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Speaker 1: This is Masters in Business with Barry Ridholts on Bloomberg Radio.

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Speaker 1: This week on the podcast, I have a special guest.

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Speaker 1: Her name is Professor Barbara Con and she teaches retail

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Speaker 1: and marketing at the Wharton School of Business. If you

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Speaker 1: are at all intrigued by the impact of not only

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Speaker 1: Amazon on the worlds of retail, but how overbuilt retail is,

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Speaker 1: and why it's inevitable that B and C class malls

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Speaker 1: would would go out, why so many retailers are failing

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Speaker 1: to keep up, failing to compete, why it's inevitable that

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Speaker 1: we're going to see a lot of these retailers go down,

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Speaker 1: and how all these really interesting applications of data, analytics

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Speaker 1: and technology is completely changing how retailers operate. Uh the

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Speaker 1: experiential aspect of it, the ability need to capture data

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Speaker 1: in stores that previously only existed online is a very

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Speaker 1: very significant change, and the ramifications from that are going

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Speaker 1: to be felt for quite a long while. With no

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Speaker 1: further ado, here is my conversation with Professor Barbara Con.

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Speaker 1: I'm Barry Ritolts. You're listening to Masters in Business on

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Speaker 1: Bloomberg Radio. My special guest today is Professor Barbara Con.

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Speaker 1: She is a professor of marketing and a director of

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Speaker 1: the J. H. Baker Retailing Center at Wharton, part of

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Speaker 1: the University of Pennsylvania. Previously to that, she was dean

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Speaker 1: at the University of Miami Business School. She is the

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Speaker 1: author of The Shopping Revolution, How successful retailers can win

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Speaker 1: customers in an Era of Endless Disruption. Barbara Con Welcome

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Speaker 1: to Bloomberg. Well, thank you very much. It's fun to

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Speaker 1: be here. Uh, it is, and and this is such

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Speaker 1: a fun topic. I really enjoy uh the subject. And

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Speaker 1: let's just jump right into it. It's a chapter in

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Speaker 1: your book. I have to start with how disruptive is Amazon.

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Speaker 1: It seems like every announcement they make royal is an

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Speaker 1: entire sector of the stock market. Yeah, it's really amazing.

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Speaker 1: Every day something new from Amazon, and every day there's

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Speaker 1: massive reaction and a lot you do see stocks move

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Speaker 1: up and down as Amazon says something or other threatens

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Speaker 1: to go into health industry, into financial services. People are afraid. Um.

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Speaker 1: And it's interesting because what Amazon does is a disruptor.

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Speaker 1: There's no doubt about it. Um, and they disrupt. One

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Speaker 1: of the most famous Jeff Bezos quotes, which I have

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Speaker 1: never seen actually written down, but everyone on the internet swears.

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Speaker 1: He said, this is your margin is my opportunity, and

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Speaker 1: that idea of taking out margin, in other words, taking

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Speaker 1: out profit is pretty scary and when they can do

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Speaker 1: in a sustainable way, that's disruption. So let me broaden

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Speaker 1: the conversation. Online retailing isn't even double digit yet, it's

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Speaker 1: not ten, of which Amazon is just under half. Are

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Speaker 1: we getting a little all worked up for five of

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Speaker 1: the market, or is the overall trend what's scaring the

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Speaker 1: Jesus out of everybody? You know, I don't think it's

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Speaker 1: that online per se. I think it's changing the whole

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Speaker 1: shopping experience. People talk about as omni channel, but right

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Speaker 1: now it's just retail. Retail is now become a seamless

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Speaker 1: integration between online and offline. The the original online retailers

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Speaker 1: are opening up stores. Even on Amazon is opening up stores,

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Speaker 1: which is kind of mind boggling that they're opening up bookstores.

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Speaker 1: You know, well, it's been so successful for Apple. Are

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Speaker 1: some of the other technology companies trying to imitate that?

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Speaker 1: You see that? Also Microsoft, and you know, I mean Sony,

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Speaker 1: which is electronic they're opening up a direct store for them.

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Speaker 1: But when they open up these new stores, they're different

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Speaker 1: from old stores. They're not the same thing at all.

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Speaker 1: They're much more concentrated on customer experience. Some of the

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Speaker 1: new stores that open up a showrooms, they don't even

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Speaker 1: carry inventory per se. And that's part of the point.

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Speaker 1: You really can't say what's the percentage of shopping online

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Speaker 1: anymore because some people will shop online pick up in

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Speaker 1: the store. Then where do you where do you code

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Speaker 1: that you know what what is that is that online

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Speaker 1: shopping or offline shopping? So I've experienced that with both

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Speaker 1: Home Depot and Lows. You want something specific, they may

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Speaker 1: not have this particular snowblower, but you can buy it online.

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Speaker 1: They're shipping stuff to the store anyway you pick it

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Speaker 1: up there. There's no additional shipping cost. Yet you feel

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Speaker 1: like you're actually making it as friction free as the

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Speaker 1: usual online shopping. Is that what's meant by omni channel

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Speaker 1: is everything to everybody. Omni channel is thinking about not

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Speaker 1: dividing up whether it's online or offline. It's all one

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Speaker 1: big channel, and that's going to become not a real

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Speaker 1: word anymore, and we're just going to think of this

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Speaker 1: as retail you know, when you buy retail, you can

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Speaker 1: go online, you can go in the store, you can

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Speaker 1: pick up there, you can buy there, whatever, shop it

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Speaker 1: on your phone. So I've noticed at stores like my

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Speaker 1: wife calls is a retail therapy, but it's stores like

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Speaker 1: Macy's or Lord and Taylor. If you're looking at something

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Speaker 1: in a salesperson, some of these stores still have sales assistance.

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Speaker 1: If you're looking at something and they don't have it

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Speaker 1: in the color, size, whatever you like, they're very quick

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Speaker 1: to say, we can order it now and have it

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Speaker 1: shipped to your home for free. Would you like to

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Speaker 1: do that? And if it's something you're familiar with the size,

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Speaker 1: it's like, yeah, sure, it's one less package I have.

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Speaker 1: They don't want to let any transaction slip away without

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Speaker 1: converting it to an actual sale. Has that been your experience,

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Speaker 1: Oh for sure that's the case. So there's not all

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Speaker 1: the traditional retailers are doing that now. So this is

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Speaker 1: a purposeful approach, not just one savvy sales person. Yeah,

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Speaker 1: you know, but I wonder when you tell that story,

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Speaker 1: one of the things that's interesting to me about is

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Speaker 1: whether that salesperson's on commits or not, because and that's

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Speaker 1: what I think is interesting about say, what I consider

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Speaker 1: a very creative retailer like Sephora, where the salespeople are

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Speaker 1: not on commission. And the reason I bring up this

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Speaker 1: point here is when you say I'll send it to

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Speaker 1: your store, send it to your home, is she really

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Speaker 1: trying to she or he the sales associate, really trying

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Speaker 1: to give something of value to you, which is the

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Speaker 1: way you told the story, or were they trying to

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Speaker 1: upsell so they make a commission. And that's a subtle difference,

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Speaker 1: but I think it's an important difference. Well, if you

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Speaker 1: walk in to a store and you find something you

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Speaker 1: like and I'm looking at three Let's say we're looking

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Speaker 1: at shirts and there are three different colors and extra

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Speaker 1: small up to double XL and I want this color

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Speaker 1: and the size and they don't have it. It's not

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Speaker 1: so much an upsell as a lost opportunity, right, And

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Speaker 1: that that's how I took it. Okay, in that case,

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Speaker 1: it's positive. But but I want to make that point

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Speaker 1: because I think this idea retailer that retailers had in

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Speaker 1: the past of doing whatever they can to make the

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Speaker 1: next sale backfired when Amazon came in, Because I think

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Speaker 1: what Amazon is trying to do is really make the

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Speaker 1: customer experience easier, you know, and they make you so

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Speaker 1: you can get in and out of the website very quickly.

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Speaker 1: When Amazon famous for is they patented in one click

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Speaker 1: shopping at the and I when I found out that

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Speaker 1: that was patented, that was shocking to me. It's like,

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Speaker 1: why would that be patentable? And then you have to

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Speaker 1: go back to think what was the way retailers thought

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Speaker 1: and what they used to think when you're online is

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Speaker 1: keep people online as long as possible. They would talk

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Speaker 1: about web strategies where you have a landing page and

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Speaker 1: if it's designed right, you go further and further into

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Speaker 1: the website with the idea the longer people are on

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Speaker 1: the website, the more they're likely to buy a store. Right.

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Speaker 1: And that's why I was saying with the salesperson too,

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Speaker 1: if it's a function of just trying to make sure

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Speaker 1: you make a sale, like you said, anything I can

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Speaker 1: do to make a sale, that's not what Amazon does.

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Speaker 1: Amazon said, let's make it as easy as possible for you.

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Speaker 1: And that was the first time people really tried to

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Speaker 1: do that, and that's why they could patent one click

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Speaker 1: shopping so going back to your example, the way you

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Speaker 1: told the story, it was easier, it was better. But

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Speaker 1: you could also imagine an alternative scenario where people are saying,

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Speaker 1: I don't want you to walk out of the store

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Speaker 1: without making a purchase, and they start doing a harder

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Speaker 1: and harder sell. That's not really customer focused anymore. That's,

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Speaker 1: you know, sales focused. Quite fascinating. Let's talk a little

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Speaker 1: bit about retail and specifically, I have to discuss the

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Speaker 1: con retailing success matrix. Tell us about those four quadrants

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Speaker 1: and what they mean. Yeah, well, I mean I did

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Speaker 1: name it that, but I think it's interesting. That's what

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Speaker 1: that name is. Something I could think of nothing else.

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Speaker 1: But anyway, the idea behind the success matrix is when

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Speaker 1: when I um I recently stepped down as director of

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Speaker 1: the J. H. Baker Retailing Center. I had been there.

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Speaker 1: I had been the director for the last six and

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Speaker 1: a half seven years, and during that time I ran

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Speaker 1: into a lot of changes in the retail industry and

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Speaker 1: being an academic, when I stepped down, I wanted to

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Speaker 1: take a deep breath and try to organize everything into

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Speaker 1: some kind of framework, and so I went back and

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Speaker 1: looked at traditional retailing matrices, and they focused on the product,

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Speaker 1: and they focused on operations or logistics if you want.

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Speaker 1: And that was it. And if you want to talk

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Speaker 1: with this about someone is a great retailer, let's say

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Speaker 1: Mickey Drexler. He was called the merchant prince. But that

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Speaker 1: meant he knew how to merchandise, he knew how to

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Speaker 1: assort product, he had a good eye. And nowhere in

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Speaker 1: any of these traditional retail matrices was the customer. As

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Speaker 1: a marketing professor, the first principle of marketing is the

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Speaker 1: principle of customer value. And what does customer value mean

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Speaker 1: in retailing? Give them a product they value from a

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Speaker 1: retailer that they trust, that idea of retailer that they trust.

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Speaker 1: That was missing. The second principle of marketing, which was

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Speaker 1: not in any of these traditional retailing matrices, was the

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Speaker 1: principle of competitive advantage. If you're in a very a

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Speaker 1: competitive market, you've got to be better than the competition.

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Speaker 1: That means either increased pleasure or take away pain. So

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Speaker 1: those two ideas form the underlying theory of the matrix.

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Speaker 1: The columns are the principle of customer value, product benefits,

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Speaker 1: or customer experience the rows are the principle of differential advantage.

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Speaker 1: Do it better by increasing pleasure or do it better

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Speaker 1: by removing pain? And that gives me the two by

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Speaker 1: two matrix that I call my so I I broke

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Speaker 1: it down in your book, which let me um, is

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Speaker 1: called the shopping revolution. Brands, experiential friction, lists, and low costs.

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Speaker 1: So each of those things either make it more fun

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Speaker 1: or less painful, or what's the sect or focused on

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Speaker 1: making the product more fun or less painful, or focusing

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Speaker 1: on making the customer experience more fun or less painful.

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Speaker 1: And what's really new in the matrix is that second

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Speaker 1: column of customer experience and what Amazon redesigned, in my opinion,

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Speaker 1: is making the customer experience frictionless easy. That's interesting. How

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Speaker 1: much of this is driven by this millennial generation? And

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Speaker 1: I guess I was going to ask a dumb question,

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Speaker 1: which is how much of it is technology? But how

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Speaker 1: do you really peel apart millennials and technology and second

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Speaker 1: nature to them? So the let me rephrase that question.

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Speaker 1: The combination of millennial preferences and the very use of technology.

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Speaker 1: Is that what's driving a lot of this? Yeah, I

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Speaker 1: think it is, actually because when Amazon started, they started online,

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Speaker 1: you know, and they started with books. And you have

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Speaker 1: to think back, why did they start with books? And

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Speaker 1: I would argue they started with books because the product

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Speaker 1: and the shopping experience could be completely digitized. Once it

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Speaker 1: can be completely digitized, then what they did is have

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Speaker 1: an endless assortment. So they had more assortment than any

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Speaker 1: physical store, and they reduced prices by ten to That

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Speaker 1: was a dominance Lucien and attracted customers. But you're right,

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Speaker 1: it started with technology, but the basic idea of removing

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Speaker 1: pain from a customer experience does not have to be technology.

