it's quite the opposite as you're experiencing.

Ian Dewar (36:39):

No, it isn't.

George Jagodzinski (36:41):

The energy and thinking that it injects into the group is just...

Ian Dewar (36:44):

We did a project with a graduate school class last year at Drexel in that we did an analytics challenge time. We gave them a bunch of customer data, and we said, "Help us understand the impact of regional style, weather, a couple other variables." We left it really open-ended. We went in and presented about our business, and then they came down to campus three months later and told us what they found. I thought it was great. And so, for us, Drexel is a good partner because it's really close to us, but I love the idea of working with university students and having... Our co-op program is not exclusive. Our intern program is not exclusive to Drexel, obviously, but having that level of new ideas and, I think, an opportunity for opportunity future graduates to try out, like, do they want to work for us? I mean, I would recommend to anyone who was getting ready to graduate to do as much research as possible on where you want to work, not just go in and you don't go in an interview begging to get a job. Really interview the company that's interviewing you.

George Jagodzinski (37:50):

Yeah, there's plenty of opportunities out there. You have to find the right one. So Ian, I always like to finish these on a fun question, which is, in life or work anywhere, personal business, what's the best advice you've ever received?

Ian Dewar (38:03):

I would say the best advice is just say yes. People ask you to do something, try it. If someone suggests that you take on a project, do it. Someone wants you to move into a new category where you're like, "I don't know that product very well," just say yes and try it out. I've tried to instill that in my professional and personal development. But also, I have two kids. I coach the girl's eight-year-old soccer team and a boy's baseball team. I listen to the kids, and sometimes, they ask the most inane questions. I think kids hear no, no, no, a lot, so if you can say yes more often, I think I'm all for that. I would say the same thing in a professional career. If you can take on a new challenge and someone asks you to do something, and it's not someone offloading their work onto you, take it.

(39:07):

You don't know exactly how to do it, figure it out. I think for me, I mean, I started my job, I got a master's degree in economics, and I turned down a job with the Canadian government. I went to Europe to lead bicycle tours. Then I got offered a position in the education department at a university in Toronto. I thought about it, and I also turned that down to design bicycle tours. My parents were like, "What are you doing?" It evolved from leading bike tours to writing marketing material, to taking photographs, to then analyzing the customer database of the bicycle tour guests, to then designing these loyalty programs for bike companies. It was always because someone said, "Hey, do you want to take on... Hey, do you think you could look at our data and figure out who's most likely to come back and go on another trip?" I was like, "Absolutely, I can." And then, I looked at the data and then I did a bunch of research to figure out how to analyze it.

(40:07):

And I think that idea that opportunities will show up if you are present for them. Thinking about these university graduates, you're probably not going to be doing 10 years from now what you studied in class today. And so, I would say, if someone presents an opportunity to you, take it and figure out how to do the work once you get it.

George Jagodzinski (40:29):

I love that. I do have a surprise question then, which is, Ian, would you like to go to Italy with me and become art thieves? You have to say yes. You have to say yes.

Ian Dewar (40:39):

I would love that, actually. I would love that, but only if we can drive the little Mini Coopers when we're done.

George Jagodzinski (40:46):

And you have to learn how to jump through lasers like Catherine Zeta-Jones, okay?

Ian Dewar (40:50):

I can do that. How hard could it be?

George Jagodzinski (40:52):

I'll have to limber up. Ian, thank you so much for being here. I really appreciated it. Enjoyed it.

(40:59):

Thanks for listening to Evolving Industry. For more, subscribe and follow us on your favorite podcast platform. And, pretty please, drop us a review. We'd really appreciate it. If you're watching or listening on YouTube, hit that Subscribe button and smash the bell button for notifications. If you know someone who's pushing the limits to evolve their business, reach out to the show at evolvingindustry@intevity.com, or reach out to me, George Jagodzinski, on LinkedIn. I love speaking with people getting the hard work done. The business environment's always changing, and you're either keeping up or going extinct. We'll catch you next time, and until then, keep evolving.