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Speaker 1: Because think of what Walmart's doing now curbside pick up.

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Speaker 1: They could have done that a long time ago and

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Speaker 1: made shopping easier, but they didn't. They made you come

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Speaker 1: into the store, walk up and down the aisles, stay

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Speaker 1: in the store as much as possible, impulse shop, you know,

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Speaker 1: all the ideas, put the milk in the back, All

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Speaker 1: of that was to keep you in the store as

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Speaker 1: long as possible. This new idea of you're a very

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Speaker 1: busy person and you don't want to spend your whole time,

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Speaker 1: the whole day in a Walmart, so you should be

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Speaker 1: able to pick it up as you drive home. That's

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Speaker 1: a new idea, but that's not technology. Coincidentally, we're having

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Speaker 1: this conversation the day after a New York Times column

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Speaker 1: front page New York Times column came out discussing some

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Speaker 1: of your work, amongst other things, how Amazon has affected

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Speaker 1: retail and how retailers have finally began to learn from

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Speaker 1: their experiences with Amazon. How far along in that process

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Speaker 1: are we that retailers are finally waking up and saying, hey,

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Speaker 1: we better do this and this, or Amazon is gonna

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Speaker 1: eat our launch. Yeah, I mean, I think they're seeing

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Speaker 1: the retail apocalypse. People are talking about that. If you

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Speaker 1: don't understand these two basic principles, the principle of customer

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Speaker 1: value and the principle of differential advantage, you're not going

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Speaker 1: to succeed radio shack, circuit city borders. You know, it's

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Speaker 1: soon Sears and Khmard who knows. But these retailers that

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Speaker 1: are not really up to snoff on customer experience, they

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Speaker 1: just can't make it in a world that has an

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Speaker 1: Amazon in it. Sears, I think that has to be

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Speaker 1: inevitable going that way. The local Sears and New where

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Speaker 1: I grew up has been there forever and finally it's

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Speaker 1: succumb And yet how are shops like best Buy and

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Speaker 1: Target seemingly thriving. Target just announced their best quarter. I

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Speaker 1: think in something like there was a game. What is

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Speaker 1: the drivers of the successful companies like best Buy, Target,

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Speaker 1: and Home Deeple and Lows for that matter, versus the

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Speaker 1: sears and the circuit city targets are very interesting example

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Speaker 1: because it shows the importance of stores and this quote

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Speaker 1: unquote omni channel experience. So one of the things they've

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Speaker 1: done that's very successful is opened up the small urban stores.

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Speaker 1: So they used to have these big boxes in suburbia

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Speaker 1: and rural markets, right, but now they have these small

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Speaker 1: urban stores where singles are, young people are living in

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Speaker 1: the city's more. They also opened them close to campuses,

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Speaker 1: and they're getting a lot of people who like to

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Speaker 1: have the physical store experience. They've been They've been tinkering

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Speaker 1: with their product assortment. They've come up with a lot

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Speaker 1: new store brands. They're trying to get the cachet of

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Speaker 1: tar J back, you know, that design kind of idea

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Speaker 1: of fun shopping, and it seems to be working. They've

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Speaker 1: been doing a lot of things. The biggest thing is

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Speaker 1: changing that store having a different assortment and it requires

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Speaker 1: rethinking your assortment when the store gets smaller. And then

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Speaker 1: these ideas of curbside pick up and making shopping easier

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Speaker 1: and making shopping fun. So how do firms differentiate on brands? Well,

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Speaker 1: you know, the luxury brands are still doing very well.

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Speaker 1: So you're looking at Louis Vatan air Mas, those those

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Speaker 1: are really doing very well. They're staying off of Amazon,

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Speaker 1: but they understand the importance of online. Also, they're partnering

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Speaker 1: with things like far Fetched or Netta Porte, which are

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Speaker 1: some kinds of online marketplaces that are dealing. But they

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Speaker 1: understand if they're going to charge those premium prices, they've

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Speaker 1: got to give superior product, pleasurable product, and a really

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Speaker 1: good customer experience. You have to feel pampered when you

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Speaker 1: buy luxury, so that's another piece of it. So what's

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Speaker 1: the flips? Are the everyday low prices the e d

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Speaker 1: LP How important is that is at a totally different

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Speaker 1: market segment or is there any overlap? Well, you know,

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Speaker 1: that's interesting thing because I think somebody might have a

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Speaker 1: Louis Vatan purse and then a Target T shirt. You

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Speaker 1: know that that's possible, but there's always going to be

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Speaker 1: a price sensitive segments. So Everyday low Price, the Walmart strategy,

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Speaker 1: Costco strategy, TJ Max, they're all doing very well, even

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Speaker 1: though the luxury brands are doing well too, because they're

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Speaker 1: going after being the best at something. So luxury is

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Speaker 1: the best at product, and everyday low price is the

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Speaker 1: lowest price. And it seems that it's a bit of

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Speaker 1: a barbell the middle where the middle class used to shop,

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Speaker 1: that's become a bit of a void. It's either high

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Speaker 1: end or lower right, Yeah, it's yeah, something special, And

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Speaker 1: that's what I mean by differential advantage. You've got to

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Speaker 1: be better. You can't just be good enough. You've got

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Speaker 1: to be better at something. Let's talk a little bit

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Speaker 1: about your academic career. What motivated you to write a

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Speaker 1: book on on the Shopping Revolution? Well, I mean for

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Speaker 1: the last seven years or six and a half years,

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Speaker 1: I was the director of the Baker Retailing Center at Wharton,

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Speaker 1: and the goal of that retailing center was actually to

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Speaker 1: convince Wharton students to go into retailing. Typically, the Wharton

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Speaker 1: students didn't go into retailing. They went into vestment banking

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Speaker 1: or hedge funds or consulting. But Jay Baker, who had

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Speaker 1: retired as the president of Coles, thought this was a

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Speaker 1: missed opportunity, and so he developed the center to encourage

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Speaker 1: people to think about retailing. And I was the director

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Speaker 1: of it, and so my goal was to really learn

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Speaker 1: as much as I could about retail and what the

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Speaker 1: excitement was, to try to convince our students to go

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Speaker 1: into the industry. At the time I was doing this,

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Speaker 1: retailing was changing radically. You know. We had all sorts,

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Speaker 1: not only Amazon, but these digitally native vertical brands started.

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Speaker 1: Those are the digitally native vertical brands of brands that

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Speaker 1: start online and they go direct to the end user.

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Speaker 1: Warby Parker was started for Wharton students, so that was

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Speaker 1: particularly sense, you know, something we were very proud of.

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Speaker 1: But there's also Casper that did it. More recent Mattress Company, Yeah,

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Speaker 1: the mattress company Bnobos which was subsequently bought by Walmart.

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Speaker 1: Um All Birds is a new one that's getting a

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Speaker 1: lot of your wearing over. But these are digitally native

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Speaker 1: vertical brands that are going out and this Nate this

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Speaker 1: We were trying to make retail sexy, but retail was

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Speaker 1: becoming sexy, you know. It was really the technology referenced

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Speaker 1: before really did change the way people think about retailing.

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Speaker 1: So so when a student graduates Wharton and goes into retail,

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Speaker 1: what aspect of this are they doing? There's it seems

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Speaker 1: there's a universe of things that makes sense and are

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Speaker 1: applicable in a modern technology world. Where do you see

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Speaker 1: them going into? Well, you know, Amazon right now, it's

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Speaker 1: big a hire of Warton students, as Goldman was really,

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Speaker 1: so you know, we're not talking warehouse workers. These are

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Speaker 1: people who knows what they're I think they're working for

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Speaker 1: AWS or whatever else. I don't know what they're were.

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Speaker 1: But Amazon is a huge company, right right, they'll eclipse

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Speaker 1: Walmart as the biggest employer if things continue, if you

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Speaker 1: extrapolate that to infinitely, which is never a good you know,

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Speaker 1: even some of our students are going to Walmart now,

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Speaker 1: which was you know, it was in the past. They

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Speaker 1: weren't so intrigued with going to Arkansas, you know, and

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Speaker 1: working in like you said, and operate actionally efficient company.

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Speaker 1: But now Walmart dot com is in San Francisco. Jet

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Speaker 1: dot Com isn't there, yea, So now it's a sexy, interesting,

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Speaker 1: fun place to work. So do you recall there was,

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Speaker 1: I want to say, a New York Times story. You

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Speaker 1: just made me think of this um where someone came

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Speaker 1: into Target to complain that their daughter was getting pregnancy

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Speaker 1: stuff in the mail. She's in high school? How dare you?

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Speaker 1: And then subsequently he had to go back and apologize

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Speaker 1: Targets Big data analytics figured out that if you buy this,

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Speaker 1: this and this, hey, you're probably pregnant and you're gonna

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Speaker 1: want this. Is that the sort of stuff that that

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Speaker 1: NBA students are doing. Yeah, that's one thing for sure.

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Speaker 1: The Wharton School, Ardine is advocating over and over and

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Speaker 1: over again data analytics, data analytics. You really can't go

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Speaker 1: into marketing anymore if you didn't understand customer analytics and

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Speaker 1: data analytics. You know in that story I remember when

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Speaker 1: it came out maybe five years ago. Was surprising, but

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Speaker 1: you know, you really didn't need data analytics to do that.

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Speaker 1: A smart salesperson could have watched this girl come into

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Speaker 1: the store via pregnancy test and by you know, vitamins

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Speaker 1: and prenatal vitamins or all these other things and what

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Speaker 1: it really wasn't rocket science to figure that out. So

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Speaker 1: given your vantage point, how has the curriculum for NBA

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Speaker 1: students changed relative to to this industry. Yeah, we've definitely

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Speaker 1: included more analytics in our marketing in everything um Adam

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Speaker 1: Grant is another professor at the Wharton School. He started

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Speaker 1: people analytics generals, yeah, or givers and takers and planed

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Speaker 1: B and M. He but he's really you know, all

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Speaker 1: of that stuff. It's even management, which maybe used to

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Speaker 1: think of management and marketing is quote unquote softer sciences,

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Speaker 1: were all using data analytics. Of course, finance has always

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Speaker 1: been dated heavily data driven. You'd be surprised that's a

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Speaker 1: relatively recent phenomenal. By relatively recent, it's a couple of decades.

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Speaker 1: It was not as endemic as you would suppose any

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Speaker 1: forty six years ago. That's interesting, quite fascinating stuff. Let's

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Speaker 1: talk a little bit about some of the older brands

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Speaker 1: who may not be quite as hip as um the

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Speaker 1: Warby Parker's or the old birds of the world. How

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Speaker 1: would you advise companies like Kellogg's or Coca Cola to

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Speaker 1: appeal to the next generation. You know, it's really interesting

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Speaker 1: to watch because I've been teaching marketing for a long time,

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Speaker 1: and we would teach branding, and we would talk about

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Speaker 1: what are the biggest brands forever the same biggest brands Coke, IBM, whatever, Toyota.

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Speaker 1: All of a sudden, the last five years, we all

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Speaker 1: know who the biggest brands are, right I mean, And

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Speaker 1: that's a change that happened very very quickly in the

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Speaker 1: last five years. And if you look at their stock prices, Kellogg's, Gillette,

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Speaker 1: they're hurting. The CpG companies are hurting, and they do

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Speaker 1: have to do something to wake up and smell the roses,

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Speaker 1: just like the retailers. So Gillette, for example, has you know,

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Speaker 1: started subscription services to compete with Dollar Shave Club and Harry's.

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Speaker 1: Coca Cola just bought a coffee company. Look what Nike

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Speaker 1: is doing. That's pretty interesting. So let's let's discuss that

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Speaker 1: because I was just reaching from my phone to grab

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Speaker 1: a data point that I wanted to ask you you're here.

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Speaker 1: The day after it was announced that Colin Kaepernick is

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Speaker 1: going to be UH, he received an extension of his

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Speaker 1: contract with Nike, and on the thirty year anniversary of

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Speaker 1: their launch of the Just Do It campaign, they made

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Speaker 1: um they made him part of that. And there seems

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Speaker 1: to be quite an interesting backlash. However, and and this

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Speaker 1: is what's so fascinating. A data point I read I

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Speaker 1: might have been the Journal of the Times specifically said

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Speaker 1: something like two thirds of Nike's customers are under thirty five.

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Speaker 1: So there, you know, Nike is not marketing to old, fat,

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Speaker 1: white conservative dudes. That's not their target demographic. Is it?

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Speaker 1: The people who are burning Nike socks and shoes? They

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Speaker 1: really don't care about that, do that? No? I mean,

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Speaker 1: I think that's the calculated decision they made. And they

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Speaker 1: had to do some things because they also had been

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Speaker 1: getting a lot of negative publicity on the women issue.

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Speaker 1: I mean, they support Serena and she's a fantastic role model,

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Speaker 1: but that's not that's not where the news is about

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Speaker 1: Nike and women. That the lawsuits and all these other things,

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Speaker 1: and that's been a news and Nike has to face that. Um.

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Speaker 1: And I think you asked me before about the difference

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Speaker 1: in millennials and baby boomers. One of the things I

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Speaker 1: see that's different is that millennial millennials seemed to hold

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Speaker 1: brands accountable, and so it's not just enough to brand

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Speaker 1: a product. You kind of have to take some positions.

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Speaker 1: You have to be responsible, and I think Nike, you know,

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Speaker 1: is taking that position. Now. They're standing up to social

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Speaker 1: issues that do concern their core market, and they took

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Speaker 1: a stand on it. Look what happened at Starbucks, you know,

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Speaker 1: one incidents in one Starbucks restaurant in Philadelphia caused an

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Speaker 1: incredible reaction around the world. That was something I was

427
00:24:07,320 --> 00:24:09,000
Speaker 1: talking to someone in You're a bit better than I said.

428
00:24:09,000 --> 00:24:11,520
Speaker 1: I don't suppose you heard about what happened in Philadelphia

429
00:24:11,600 --> 00:24:15,480
Speaker 1: with Starbucks and they had it was you know, it's

430
00:24:15,480 --> 00:24:19,159
Speaker 1: always amazing when you have such a diffuse company with

431
00:24:19,240 --> 00:24:22,560
Speaker 1: tens of thousands of stores, how hard that is to

432
00:24:23,640 --> 00:24:28,480
Speaker 1: um really get a consistent message in a consistent behavior

433
00:24:29,000 --> 00:24:33,640
Speaker 1: across tens of thousands of employees. It's uh, it's really

434
00:24:33,720 --> 00:24:37,080
Speaker 1: quite astonishing, all right. So here's the Times article. It's

435
00:24:37,080 --> 00:24:40,479
Speaker 1: not the journal. Nike returns to a familiar strategy with

436
00:24:40,640 --> 00:24:45,880
Speaker 1: the Kaepernack ad campaign. The Time suggested that Nike as

437
00:24:45,880 --> 00:24:49,520
Speaker 1: a brand has courted controversy. Charles Barkley, I'm not a

438
00:24:49,600 --> 00:24:52,680
Speaker 1: role model, Tiger Wood saying, Hey, some of these uh

439
00:24:52,880 --> 00:24:55,919
Speaker 1: golf courses wouldn't let me play because I'm an African

440
00:24:55,960 --> 00:25:00,919
Speaker 1: American years ago. So coming back to Colin Kaepernack, is

441
00:25:00,960 --> 00:25:05,640
Speaker 1: this just tacking into that controversy. Here's the data point

442
00:25:05,640 --> 00:25:08,480
Speaker 1: I wanted to find. Nearly two thirds of individuals who

443
00:25:08,480 --> 00:25:11,200
Speaker 1: wear Nike in the United States are under thirty five

444
00:25:11,280 --> 00:25:14,359
Speaker 1: years old. So so this wasn't a coincidence. This was

445
00:25:14,400 --> 00:25:16,760
Speaker 1: a very conscious Oh, they had to know that they

446
00:25:16,800 --> 00:25:18,560
Speaker 1: get I mean, Trump made it clear they were going

447
00:25:18,600 --> 00:25:21,600
Speaker 1: to get some backlash on this, and he, true to form,

448
00:25:21,720 --> 00:25:25,080
Speaker 1: responded um yesterday, though not as extremely as one might

449
00:25:25,119 --> 00:25:28,320
Speaker 1: have thought, but he did respond um. And and that

450
00:25:28,520 --> 00:25:31,840
Speaker 1: then the boycott Nike kind of hashtag boycott Nike, and

451
00:25:31,960 --> 00:25:34,719
Speaker 1: the crazy videos that are coming up with people burning

452
00:25:34,720 --> 00:25:37,800
Speaker 1: their expensive shoes, which is kind of silly because a,

453
00:25:38,000 --> 00:25:41,600
Speaker 1: you already gave them your money and be really shouldn't

454
00:25:41,640 --> 00:25:44,359
Speaker 1: if you really think it's a veterans issue, then donated

455
00:25:44,440 --> 00:25:47,080
Speaker 1: to Veterans group. By the way, yesterday, I'm doing this

456
00:25:47,119 --> 00:25:49,280
Speaker 1: from my memory, so I'm going to get the numbers wrong.

457
00:25:49,680 --> 00:25:52,639
Speaker 1: But it was something like Nike stock fell two point

458
00:25:53,320 --> 00:25:57,359
Speaker 1: seven percent, but Adiita stock felt two point It was

459
00:25:57,400 --> 00:26:00,639
Speaker 1: almost no difference that if their biggest rival felt the

460
00:26:00,680 --> 00:26:03,479
Speaker 1: same amount, it might have just been uh, you know,

461
00:26:03,520 --> 00:26:06,520
Speaker 1: the whole segment is going to suffer backlash for a

462
00:26:06,560 --> 00:26:09,479
Speaker 1: couple of days and then back to back to usual.

463
00:26:09,840 --> 00:26:12,200
Speaker 1: But when you take some of these positions, you're gonna

464
00:26:12,200 --> 00:26:16,439
Speaker 1: get polarization. And they must have calculated, um, you know,

465
00:26:16,600 --> 00:26:19,520
Speaker 1: we'll lose some but will gain loyalty in other markets,

466
00:26:19,640 --> 00:26:23,160
Speaker 1: and they thought it was worth it. So let's talk

467
00:26:23,160 --> 00:26:26,520
Speaker 1: a little bit about the paradox of luxury. You you

468
00:26:26,600 --> 00:26:30,920
Speaker 1: referenced it earlier. People have to either have some very

469
00:26:30,960 --> 00:26:36,920
Speaker 1: positive affiliation with the products, or the brands or the experience.

470
00:26:37,240 --> 00:26:40,000
Speaker 1: What is the paradox of luxury. Well, you know, usually

471
00:26:40,000 --> 00:26:42,639
Speaker 1: in economics, which I'm sure you know very well, supply

472
00:26:42,720 --> 00:26:45,480
Speaker 1: and demand says you lower price, make things more accessible

473
00:26:45,640 --> 00:26:48,200
Speaker 1: than your market share is going to go up. In luxury,

474
00:26:48,240 --> 00:26:51,400
Speaker 1: that's the paradox. If you lower brands too much, like

475
00:26:51,480 --> 00:26:54,320
Speaker 1: Michael Core's a lower price too much like Michael Cores

476
00:26:54,359 --> 00:26:57,800
Speaker 1: and Coach did inadvertently by having a lot of discounting

477
00:26:57,840 --> 00:27:00,040
Speaker 1: and selling a lot of their products and out, that

478
00:27:01,119 --> 00:27:03,720
Speaker 1: diminishes the value of the brand. So if the and

479
00:27:03,800 --> 00:27:06,520
Speaker 1: if you make it too accessible, it diminishes the value

480
00:27:06,560 --> 00:27:10,440
Speaker 1: of a luxury brand. Luxury is for elite luxury. Special

481
00:27:10,960 --> 00:27:14,040
Speaker 1: luxury is inaccessible. So when you make it a little

482
00:27:14,080 --> 00:27:17,480
Speaker 1: bit more affordable, of the notion of affordable luxuries almost

483
00:27:17,480 --> 00:27:22,080
Speaker 1: an oxymoron. That's the paradox of luxury doesn't follow the

484
00:27:22,160 --> 00:27:25,159
Speaker 1: regular rules of supply and so this goes back to

485
00:27:25,400 --> 00:27:28,000
Speaker 1: the old days of general motors when they would sell

486
00:27:28,119 --> 00:27:32,359
Speaker 1: essentially the same car. The high end was a Cadillac,

487
00:27:32,520 --> 00:27:35,000
Speaker 1: the middle was a Buick, and the cheap car was

488
00:27:35,040 --> 00:27:38,840
Speaker 1: a Chevy. They were all essentially rebadged and and up

489
00:27:39,480 --> 00:27:43,560
Speaker 1: um scaled versions of each other. Is that the concept? Yeah,

490
00:27:43,600 --> 00:27:45,920
Speaker 1: I mean, so maybe the guts of the car was similar,

491
00:27:46,000 --> 00:27:49,280
Speaker 1: but the trappings or that we're really different. And the

492
00:27:49,320 --> 00:27:52,040
Speaker 1: dealerships were dealing right, and the service was different, the

493
00:27:52,080 --> 00:27:54,840
Speaker 1: brand was different, that materials in the car might have

494
00:27:54,880 --> 00:27:57,440
Speaker 1: been different higher value. So there was I'm not saying

495
00:27:57,480 --> 00:27:59,879
Speaker 1: it was silly. I think there was value to what

496
00:28:00,119 --> 00:28:03,080
Speaker 1: going on. But that's the paradox of luxury, and part

497
00:28:03,080 --> 00:28:05,639
Speaker 1: of what makes it special. It is not everybody has it,

498
00:28:06,920 --> 00:28:13,240
Speaker 1: so it's the scarcity creates creates a specific value that

499
00:28:13,400 --> 00:28:17,680
Speaker 1: that's kind of that's kind of interesting. So within the

500
00:28:17,720 --> 00:28:21,400
Speaker 1: existing world of brands that are being disrupted. How can

501
00:28:21,440 --> 00:28:25,640
Speaker 1: they jiu jitsu this? How can the disrupted become the disruptive? Well,

502
00:28:25,680 --> 00:28:27,719
Speaker 1: that's interesting to think of. You know, you're seeing a

503
00:28:27,720 --> 00:28:30,480
Speaker 1: lot of pressure on these digitally native vertical brands. They're

504
00:28:30,520 --> 00:28:32,639
Speaker 1: they're considered some of the disruptors. A lot of what

505
00:28:32,760 --> 00:28:37,880
Speaker 1: they have done by going direct without all these intermediary channels,

506
00:28:37,960 --> 00:28:40,200
Speaker 1: they've been able to lower the price. And so a

507
00:28:40,240 --> 00:28:44,640
Speaker 1: Warby Parker is a very high designed glass, but it's glasses,

508
00:28:44,680 --> 00:28:47,920
Speaker 1: but it's sold at nine rather than a five hundred dollars.

509
00:28:48,760 --> 00:28:51,160
Speaker 1: So that's part of what the disruption is. It goes

510
00:28:51,200 --> 00:28:53,800
Speaker 1: back to that notion of your margin is my opportunity.

511
00:28:54,200 --> 00:28:57,239
Speaker 1: So I'm giving you what you really want, but I'm

512
00:28:57,360 --> 00:29:00,360
Speaker 1: charging a lower price. So that's one way that they've

513
00:29:00,400 --> 00:29:03,000
Speaker 1: been disrupting. And the other way the disruptions have been

514
00:29:03,080 --> 00:29:06,280
Speaker 1: is making it more convenient. Um. I suppose there's something

515
00:29:06,680 --> 00:29:09,400
Speaker 1: lurking out there that we haven't seen yet, but right

516
00:29:09,440 --> 00:29:13,080
Speaker 1: now that's what people are doing. Um. I can't imagine

517
00:29:13,080 --> 00:29:15,600
Speaker 1: what it will be. But maybe there's another dimension in

518
00:29:15,720 --> 00:29:18,520
Speaker 1: my matrix I haven't thought about yet. So so you

519
00:29:18,520 --> 00:29:21,680
Speaker 1: you said you can't imagine what what they'll do next.

520
00:29:22,600 --> 00:29:26,600
Speaker 1: How challenging is it to predict trends or even just

521
00:29:26,720 --> 00:29:30,800
Speaker 1: extrapolate trends. It seems that there's a new meme and

522
00:29:30,840 --> 00:29:35,280
Speaker 1: a hot new flavor every other day. Are these things

523
00:29:35,320 --> 00:29:39,640
Speaker 1: just passing fancies or is there really a bigger shift

524
00:29:39,680 --> 00:29:43,960
Speaker 1: taking place in a lack of consistency and brands over time?

525
00:29:44,000 --> 00:29:45,720
Speaker 1: I mean what I think what you're talking about is

526
00:29:45,760 --> 00:29:48,680
Speaker 1: the way retail changed over time and got people to

527
00:29:48,680 --> 00:29:52,880
Speaker 1: buy more, which was changed style, change trends. So in

528
00:29:52,920 --> 00:29:56,000
Speaker 1: the old days, heym's went up and down or colors arc,

529
00:29:56,160 --> 00:29:58,560
Speaker 1: wasn't it? That was what a long arc of time.

530
00:29:58,600 --> 00:30:01,640
Speaker 1: It didn't change see from day to day, would change

531
00:30:01,640 --> 00:30:03,840
Speaker 1: season and season to season, but it gave you a

532
00:30:03,840 --> 00:30:06,760
Speaker 1: reason to buy more. Same thing with electronics or innovations

533
00:30:06,840 --> 00:30:09,480
Speaker 1: or cars. The technology just got better and better, and

534
00:30:09,480 --> 00:30:11,880
Speaker 1: so you needed so that you do need to see

535
00:30:11,920 --> 00:30:14,200
Speaker 1: something new in order to get people to buy because

536
00:30:14,320 --> 00:30:16,640
Speaker 1: products just don't wear out that fast. You know, if

537
00:30:16,680 --> 00:30:18,840
Speaker 1: they wore out that then you'd have to replace. But

538
00:30:18,880 --> 00:30:21,280
Speaker 1: a lot of things don't, so you need fashion style,

539
00:30:21,640 --> 00:30:25,600
Speaker 1: new technology. What Amazon did and the digitally native vertical

540
00:30:25,680 --> 00:30:29,120
Speaker 1: brands did was I do think significant disruption which is

541
00:30:29,160 --> 00:30:32,440
Speaker 1: different than this changing in styles and trends. And they

542
00:30:32,520 --> 00:30:36,840
Speaker 1: realized that the whole model of retail had gotten stale um.

543
00:30:36,920 --> 00:30:39,400
Speaker 1: And that's when I went back to that salesforce commission

544
00:30:39,560 --> 00:30:41,840
Speaker 1: kind of idea, the idea that if you would go

545
00:30:41,880 --> 00:30:43,960
Speaker 1: into a department store and try to run away from

546
00:30:44,000 --> 00:30:47,000
Speaker 1: the perfume women, you know that we're going to surray you. Like,

547
00:30:47,080 --> 00:30:49,719
Speaker 1: what were they thinking, You know, they were thinking that

548
00:30:49,720 --> 00:30:52,040
Speaker 1: these are commissioned people who are going to do anything

549
00:30:52,080 --> 00:30:55,720
Speaker 1: to So let's talk about that. We we've been other

550
00:30:55,760 --> 00:30:59,040
Speaker 1: folks have been discussing the death of the mall for

551
00:30:59,280 --> 00:31:02,920
Speaker 1: years and years and years. Is that overblown or has

552
00:31:03,560 --> 00:31:07,920
Speaker 1: that sort of post war suburban shopping experience. Is that

553
00:31:08,040 --> 00:31:10,920
Speaker 1: also circling the draink Yeah? No, I think that that's

554
00:31:10,960 --> 00:31:13,600
Speaker 1: what's happened, Like it got stale. So we have way

555
00:31:13,640 --> 00:31:17,880
Speaker 1: too many stores in the US. We're over called, overstored, overbuilt,

556
00:31:18,920 --> 00:31:24,200
Speaker 1: like a substantial amount versus Japan and the UK even Yeah, right, substantial.

557
00:31:24,280 --> 00:31:26,840
Speaker 1: So even if you didn't see all this change, those

558
00:31:26,880 --> 00:31:28,400
Speaker 1: stores were gonna have to go out of business. We

559
00:31:28,520 --> 00:31:30,760
Speaker 1: had too many, and if you look at the malls

560
00:31:30,800 --> 00:31:32,360
Speaker 1: that are going out of business, they're called the B

561
00:31:32,520 --> 00:31:35,120
Speaker 1: and C malls. They were terrible malls. You know when

562
00:31:35,160 --> 00:31:38,360
Speaker 1: the Macy closed down is that as the destination. All

563
00:31:38,400 --> 00:31:40,120
Speaker 1: those stores in the middle had to go out. There

564
00:31:40,160 --> 00:31:43,000
Speaker 1: was no traffic. So that's what's going down. But just

565
00:31:43,240 --> 00:31:46,720
Speaker 1: as those stores malls are going down, some exciting, beautiful

566
00:31:46,840 --> 00:31:49,360
Speaker 1: new flagship malls are being built. Look what's happening in

567
00:31:49,440 --> 00:31:52,680
Speaker 1: New York City. There's some beautiful stores being built that

568
00:31:52,760 --> 00:31:55,200
Speaker 1: should attract a lot of traffic. Can you stick around

569
00:31:55,200 --> 00:31:57,080
Speaker 1: a little bit? I have a ton more questions. Okay,

570
00:31:57,640 --> 00:32:01,120
Speaker 1: we have been speaking to professor Barbara on she teaches

571
00:32:01,640 --> 00:32:05,640
Speaker 1: marketing at Wharton. If you enjoy this conversation, be sure

572
00:32:05,640 --> 00:32:08,400
Speaker 1: and come back for the podcast extras, where we keep

573
00:32:08,480 --> 00:32:12,400
Speaker 1: the tape rolling and continue discussing all things retail. You

574
00:32:12,480 --> 00:32:17,520
Speaker 1: can find that at iTunes, Overcast, SoundCloud, Stitcher, and Bloomberg

575
00:32:17,920 --> 00:32:21,600
Speaker 1: or wherever final podcasts are sold. We love your comments,

576
00:32:21,880 --> 00:32:26,440
Speaker 1: feedback and suggestions right to us at m IB podcast

577
00:32:26,560 --> 00:32:29,400
Speaker 1: at Bloomberg dot net. Check out my daily column on

578
00:32:29,480 --> 00:32:31,920
Speaker 1: Bloomberg dot com. You could follow me on Twitter at

579
00:32:32,000 --> 00:32:35,520
Speaker 1: rid Holts. I'm Barry Riholts. You're listening to Masters in

580
00:32:35,560 --> 00:32:52,840
Speaker 1: Business on Bloomberg Radio. Welcome to the podcast, Barbara, Thank

581
00:32:52,840 --> 00:32:55,440
Speaker 1: you so much for doing this. I find this subject

582
00:32:56,000 --> 00:33:00,320
Speaker 1: absolutely fascinating. And I have a bunch of of sans

583
00:33:00,360 --> 00:33:03,680
Speaker 1: too that we didn't get to. Um. But I have

584
00:33:03,840 --> 00:33:07,840
Speaker 1: to come back to the luxury as a scarce good um.

585
00:33:08,000 --> 00:33:10,160
Speaker 1: And I'll share a quick funny story with you. My

586
00:33:10,320 --> 00:33:13,520
Speaker 1: wife teaches fashion illustration and design, so when I get

587
00:33:13,640 --> 00:33:17,720
Speaker 1: dragged around to various stores, it's not so much retail

588
00:33:17,760 --> 00:33:22,240
Speaker 1: therapy as it is research and and where I am

589
00:33:22,560 --> 00:33:26,040
Speaker 1: the reckless, Oh that's nice, get one of those. Um.

590
00:33:27,240 --> 00:33:30,440
Speaker 1: She is the much more fiscally prudent of the two

591
00:33:30,520 --> 00:33:33,440
Speaker 1: of us. And one day we're I forgot where we were,

592
00:33:33,960 --> 00:33:39,040
Speaker 1: but she sees this product bag and it's ungodly expensive.

593
00:33:39,480 --> 00:33:41,600
Speaker 1: It's this leather fringe bag. I want to say, it

594
00:33:41,720 --> 00:33:46,160
Speaker 1: was like twelve or fourteen thousand, some insane insane number

595
00:33:46,480 --> 00:33:48,880
Speaker 1: that I gasped. I'm like, you know, you could buy

596
00:33:48,920 --> 00:33:51,960
Speaker 1: a small car for the cost of that that bay

597
00:33:52,640 --> 00:33:56,600
Speaker 1: and um, And speaking of cars, I troll around eBay

598
00:33:56,920 --> 00:34:00,239
Speaker 1: all the time looking at old cars to occasionally, um

599
00:34:00,320 --> 00:34:04,000
Speaker 1: tickle my fancy. And on a lark, I started searching

600
00:34:04,120 --> 00:34:08,640
Speaker 1: for that bag and one day there it is. It's

601
00:34:09,160 --> 00:34:12,440
Speaker 1: less than a thousand dollars. It's which to me is

602
00:34:12,480 --> 00:34:16,000
Speaker 1: still a ridiculous price for bags, but you walk into

603
00:34:16,080 --> 00:34:21,960
Speaker 1: the store and hundred is pretty typical. So for her birthday,

604
00:34:22,040 --> 00:34:27,399
Speaker 1: I surprised her with an eBay purchased product, ungodly expensive bag.

605
00:34:28,760 --> 00:34:31,719
Speaker 1: What does the used market due to luxury? And what

606
00:34:31,840 --> 00:34:34,520
Speaker 1: do things like you mentioned Netta Porta and some of

607
00:34:34,600 --> 00:34:38,720
Speaker 1: the Cpretta Porta, what is Netta Porte? And far fetch? Okay?

608
00:34:39,040 --> 00:34:43,719
Speaker 1: So they sell rents repurpose, well, they do both, some

609
00:34:43,840 --> 00:34:46,400
Speaker 1: of them on marketplaces. Some of them have their own inventories.

610
00:34:46,480 --> 00:34:49,000
Speaker 1: Some of them concatenate a lot of little stores on

611
00:34:49,120 --> 00:34:52,040
Speaker 1: their platform. They're different models there. But luxury is a

612
00:34:52,120 --> 00:34:55,120
Speaker 1: really interesting business. There's catches on it. One of them

613
00:34:55,200 --> 00:34:58,120
Speaker 1: is this whole counterfeit market. Oh for sure. That was

614
00:34:58,239 --> 00:35:01,120
Speaker 1: the concern with eBay. I actually had to write the

615
00:35:01,200 --> 00:35:03,799
Speaker 1: person and say, listen, I'm interested in this bag, how

616
00:35:03,840 --> 00:35:07,040
Speaker 1: do I know it's real? And they sent me a

617
00:35:07,200 --> 00:35:09,799
Speaker 1: thing back here. I've sold ten thousand items. I've been

618
00:35:09,800 --> 00:35:12,920
Speaker 1: on eBay for whatever a decade. I have all the

619
00:35:12,960 --> 00:35:17,480
Speaker 1: paperwork with this, and and so my wife's I I

620
00:35:18,360 --> 00:35:19,520
Speaker 1: When I gave it to her, I said, and make

621
00:35:19,560 --> 00:35:22,000
Speaker 1: sure this is real. And she looked at and she goes,

622
00:35:22,160 --> 00:35:25,680
Speaker 1: if this is fake, it's a fantastic alright. Was she happy?

623
00:35:26,480 --> 00:35:28,840
Speaker 1: Thrilled to death? Can I tell you? She at we

624
00:35:29,120 --> 00:35:32,439
Speaker 1: The reason I even remembered this is she just said

625
00:35:32,480 --> 00:35:34,680
Speaker 1: to me, well, falls coming up, and I'm excited about that.

626
00:35:34,760 --> 00:35:37,239
Speaker 1: And I'm like, why Jean sweater. She's like, no, I

627
00:35:37,320 --> 00:35:39,080
Speaker 1: get to take the product bag out of the closet.

628
00:35:39,160 --> 00:35:42,399
Speaker 1: It's it's a leather fringe bag, so it's her fall bag.

629
00:35:42,840 --> 00:35:44,880
Speaker 1: Very she's very excited about it. But that's a real

630
00:35:45,000 --> 00:35:48,080
Speaker 1: big problem. Like it's a big problem, particularly in China

631
00:35:48,200 --> 00:35:50,600
Speaker 1: where a lot of these things are manufactured, and some

632
00:35:50,719 --> 00:35:53,359
Speaker 1: of the luxury products would be the branded products would

633
00:35:53,360 --> 00:35:55,400
Speaker 1: be done during the day and after hours on the

634
00:35:55,520 --> 00:35:58,680
Speaker 1: same manufacturing, some of the counterfeits would be dead. So

635
00:35:58,800 --> 00:36:01,479
Speaker 1: what is the difference between counterfeits? So in that case,

636
00:36:01,640 --> 00:36:04,560
Speaker 1: the counterfeit and the real product was actually the product

637
00:36:04,719 --> 00:36:07,680
Speaker 1: was the same. The branch wasn't authorized, it wasn't didn't

638
00:36:07,719 --> 00:36:10,120
Speaker 1: have the paperwork, the certificates and things, so they were

639
00:36:10,200 --> 00:36:12,640
Speaker 1: bringing in they were using the same materials in some

640
00:36:12,920 --> 00:36:16,280
Speaker 1: now those counterfeits are expensive. There's different levels of counterfeits.

641
00:36:16,560 --> 00:36:20,360
Speaker 1: Want a good, counterfeits want cheap. The very best counterfeits

642
00:36:20,360 --> 00:36:23,120
Speaker 1: are actually quite good. Um. But you have to know

643
00:36:23,239 --> 00:36:24,800
Speaker 1: what you're doing. You have to have the eye to

644
00:36:24,880 --> 00:36:27,440
Speaker 1: see the difference. Is some of the counterfeits are terrible.

645
00:36:27,760 --> 00:36:30,800
Speaker 1: But that's a real There's been pressure now on Ali Baba,

646
00:36:31,000 --> 00:36:34,759
Speaker 1: on and on Amazon because they hadn't been policing whether

647
00:36:36,040 --> 00:36:39,640
Speaker 1: resellers and third parties sellers were selling real products or

648
00:36:39,680 --> 00:36:42,560
Speaker 1: counterfeits are all of that, and so luxury products never

649
00:36:42,640 --> 00:36:45,239
Speaker 1: wanted to go on those platforms unless they could be

650
00:36:45,320 --> 00:36:48,480
Speaker 1: assured that there were no counterfeits. So if you if

651
00:36:48,520 --> 00:36:52,160
Speaker 1: you go down to Chinatown, you could buy a nice

652
00:36:52,320 --> 00:36:55,239
Speaker 1: Rolex watch for about fifty bucks. The problem is it's

653
00:36:55,360 --> 00:36:59,440
Speaker 1: Rolex with two ls other Other than that, it's hard

654
00:36:59,520 --> 00:37:02,040
Speaker 1: to tell the difference. That some of the fakes are

655
00:37:02,200 --> 00:37:05,000
Speaker 1: pretty spectac Yeah. I mean in Rolex, I doubt it's

656
00:37:05,040 --> 00:37:08,719
Speaker 1: real gold if it's for sure, um. So, so that's

657
00:37:08,760 --> 00:37:12,799
Speaker 1: the issue with with um luxury. I it's really fascinating.

658
00:37:13,160 --> 00:37:16,239
Speaker 1: I know in China they've had fake Apple stores and

659
00:37:16,480 --> 00:37:19,600
Speaker 1: all sorts of stuff. What was has there been a

660
00:37:19,680 --> 00:37:22,279
Speaker 1: resolution with eBay or Amazon or is this still an

661
00:37:22,320 --> 00:37:25,000
Speaker 1: on way is ongoing, but I think that they are.

662
00:37:25,080 --> 00:37:27,840
Speaker 1: Amazon has now acknowledged that they're going to have to

663
00:37:27,880 --> 00:37:30,200
Speaker 1: control their counterfeit issue or they're not going to get

664
00:37:30,200 --> 00:37:32,759
Speaker 1: the luxury brands to come on. But you know, we're

665
00:37:32,800 --> 00:37:36,239
Speaker 1: talking about luxury. Was interesting this notion that accessibility makes

666
00:37:36,320 --> 00:37:40,360
Speaker 1: luxury less desirable because, as you said, scarcity or exclusivity

667
00:37:40,440 --> 00:37:43,480
Speaker 1: is what luxury is, and yet people still want to

668
00:37:43,520 --> 00:37:47,080
Speaker 1: buy online. Now online makes it more accessible, So that's

669
00:37:47,120 --> 00:37:50,279
Speaker 1: another paradox. Luxury had to figure out, how can I

670
00:37:50,520 --> 00:37:54,480
Speaker 1: have the luxury experience and still have the convenience of online.

671
00:37:54,840 --> 00:37:58,640
Speaker 1: And they've been doing all sorts of experimenting with how

672
00:37:58,719 --> 00:38:01,920
Speaker 1: to keep the convenience of online but keep the exclusivity

673
00:38:02,040 --> 00:38:05,880
Speaker 1: of luxury. So for example, they'll have specialized buyers or

674
00:38:05,960 --> 00:38:08,960
Speaker 1: personalized buyers where you can talk to them online and

675
00:38:09,080 --> 00:38:11,239
Speaker 1: do the business online, but it's still a one to

676
00:38:11,360 --> 00:38:14,800
Speaker 1: one luxury experience like a personal shop, personal shop or

677
00:38:14,920 --> 00:38:17,440
Speaker 1: something like that. And so they've been trying to do

678
00:38:17,680 --> 00:38:19,800
Speaker 1: things and then when they ship you the product, the

679
00:38:19,880 --> 00:38:22,560
Speaker 1: packaging is beautiful. You know, some of the luxury comes

680
00:38:22,600 --> 00:38:25,160
Speaker 1: in the packaging that goes around the product. Have you

681
00:38:25,360 --> 00:38:31,320
Speaker 1: been reading about these unboxing videos on YouTube? So I

682
00:38:31,480 --> 00:38:35,080
Speaker 1: just saw this this weekend. Apparently there's a little bit

683
00:38:35,200 --> 00:38:37,920
Speaker 1: of a dopamine hit if you watch a video of

684
00:38:38,040 --> 00:38:43,480
Speaker 1: someone unwrapping a delivery, whether it's an Amazon box or

685
00:38:43,520 --> 00:38:46,120
Speaker 1: something else, they unwrapid the unpacking and it's like right

686
00:38:46,120 --> 00:38:47,880
Speaker 1: now and off the shop. I've gone through that experience.

687
00:38:48,680 --> 00:38:51,560
Speaker 1: I don't know how much I really buy into that UM,

688
00:38:51,680 --> 00:38:55,280
Speaker 1: but it's fascinating. But what what I do recall reading

689
00:38:55,320 --> 00:39:00,520
Speaker 1: about UM earlier. Uh, to your point about the experience,

690
00:39:00,920 --> 00:39:04,440
Speaker 1: if you go into Tiffany's and for whatever reason, they

691
00:39:04,560 --> 00:39:08,200
Speaker 1: think you're a high roller type shopper, you get brought

692
00:39:08,280 --> 00:39:11,120
Speaker 1: up into the special, secret private room that the public

693
00:39:11,200 --> 00:39:14,640
Speaker 1: doesn't get to see, and it's apparently a very different

694
00:39:14,800 --> 00:39:18,800
Speaker 1: and much more expensive experience. Tiffany's is an interesting example.

695
00:39:18,840 --> 00:39:21,239
Speaker 1: They're coming back up. Tiffany some people say is the

696
00:39:21,320 --> 00:39:24,520
Speaker 1: only true American luxury brand. It started and I think

697
00:39:26,200 --> 00:39:29,040
Speaker 1: the same year Airmez started, so it's been around for

698
00:39:29,200 --> 00:39:31,719
Speaker 1: long enough. Luxury really has to have history, it has

699
00:39:31,760 --> 00:39:34,080
Speaker 1: to have legacy to be a real luxury brand, and

700
00:39:34,120 --> 00:39:37,800
Speaker 1: Tiffany's really the only American brand that can claim that credit.

701
00:39:38,320 --> 00:39:40,839
Speaker 1: But they kind of lost their way maybe thirty years

702
00:39:40,880 --> 00:39:43,160
Speaker 1: ago when they had too much silver in their store

703
00:39:43,480 --> 00:39:46,839
Speaker 1: and they had all these young adolescent teenage girls coming

704
00:39:46,920 --> 00:39:50,080
Speaker 1: into the store right next to these very rich people

705
00:39:50,160 --> 00:39:52,840
Speaker 1: buying diamonds in private rooms, and that was not a

706
00:39:52,920 --> 00:39:57,200
Speaker 1: good juxtamosition. Yeah, that's what should have been online, the silver. Yeah, right,

707
00:39:57,480 --> 00:39:59,520
Speaker 1: so now they have they still sell some silver, but

708
00:39:59,600 --> 00:40:02,400
Speaker 1: it's a a small part of it. And they've really

709
00:40:02,560 --> 00:40:06,400
Speaker 1: tried to re up the luxury vision of Tiffany's. Make it.

710
00:40:06,640 --> 00:40:08,759
Speaker 1: You know what Audrey Hepburn saw in it. Nothing can

711
00:40:08,840 --> 00:40:11,560
Speaker 1: go bad in the Tiffany's store, you know. So that's

712
00:40:11,560 --> 00:40:15,680
Speaker 1: an interesting point that Tiffany's might be the only luxury store.

713
00:40:16,280 --> 00:40:19,200
Speaker 1: I'm thinking of things like Ralph Lauren. But they make

714
00:40:19,280 --> 00:40:23,120
Speaker 1: everything from the low end to the Purple label, which

715
00:40:23,200 --> 00:40:26,400
Speaker 1: is crazy expensive, um and whatever you can find a

716
00:40:26,480 --> 00:40:29,400
Speaker 1: name and Marcus. But I assume half that stuff is

717
00:40:29,480 --> 00:40:33,280
Speaker 1: coming from Europe. So the traditional luxury brands are French

718
00:40:33,360 --> 00:40:35,760
Speaker 1: and Italian. You know, that's where you made in Italy.

719
00:40:36,040 --> 00:40:38,200
Speaker 1: You know, Gucci's off the charts right now. Gucci is

720
00:40:38,239 --> 00:40:42,480
Speaker 1: crazy doing crazy well, Louis buiton MS. Those are French brands,

721
00:40:42,560 --> 00:40:47,000
Speaker 1: you know, some of those um But Ralph Lauren had

722
00:40:47,080 --> 00:40:49,759
Speaker 1: this what I call a branded house strategy, which is

723
00:40:49,840 --> 00:40:53,640
Speaker 1: what you described under the same brand name from Purple

724
00:40:53,760 --> 00:40:56,279
Speaker 1: Label or Collection all the way down to outlet. You

725
00:40:56,320 --> 00:40:59,279
Speaker 1: could tell it was all Ralph or Paolo. Whereas the

726
00:40:59,360 --> 00:41:02,719
Speaker 1: luxury houses in Europe a house of brands, and each

727
00:41:02,800 --> 00:41:06,000
Speaker 1: house is a special brand. They don't have one brand

728
00:41:06,120 --> 00:41:08,840
Speaker 1: name over all of their different offerings. So when you

729
00:41:08,920 --> 00:41:11,640
Speaker 1: look at Coach, which I recall back in the day,

730
00:41:11,680 --> 00:41:14,640
Speaker 1: at one point Coach was pretty high end. I don't

731
00:41:14,640 --> 00:41:17,360
Speaker 1: know if that's the case. We were talking about Professor

732
00:41:17,440 --> 00:41:19,960
Speaker 1: Scott Galloway, an n y U Stern. He's made the

733
00:41:20,040 --> 00:41:23,960
Speaker 1: claim that Apple is the first technology luxury brands. I

734
00:41:24,080 --> 00:41:26,960
Speaker 1: agree that you do. It's kind of when you look

735
00:41:27,000 --> 00:41:30,799
Speaker 1: at their prices, they're certainly premium, and they're counterfeited also,

736
00:41:30,960 --> 00:41:33,680
Speaker 1: just the way luxury is, which almost a badge of

737
00:41:33,760 --> 00:41:37,200
Speaker 1: honor to be counterfeited. You know, nobody is counterfeiting Android,

738
00:41:38,520 --> 00:41:41,480
Speaker 1: so so, but you know Coach that you mentioned that

739
00:41:41,800 --> 00:41:44,440
Speaker 1: was an American brand, but they're now starting to copy

740
00:41:44,560 --> 00:41:47,440
Speaker 1: the European strategy. So they changed their name to the

741
00:41:47,480 --> 00:41:51,240
Speaker 1: holding company Tapestry, and now they have a house of brands,

742
00:41:51,280 --> 00:41:54,120
Speaker 1: So they have Coach, they have Stuart white Smith, they

743
00:41:54,200 --> 00:41:58,080
Speaker 1: have Kate Spade, all under the house Tapestry, and so

744
00:41:58,200 --> 00:42:00,880
Speaker 1: they're moving and they're trying to take back the too

745
00:42:00,960 --> 00:42:04,320
Speaker 1: much outlet selling and trying to resurrect the grandeur that

746
00:42:04,440 --> 00:42:06,560
Speaker 1: Coach used to have. And they're doing well. Their stock

747
00:42:06,640 --> 00:42:09,359
Speaker 1: prices went up, their their sales are going up. They're

748
00:42:09,400 --> 00:42:12,560
Speaker 1: doing very well with that strategy. My wife taught me

749
00:42:12,960 --> 00:42:17,000
Speaker 1: a shocking data point way back when the stuff you've

750
00:42:17,000 --> 00:42:19,760
Speaker 1: seen in the outlet centers, that's not the same stuff

751
00:42:19,800 --> 00:42:22,799
Speaker 1: that you can get in the stores, although occasionally there

752
00:42:22,880 --> 00:42:26,440
Speaker 1: are um leftovers and end runs and they do get

753
00:42:26,520 --> 00:42:30,560
Speaker 1: dumped there, but a lot of stores specifically manufacturer for

754
00:42:30,719 --> 00:42:34,160
Speaker 1: the outlet right, which that was what Coach did wrong. See,

755
00:42:34,239 --> 00:42:36,640
Speaker 1: but your wife said, is the right strategy. You want

756
00:42:36,680 --> 00:42:38,560
Speaker 1: to you have to keep it separate because why would

757
00:42:38,560 --> 00:42:40,960
Speaker 1: anybody pay full price if you get the same product

758
00:42:41,040 --> 00:42:43,560
Speaker 1: in an outlet. But Coach had some of the same

759
00:42:43,600 --> 00:42:46,560
Speaker 1: product in their outlets, and what that did was under

760
00:42:46,840 --> 00:42:49,000
Speaker 1: undermine the value of the brand. If you're paying a

761
00:42:49,120 --> 00:42:51,520
Speaker 1: high price, and someone else got the same product, the

762
00:42:51,640 --> 00:42:54,880
Speaker 1: exact same product, at an outlet price. Why would you

763
00:42:54,960 --> 00:42:57,120
Speaker 1: want to pay the higher price? And and and Coach

764
00:42:57,239 --> 00:42:59,320
Speaker 1: was hurt by that, so let me push back on that.

765
00:43:00,160 --> 00:43:04,200
Speaker 1: I notice I'm wearing Brooks Brothers. Is probably the wrong example.

766
00:43:04,280 --> 00:43:06,840
Speaker 1: This is a Brooks brother shirt. But I noticed that

767
00:43:06,960 --> 00:43:11,080
Speaker 1: a lot of products, the same exact products are sold

768
00:43:11,880 --> 00:43:14,600
Speaker 1: at multiple times at different prices. So I could walk

769
00:43:14,640 --> 00:43:17,800
Speaker 1: into a Lord and Taylor. So we're recording this in September.

770
00:43:18,160 --> 00:43:19,920
Speaker 1: All the new full stuff has already been out for

771
00:43:20,000 --> 00:43:23,200
Speaker 1: a month. If I want shopping last month for full stuff,

772
00:43:23,719 --> 00:43:26,520
Speaker 1: it's full price, it's not discount that, it's not coupons,

773
00:43:26,880 --> 00:43:29,640
Speaker 1: it's not on sale. And then by the time I

774
00:43:29,680 --> 00:43:33,279
Speaker 1: don't know, November rolls around, the coupons start, and then

775
00:43:33,320 --> 00:43:36,080
Speaker 1: as we get closer to Christmas, the big discount start,

776
00:43:36,360 --> 00:43:38,480
Speaker 1: and then by the time we hit January, the same

777
00:43:38,560 --> 00:43:41,080
Speaker 1: product you could pay buy a shirt for a hundred

778
00:43:41,080 --> 00:43:45,200
Speaker 1: and twenty five dollars sixty dollars. Now, you may not

779
00:43:45,320 --> 00:43:47,360
Speaker 1: get the right color, you may not get the right size,

780
00:43:47,400 --> 00:43:49,719
Speaker 1: you may not get exactly what you want. But if

781
00:43:49,760 --> 00:43:52,160
Speaker 1: your price sensitive, there seems to be a range. You

782
00:43:52,239 --> 00:43:56,080
Speaker 1: can buy the same product across six months at all

783
00:43:56,160 --> 00:43:59,480
Speaker 1: these crazy different price points. That is that a purposeful strategy.

784
00:43:59,640 --> 00:44:02,359
Speaker 1: When started, it made sense, you know, because you would

785
00:44:02,560 --> 00:44:04,960
Speaker 1: target people at different willingness to pay, and so you

786
00:44:05,000 --> 00:44:06,680
Speaker 1: get the people are willing to pay at the beginning

787
00:44:06,719 --> 00:44:09,239
Speaker 1: of season to pay high. People who couldn't afford it

788
00:44:09,400 --> 00:44:11,279
Speaker 1: or didn't want to would wait till the end of

789
00:44:11,320 --> 00:44:14,839
Speaker 1: season and pay low. Unfortunately, people got addicted to those

790
00:44:14,880 --> 00:44:18,719
Speaker 1: price promotions. They could predict those pressure promotions, and consequently

791
00:44:18,800 --> 00:44:21,480
Speaker 1: they were very reluctant to pay full price, and it

792
00:44:21,560 --> 00:44:24,360
Speaker 1: got really bad around holiday seasons where it's big, you know,

793
00:44:24,480 --> 00:44:27,160
Speaker 1: that's the big bonanza for retail, where it said if

794
00:44:27,200 --> 00:44:29,400
Speaker 1: you waited long enough, you know you're going to get

795
00:44:29,440 --> 00:44:32,040
Speaker 1: the discount or Black Friday and all these other things.

796
00:44:32,280 --> 00:44:35,719
Speaker 1: People got addicted to the discounts and that was very bad.

797
00:44:35,960 --> 00:44:38,359
Speaker 1: Undermine the value of the branded It is what hurt

798
00:44:38,440 --> 00:44:40,879
Speaker 1: Michael Cores for a while. Michael course has pulled back

799
00:44:40,960 --> 00:44:43,000
Speaker 1: on that so they can be seen as more luxury

800
00:44:43,080 --> 00:44:45,800
Speaker 1: now um And part of the reason for it was

801
00:44:45,880 --> 00:44:49,480
Speaker 1: the price sensitivity or price discrimination. Another reason was if

802
00:44:49,520 --> 00:44:52,520
Speaker 1: they didn't forecast demand correctly. And it's hard to forecast

803
00:44:52,560 --> 00:44:55,239
Speaker 1: demand for a fashion product because you don't know what

804
00:44:55,360 --> 00:44:57,600
Speaker 1: the consumers are gonna like or not like, So you

805
00:44:57,840 --> 00:45:00,920
Speaker 1: over order certain things and then you've got extra inventory

806
00:45:01,000 --> 00:45:02,920
Speaker 1: that you've got a discount at the end of the season.

807
00:45:03,080 --> 00:45:06,560
Speaker 1: And you're doing that years in advance. It's not like

808
00:45:06,719 --> 00:45:11,000
Speaker 1: thirteen months in advance typically crazy. So that's now that's changed.

809
00:45:11,200 --> 00:45:13,359
Speaker 1: And this is another thing that's not just Amazon has

810
00:45:13,360 --> 00:45:16,200
Speaker 1: done that. Zarah has changed this a lot. Zarah has changed.

811
00:45:16,239 --> 00:45:19,640
Speaker 1: They do like not a lot of turnovers in the store.

812
00:45:19,680 --> 00:45:22,200
Speaker 1: They don't have this eighteen month lead time or anything

813
00:45:22,239 --> 00:45:24,759
Speaker 1: like that, and there's all this pressure. The part of

814
00:45:24,800 --> 00:45:28,320
Speaker 1: the disruption is to give customers a better experience, so

815
00:45:28,480 --> 00:45:31,400
Speaker 1: they have to be better at forecasting demand. They have

816
00:45:31,640 --> 00:45:33,640
Speaker 1: to get the right product in the store so they

817
00:45:33,680 --> 00:45:36,800
Speaker 1: don't have leftover inventory at the end. Because what the

818
00:45:36,960 --> 00:45:39,839
Speaker 1: process you described, you could see, you know, long term,

819
00:45:39,880 --> 00:45:42,360
Speaker 1: it's not gonna work. People understand it that, you know,

820
00:45:42,480 --> 00:45:44,560
Speaker 1: everybody knows that happens. Why wouldn't they wait for the

821
00:45:44,640 --> 00:45:49,239
Speaker 1: discount price, especially given I would make an argument that

822
00:45:49,800 --> 00:45:51,600
Speaker 1: there hasn't been a whole lot of wage growth in

823
00:45:51,680 --> 00:45:54,440
Speaker 1: the real wage growth after inflation from the middle class

824
00:45:54,800 --> 00:45:57,360
Speaker 1: over the past twenty or thirty years. That has to

825
00:45:57,440 --> 00:46:00,479
Speaker 1: have an impact on the selling strategies of retailers. Yeah,

826
00:46:01,760 --> 00:46:03,759
Speaker 1: I agree, but that's what you're saying, Like with all

827
00:46:03,880 --> 00:46:06,080
Speaker 1: with Macy's and stuff, when you talk about whether their

828
00:46:06,160 --> 00:46:09,480
Speaker 1: new strategy they're announcing, one of them is much more

829
00:46:09,560 --> 00:46:13,840
Speaker 1: meticulous forecasting a product assortment, having a better idea before

830
00:46:13,920 --> 00:46:16,040
Speaker 1: you put you know, excess inventory in the store. And

831
00:46:16,160 --> 00:46:18,600
Speaker 1: is that just big data? I mean, I would imagine

832
00:46:18,960 --> 00:46:21,279
Speaker 1: that if they they don't just get to turn a

833
00:46:21,360 --> 00:46:24,360
Speaker 1: dial and say, okay, now we're better forecasters. Couldn't they

834
00:46:24,400 --> 00:46:26,919
Speaker 1: have been a better forecaster five or ten years ago.

835
00:46:27,560 --> 00:46:31,520
Speaker 1: Computer technology has improved, but not so much over a decade.

836
00:46:32,080 --> 00:46:36,200
Speaker 1: That is it the algorithms? Is it just? It's also

837
00:46:36,360 --> 00:46:39,080
Speaker 1: the changing the system so you can see what sells

838
00:46:39,120 --> 00:46:42,680
Speaker 1: and reproducing faster, you know that business intelligence that well,

839
00:46:42,760 --> 00:46:46,200
Speaker 1: that's the data, but also the operations like don't order things,

840
00:46:46,320 --> 00:46:49,399
Speaker 1: see what's selling and then order it um rather than

841
00:46:49,880 --> 00:46:51,920
Speaker 1: and the other thing that Zara did. They also were

842
00:46:51,960 --> 00:46:55,160
Speaker 1: customer focused, where the design luxury houses a product focus.

843
00:46:55,400 --> 00:46:58,520
Speaker 1: So the luxury housers say, I'm the designer, this is

844
00:46:58,600 --> 00:47:01,759
Speaker 1: what you like, Zara says, is I'm gonna look and

845
00:47:01,840 --> 00:47:04,279
Speaker 1: see what the customers like, and then I'm gonna put

846
00:47:04,320 --> 00:47:07,200
Speaker 1: what the fashionista is like in my store. So they

847
00:47:07,360 --> 00:47:10,200
Speaker 1: have their sales associates at the end of every single

848
00:47:10,320 --> 00:47:14,360
Speaker 1: day report back to headquarters what they've observed, their customers

849
00:47:14,400 --> 00:47:17,759
Speaker 1: are coming and wearing, what they've observed their customers asked for,

850
00:47:18,320 --> 00:47:21,160
Speaker 1: and they use that customer data in addition to what

851
00:47:21,320 --> 00:47:24,320
Speaker 1: the fashion houses are doing to try to better predict

852
00:47:24,400 --> 00:47:26,640
Speaker 1: what customers are gonna like or what they're not gonna like.

853
00:47:26,920 --> 00:47:30,040
Speaker 1: How unique is that what Zara is, Well, Zara was

854
00:47:30,080 --> 00:47:31,680
Speaker 1: one of the first ones to do it, and then

855
00:47:31,800 --> 00:47:33,799
Speaker 1: they do a very good job and they're doing very

856
00:47:33,920 --> 00:47:36,279
Speaker 1: very well. But again this gets back to like this

857
00:47:36,360 --> 00:47:39,160
Speaker 1: shouldn't have been rocket science, that you should that you

858
00:47:39,200 --> 00:47:41,759
Speaker 1: should ask the customers what they actually like before you

859
00:47:41,920 --> 00:47:45,000
Speaker 1: just load up on inventory in your store, you know,

860
00:47:45,160 --> 00:47:47,920
Speaker 1: But that just didn't happen until recently. But what about

861
00:47:48,480 --> 00:47:50,520
Speaker 1: I'm no, I'm gonna mangle this term. What about the

862
00:47:50,840 --> 00:47:55,120
Speaker 1: knockoffs and the fast fashion? How significant is that too? Well,

863
00:47:55,200 --> 00:47:58,160
Speaker 1: I mean, Zara sometimes called called fast fashion, but it's

864
00:47:58,160 --> 00:48:01,239
Speaker 1: a higher, a little bit higher price point fashion. But

865
00:48:01,360 --> 00:48:03,760
Speaker 1: that is the idea instead of, like you said, waiting

866
00:48:03,800 --> 00:48:06,799
Speaker 1: the eighteen months for luxury to come in, let's get

867
00:48:06,920 --> 00:48:08,920
Speaker 1: people now want to buy in season. That's a very

868
00:48:09,000 --> 00:48:11,640
Speaker 1: big difference in season. Yeah, so like if it's fall,

869
00:48:11,680 --> 00:48:14,200
Speaker 1: I want to buy fall now? Where they the luxury

870
00:48:14,239 --> 00:48:17,400
Speaker 1: houses were treating teaching you to buy fall? You know

871
00:48:17,800 --> 00:48:20,000
Speaker 1: before it was right? Who wants to go shopping in

872
00:48:20,120 --> 00:48:22,959
Speaker 1: July and August for a winter coat? It makes no sense?

873
00:48:23,239 --> 00:48:25,719
Speaker 1: Can see what I mean? It's like that should have

874
00:48:25,800 --> 00:48:28,480
Speaker 1: been obvious to people, but they looked at it from

875
00:48:28,520 --> 00:48:31,600
Speaker 1: the product and operations side. I mean, obviously there was

876
00:48:31,640 --> 00:48:34,600
Speaker 1: a logic to doing it. Getting You have to manufacturer,

877
00:48:34,760 --> 00:48:36,400
Speaker 1: you have to get the supply, you have to do

878
00:48:36,560 --> 00:48:38,319
Speaker 1: all these things. It took a long time to get

879
00:48:38,360 --> 00:48:41,680
Speaker 1: the product to the store. But guess what, Zara figured

880
00:48:41,680 --> 00:48:43,040
Speaker 1: out how to do it in a way that took

881
00:48:43,080 --> 00:48:46,480
Speaker 1: a lot less time. I will admit to once so

882
00:48:47,080 --> 00:48:50,279
Speaker 1: I had this disan ski coat for years and I

883
00:48:50,360 --> 00:48:52,480
Speaker 1: made the mistake of buying a light colored coat, which

884
00:48:52,560 --> 00:48:54,040
Speaker 1: is a terrible idea in New York City, it just

885
00:48:54,120 --> 00:48:57,640
Speaker 1: gets filthy. And I tried on this black and sort

886
00:48:57,680 --> 00:49:02,480
Speaker 1: of neon yellow one and Dessaunt is an exorbitant French

887
00:49:02,680 --> 00:49:06,080
Speaker 1: luxury brand or wherever it comes from, and I couldn't

888
00:49:06,120 --> 00:49:08,960
Speaker 1: pull the trigger on it was too expensive. That September,

889
00:49:09,080 --> 00:49:11,719
Speaker 1: I just happened to stop into a ski shop that

890
00:49:11,840 --> 00:49:15,799
Speaker 1: at a giant preseason sale and literally found the same

891
00:49:15,840 --> 00:49:19,520
Speaker 1: exact code for thirty off for a third of what

892
00:49:19,640 --> 00:49:22,280
Speaker 1: I would have paid last year. And I couldn't couldn't

893
00:49:22,280 --> 00:49:26,800
Speaker 1: resist that. But that said, really, how how did we

894
00:49:26,960 --> 00:49:30,200
Speaker 1: ever get trained to buy winter clothes in August? It

895
00:49:30,280 --> 00:49:33,120
Speaker 1: doesn't make any sense now, and that now that customers

896
00:49:33,160 --> 00:49:35,879
Speaker 1: pushing back, that's again what the millennials are doing. One

897
00:49:35,960 --> 00:49:39,200
Speaker 1: of our young designers, Rebecca Minkoff, which is she's considered

898
00:49:39,239 --> 00:49:41,880
Speaker 1: a millennial designer. She was one of the ones on

899
00:49:42,080 --> 00:49:44,480
Speaker 1: that New York Fashion Week saying, you know, I'm going

900
00:49:44,560 --> 00:49:47,600
Speaker 1: to start showing during fashion week what people want to

901
00:49:47,640 --> 00:49:51,880
Speaker 1: buy now? Um, and that was considered revolution right, It

902
00:49:52,040 --> 00:49:55,279
Speaker 1: makes it makes so much sense. What else is you

903
00:49:55,480 --> 00:49:57,200
Speaker 1: have a bird's eye view of what's going on in

904
00:49:57,440 --> 00:50:00,800
Speaker 1: in retail and fashion and related areas. What do you

905
00:50:00,880 --> 00:50:04,160
Speaker 1: think is really interesting? What is something that you're kind

906
00:50:04,200 --> 00:50:06,080
Speaker 1: of intrigued about these days. Well, one of the things

907
00:50:06,160 --> 00:50:08,680
Speaker 1: I think is interesting is how important in store tech is.

908
00:50:09,080 --> 00:50:11,960
Speaker 1: I think that, yeah, you know, like the beacons in there,

909
00:50:12,120 --> 00:50:17,040
Speaker 1: or the smart boards and the magic mirrors mirror mentioned

910
00:50:17,120 --> 00:50:19,520
Speaker 1: Rebecca Minkoff, she does that in her own stores. If

911
00:50:19,560 --> 00:50:21,799
Speaker 1: you go to the Soho store, you'll see it, which

912
00:50:21,880 --> 00:50:24,280
Speaker 1: is where all the items in the store are coated

913
00:50:24,320 --> 00:50:26,520
Speaker 1: with r F I D code And when you walk

914
00:50:26,640 --> 00:50:29,279
Speaker 1: into the dressing room, on the mirror in front of you,

915
00:50:29,680 --> 00:50:32,640
Speaker 1: they show the items you're bringing into the kids in

916
00:50:32,719 --> 00:50:34,880
Speaker 1: the dressing room. It's right there on the mirror. And

917
00:50:34,960 --> 00:50:36,879
Speaker 1: then if you want a different size, you can push

918
00:50:36,960 --> 00:50:40,399
Speaker 1: on the mirror and the sales different size. They'll also

919
00:50:40,480 --> 00:50:42,440
Speaker 1: give you suggestions. If you bring in a you know,

920
00:50:42,520 --> 00:50:44,840
Speaker 1: a pencil black skirt, they'll say this blousse will go

921
00:50:44,960 --> 00:50:46,680
Speaker 1: with it, this person go with it. All of that

922
00:50:46,800 --> 00:50:49,560
Speaker 1: makes me perfect sense. How has no one ever thought about? Now?

923
00:50:49,680 --> 00:50:52,120
Speaker 1: The thing about that that's interesting is it makes perfect

924
00:50:52,160 --> 00:50:56,719
Speaker 1: sense and apparently has increased sales. You know, it is expensive,

925
00:50:56,760 --> 00:51:00,319
Speaker 1: but apparently the upsale up cell has worked very well

926
00:51:00,400 --> 00:51:04,560
Speaker 1: on that. But more importantly is collecting the data online.

927
00:51:04,800 --> 00:51:07,239
Speaker 1: If you go online and you put something into your

928
00:51:07,320 --> 00:51:09,520
Speaker 1: car and you don't buy it, you know, you get

929
00:51:09,560 --> 00:51:12,240
Speaker 1: all these ads for the next two months, right, because

930
00:51:12,280 --> 00:51:14,080
Speaker 1: they figure if you went all the way through what's

931
00:51:14,120 --> 00:51:17,080
Speaker 1: called the purchase funnel to put something in your car,

932
00:51:17,520 --> 00:51:19,600
Speaker 1: you must have really liked it and maybe we can

933
00:51:19,680 --> 00:51:22,480
Speaker 1: get the price tweaked right, or maybe and we'll get

934
00:51:22,520 --> 00:51:24,480
Speaker 1: you to buy. So they'd spent a lot of time

935
00:51:24,560 --> 00:51:28,560
Speaker 1: on that last miles. So to speak up the car. Well,

936
00:51:28,680 --> 00:51:31,680
Speaker 1: in the physical store, if you went to the trouble

937
00:51:31,960 --> 00:51:35,040
Speaker 1: of bringing something into the dressing room, you must have

938
00:51:35,160 --> 00:51:37,879
Speaker 1: liked it. And then if you didn't buy it, why

939
00:51:38,040 --> 00:51:40,280
Speaker 1: did you not buy it? What was wrong with those items?

940
00:51:40,600 --> 00:51:43,879
Speaker 1: That data was never collected in a physical store. Now

941
00:51:44,080 --> 00:51:46,600
Speaker 1: that we're taking this into the dressing room, I can

942
00:51:46,760 --> 00:51:49,520
Speaker 1: see what you bring into the dressing room and what

943
00:51:49,680 --> 00:51:52,640
Speaker 1: you purchase or what you don't purchase, and that's very

944
00:51:52,760 --> 00:51:55,640
Speaker 1: useful information. So now you're capturing all the data that

945
00:51:55,880 --> 00:52:00,080
Speaker 1: you previously were to disadvantage versus online retailers. Right. How

946
00:52:00,160 --> 00:52:01,480
Speaker 1: you can do that in this and what are they

947
00:52:01,520 --> 00:52:04,759
Speaker 1: actually using that data for? Is it productive for them? Yeah?

948
00:52:04,800 --> 00:52:07,000
Speaker 1: You can figure out like why is this item not selling?

949
00:52:07,040 --> 00:52:09,720
Speaker 1: Maybe it's not sized right, maybe it's too much money

950
00:52:09,800 --> 00:52:12,440
Speaker 1: for this. You know, you can figure out reasons why

951
00:52:12,520 --> 00:52:15,000
Speaker 1: people are choosing not to sell. I mean, so one

952
00:52:15,080 --> 00:52:16,880
Speaker 1: of the things that things aren't making it into the

953
00:52:16,960 --> 00:52:19,200
Speaker 1: dressing room. Maybe they don't look good on the rack,

954
00:52:19,360 --> 00:52:21,440
Speaker 1: maybe they're in the wrong place in the store. All

955
00:52:21,480 --> 00:52:24,520
Speaker 1: of a sudden, you can fine tune your merchandise to

956
00:52:25,320 --> 00:52:29,040
Speaker 1: be what customers want. You're getting customer input right there

957
00:52:29,120 --> 00:52:31,480
Speaker 1: at the store, which they didn't used to get that.

958
00:52:31,760 --> 00:52:34,560
Speaker 1: That's quite fascinating. So I know I only have you

959
00:52:34,680 --> 00:52:38,400
Speaker 1: for a finite amount of time. Let's jump to my

960
00:52:38,520 --> 00:52:42,960
Speaker 1: favorite questions that I ask all of my guests. Tell

961
00:52:43,080 --> 00:52:46,480
Speaker 1: us the most important thing that your students don't know

962
00:52:46,600 --> 00:52:50,080
Speaker 1: about you. Well, I don't know if my students, but

963
00:52:50,200 --> 00:52:52,279
Speaker 1: one of the things that's happened recently to me is

964
00:52:52,400 --> 00:52:56,960
Speaker 1: that I can't drive over bridges anymore. Really, I'm scared

965
00:52:57,040 --> 00:52:59,440
Speaker 1: of driving over bridges. This is what happened in Italy,

966
00:52:59,680 --> 00:53:02,439
Speaker 1: or just it seems crazy to me to drive over

967
00:53:02,520 --> 00:53:05,040
Speaker 1: a bridge. I don't know. I can walk over bridges,

968
00:53:05,120 --> 00:53:07,520
Speaker 1: but I don't like to drive over bridges, and as

969
00:53:07,560 --> 00:53:10,600
Speaker 1: a result, it's limited how much i'd drive. Now. Really,

970
00:53:10,840 --> 00:53:17,400
Speaker 1: that's not you're okay with tunnels, I'm okay with you.

971
00:53:17,840 --> 00:53:20,080
Speaker 1: I will tell you that as a kid driving over

972
00:53:20,160 --> 00:53:25,080
Speaker 1: the Williamsburg Bridge in the outer roadway, where it was

973
00:53:25,239 --> 00:53:29,680
Speaker 1: just this sort of metal um framework, like a mesh framework,

974
00:53:29,719 --> 00:53:31,600
Speaker 1: where you can look down through the road at the water,

975
00:53:31,960 --> 00:53:34,480
Speaker 1: and I made this horrible humming sound on the tires.

976
00:53:35,000 --> 00:53:38,840
Speaker 1: I was never thrilled with that particular bridge. It's funny.

977
00:53:38,880 --> 00:53:41,839
Speaker 1: I can be a passenger in a car driving over bridge.

978
00:53:41,840 --> 00:53:43,600
Speaker 1: I just don't want to drive it myself. I don't

979
00:53:43,600 --> 00:53:45,480
Speaker 1: trust myself, even though I don't know what I could do.

980
00:53:46,040 --> 00:53:48,400
Speaker 1: I'm afraid i'd freak out. But you know, if you

981
00:53:48,520 --> 00:53:50,040
Speaker 1: have to have that fear now, I didn't have it

982
00:53:50,080 --> 00:53:51,680
Speaker 1: when I was younger, I haven't now. If you have

983
00:53:51,760 --> 00:53:56,680
Speaker 1: to have it now in the land of uber and driving, okay,

984
00:53:56,760 --> 00:53:59,120
Speaker 1: it's not as as it could be. Who who are

985
00:53:59,160 --> 00:54:02,440
Speaker 1: your early mentors, who guarded your career in academia and

986
00:54:02,560 --> 00:54:05,280
Speaker 1: who led you into the world of marketing and retail.

987
00:54:05,480 --> 00:54:07,840
Speaker 1: Well you know, um, if you're a doctoral student and

988
00:54:07,880 --> 00:54:09,960
Speaker 1: you get a PhD, which I did a lot of times,

989
00:54:10,080 --> 00:54:13,080
Speaker 1: your your dissertation advisor is a big mentor, and my

990
00:54:13,400 --> 00:54:17,000
Speaker 1: dissertation I got my PhD at Columbia and my dissertation

991
00:54:17,080 --> 00:54:20,759
Speaker 1: advisor was Don Morrison, who just recently retired UM. And

992
00:54:20,960 --> 00:54:24,000
Speaker 1: he was he called himself a full service advisor. He

993
00:54:24,080 --> 00:54:27,640
Speaker 1: advised everything in my academic life and my personal life,

994
00:54:27,680 --> 00:54:30,680
Speaker 1: so he made a really big difference. More recently, I

995
00:54:30,920 --> 00:54:33,040
Speaker 1: UM left Wharton for a few years to go down

996
00:54:33,080 --> 00:54:35,000
Speaker 1: to University of Miami to be the dean of the

997
00:54:35,040 --> 00:54:38,160
Speaker 1: Business school there. And when I was there, Donna Leela

998
00:54:38,360 --> 00:54:41,680
Speaker 1: was the president of Miami. Um Clinton administration. Yeah, she

999
00:54:41,840 --> 00:54:44,600
Speaker 1: was the Secretary of Health and Human Services under Clinton

1000
00:54:44,719 --> 00:54:47,839
Speaker 1: for the longest serving Health and Human Services, and then

1001
00:54:47,960 --> 00:54:49,920
Speaker 1: she was also had a big career in academia. She

1002
00:54:50,040 --> 00:54:53,000
Speaker 1: was president of Hunter College and she was president University

1003
00:54:53,000 --> 00:54:57,080
Speaker 1: of Miami. More recently, she headed the Clinton Foundation when

1004
00:54:57,160 --> 00:55:00,279
Speaker 1: Hillary was running, which was kind of an interesting least

1005
00:55:00,280 --> 00:55:03,319
Speaker 1: to be I would imagine. And now she went back

1006
00:55:03,400 --> 00:55:06,400
Speaker 1: to Miami and she just won the Democratic seat for

1007
00:55:06,560 --> 00:55:10,040
Speaker 1: a congress for you know, the counsel. Yeah, so she

1008
00:55:10,400 --> 00:55:13,480
Speaker 1: was very ray. Very recently, she won the Democratic primary

1009
00:55:13,640 --> 00:55:15,840
Speaker 1: for that seat, which I think was held by a

1010
00:55:15,880 --> 00:55:18,560
Speaker 1: Republican but so hopefully she can still win it. And

1011
00:55:18,680 --> 00:55:21,760
Speaker 1: she's seventy seven, and I gotta say she's an amazing

1012
00:55:21,880 --> 00:55:23,960
Speaker 1: role model. She really taught me what it was like

1013
00:55:24,080 --> 00:55:25,840
Speaker 1: to be a leader. Taught me, you know, how to

1014
00:55:25,960 --> 00:55:29,400
Speaker 1: face adversary, adversity, you know, to figure out what you

1015
00:55:29,400 --> 00:55:32,759
Speaker 1: should do. She taught me the importance of low hanging fruit,

1016
00:55:32,960 --> 00:55:36,480
Speaker 1: visible signs, and long term strategy. She was really amazing.

1017
00:55:37,040 --> 00:55:39,000
Speaker 1: I had no idea she had she was running or

1018
00:55:39,080 --> 00:55:41,279
Speaker 1: had won that. And just last night I think it

1019
00:55:41,360 --> 00:55:45,920
Speaker 1: was Massachusetts. Um there was a woman challenger to the

1020
00:55:46,120 --> 00:55:52,719
Speaker 1: sitting Democrat uh in the House, and she beat him.

1021
00:55:52,760 --> 00:55:56,319
Speaker 1: And there's no Republican running against them. This year very

1022
00:55:56,400 --> 00:55:59,560
Speaker 1: much looks like the year of the woman, a giant,

1023
00:56:00,040 --> 00:56:04,000
Speaker 1: giant shift. It's quite fascinating, Donna La, that's really interesting.

1024
00:56:04,360 --> 00:56:07,520
Speaker 1: Um So tell us about the retailers who influence the

1025
00:56:07,560 --> 00:56:11,000
Speaker 1: way you look at the world of retail. Well, you know,

1026
00:56:11,160 --> 00:56:12,560
Speaker 1: that was one of the things I tried to do

1027
00:56:12,640 --> 00:56:15,400
Speaker 1: in my book, also to look at who's winning, and

1028
00:56:15,880 --> 00:56:18,040
Speaker 1: and that's what I focused on. Who's losing I wasn't

1029
00:56:18,080 --> 00:56:20,680
Speaker 1: as interested in. And so the retailers I think are

1030
00:56:20,719 --> 00:56:22,799
Speaker 1: doing a great job. Of course, at Amazon, I'm really

1031
00:56:22,840 --> 00:56:26,640
Speaker 1: impressed with Walmart, Costco is a very interesting reach. They've

1032
00:56:26,640 --> 00:56:30,040
Speaker 1: been a them and BJS have both been doing really well.

1033
00:56:30,160 --> 00:56:33,160
Speaker 1: And there's a data point I saw that said of

1034
00:56:33,239 --> 00:56:38,560
Speaker 1: Costco members are Amazon Prime, which means they're holding two memberships. Um.

1035
00:56:38,719 --> 00:56:42,160
Speaker 1: And that means and Amazon sells the same things Costco sells.

1036
00:56:42,200 --> 00:56:45,799
Speaker 1: So Costco is doing something right. Get the Giant if

1037
00:56:45,880 --> 00:56:48,720
Speaker 1: you have like five kids and you want those giant

1038
00:56:49,280 --> 00:56:52,000
Speaker 1: like I personally don't need two gallons of salsa, But

1039
00:56:52,640 --> 00:56:54,839
Speaker 1: if you walk into a Costco when you want those

1040
00:56:54,960 --> 00:56:59,279
Speaker 1: giant packages, I love the idea. Yeah, business is like it,

1041
00:56:59,440 --> 00:57:01,640
Speaker 1: but it's all so. You know, they sell gas, so

1042
00:57:01,760 --> 00:57:03,840
Speaker 1: you have to drive there anyway. They have the in

1043
00:57:04,040 --> 00:57:06,680
Speaker 1: store sampling. There's a bit of a treasure hunt feeling

1044
00:57:06,760 --> 00:57:10,000
Speaker 1: in Costco. So the point is that there's something they're

1045
00:57:10,040 --> 00:57:13,320
Speaker 1: doing right in the physical store to make people have

1046
00:57:13,520 --> 00:57:16,520
Speaker 1: two memberships. That's I'm really impressed with them. I visited

1047
00:57:16,600 --> 00:57:19,160
Speaker 1: Costco in Seattle and I just loved that. I love

1048
00:57:19,240 --> 00:57:21,960
Speaker 1: their philosophy, I love the way they think. You mentioned

1049
00:57:22,040 --> 00:57:27,720
Speaker 1: Mickey Drexler and the Gap previously. Um, any of the retailers, Starbucks,

1050
00:57:27,800 --> 00:57:31,520
Speaker 1: anybody else come to mind. As as doing anything innovative. Well,

1051
00:57:31,800 --> 00:57:35,720
Speaker 1: obviously Starbucks invented customer experience, you know, they the third

1052
00:57:35,800 --> 00:57:37,800
Speaker 1: Place and all of that stuff. I can't tell you

1053
00:57:37,880 --> 00:57:40,160
Speaker 1: how many Harvard cases are written a bad start, really,

1054
00:57:40,320 --> 00:57:43,360
Speaker 1: you know. Yeah, so that whole idea when they described

1055
00:57:43,440 --> 00:57:46,880
Speaker 1: experience is different than than the way Amazon I'm described it,

1056
00:57:46,960 --> 00:57:49,680
Speaker 1: but they understood that also, so that I also like

1057
00:57:49,840 --> 00:57:52,840
Speaker 1: t J Max and Burlington give the notion of the

1058
00:57:53,120 --> 00:57:56,080
Speaker 1: treasure hunt in those stores, um, and how they keep

1059
00:57:56,160 --> 00:58:00,360
Speaker 1: the prices way down and still understand scarcity and exclusive civity.

1060
00:58:00,480 --> 00:58:02,760
Speaker 1: You know, that's kind of interesting. You don't want to

1061
00:58:02,800 --> 00:58:04,919
Speaker 1: go into a store and see twenty different of these

1062
00:58:05,480 --> 00:58:07,520
Speaker 1: A dresses on a special price. You want to find

1063
00:58:07,600 --> 00:58:10,880
Speaker 1: one that's just for you. You know, that's an interesting idea.

1064
00:58:11,480 --> 00:58:14,400
Speaker 1: So let's talk about books. This is everybody's favorite question.

1065
00:58:14,520 --> 00:58:18,120
Speaker 1: Tell us about some of your favorite books, be they fiction, nonfiction,

1066
00:58:18,840 --> 00:58:21,280
Speaker 1: retail related, or not. You know, I was an English

1067
00:58:21,360 --> 00:58:24,240
Speaker 1: lit major, so I read lots of fiction for a

1068
00:58:24,320 --> 00:58:27,240
Speaker 1: really long time, and my best my favorite books would

1069
00:58:27,240 --> 00:58:29,920
Speaker 1: be the classics or some of the best selling fiction.

1070
00:58:30,240 --> 00:58:33,560
Speaker 1: But most recently I have been reading more nonfiction, so

1071
00:58:33,720 --> 00:58:37,000
Speaker 1: I really like, um, you know, Malcolm Gladwell, Michael Lewis.

1072
00:58:37,040 --> 00:58:40,480
Speaker 1: I also like to read female comedians. So I like

1073
00:58:40,680 --> 00:58:43,680
Speaker 1: Sarah Silverman and I like Tina Facebook. I like. I

1074
00:58:43,760 --> 00:58:46,480
Speaker 1: read both of those and they're both very amusing. Yeah,

1075
00:58:46,520 --> 00:58:49,040
Speaker 1: they're very amusing and I like their take. So the

1076
00:58:49,120 --> 00:58:52,680
Speaker 1: Sarah Silverman's book was The Bed or something like that

1077
00:58:53,400 --> 00:58:58,920
Speaker 1: and ums Pants. Yeah, yeah, they were both um absolutely.

1078
00:58:59,160 --> 00:59:03,280
Speaker 1: Uh any other female comedian books you would recommend, because

1079
00:59:03,360 --> 00:59:04,800
Speaker 1: those are the only two I have. Those are the

1080
00:59:04,920 --> 00:59:06,720
Speaker 1: two ones I read. I don't. I have to read

1081
00:59:06,800 --> 00:59:09,840
Speaker 1: so much academic stuff that it's sometimes hard to read books.

1082
00:59:10,000 --> 00:59:13,560
Speaker 1: So what what has you excited about retail today? What

1083
00:59:13,640 --> 00:59:16,600
Speaker 1: do you really jazzed about. Well, one of the things

1084
00:59:16,680 --> 00:59:19,160
Speaker 1: I'm starting to do, I'm thinking of developing, working with

1085
00:59:19,240 --> 00:59:22,280
Speaker 1: a partner to develop a new course on visual marketing

1086
00:59:22,680 --> 00:59:25,280
Speaker 1: and visual markets. So what we can learn by eye

1087
00:59:25,360 --> 00:59:28,560
Speaker 1: tracking and what people are attracted to the website or

1088
00:59:28,600 --> 00:59:31,000
Speaker 1: in a physical stuff. You can wear goggles and see

1089
00:59:31,000 --> 00:59:32,880
Speaker 1: what people look at the store, you can see what

1090
00:59:32,960 --> 00:59:36,520
Speaker 1: they look at online. We start to see what's automatic

1091
00:59:36,640 --> 00:59:39,040
Speaker 1: reaction to visual You know, you said your wife as

1092
00:59:39,080 --> 00:59:42,040
Speaker 1: a designer, it's kind of interesting to see what people

1093
00:59:42,080 --> 00:59:45,200
Speaker 1: are struck by how they scan a product. So this

1094
00:59:45,400 --> 00:59:48,280
Speaker 1: new neural marketing idea, the idea of new ways to

1095
00:59:48,320 --> 00:59:50,880
Speaker 1: collect data, new ways to get in people's heads or

1096
00:59:50,960 --> 00:59:54,120
Speaker 1: to see what they automatically and can't tell you they appreciate.

1097
00:59:54,520 --> 00:59:57,320
Speaker 1: When you start to care about what customers want in retail,

1098
00:59:57,720 --> 01:00:00,680
Speaker 1: these different ways of measuring it is pretty exciting. Uh

1099
01:00:01,080 --> 01:00:04,480
Speaker 1: that that that's quite interesting. Um, what do you think

1100
01:00:04,600 --> 01:00:06,640
Speaker 1: is the most significant change we're going to see in

1101
01:00:06,720 --> 01:00:09,560
Speaker 1: retail over the next couple of years. I think we're

1102
01:00:09,560 --> 01:00:12,240
Speaker 1: going to continue to see retailers that just don't cut

1103
01:00:12,320 --> 01:00:14,920
Speaker 1: it go out of business. And I think that's okay,

1104
01:00:15,040 --> 01:00:18,080
Speaker 1: you know, And I think Amazon is gonna keep pushing.

1105
01:00:18,400 --> 01:00:21,400
Speaker 1: They're gonna They're gonna go into other businesses that I'm

1106
01:00:21,480 --> 01:00:23,640
Speaker 1: really interested to see what happens. They're talking about the

1107
01:00:23,720 --> 01:00:27,360
Speaker 1: retailization of healthcare, talk about the situation that is so

1108
01:00:27,520 --> 01:00:31,040
Speaker 1: non customer focused healthcare. I mean, you can't get worse

1109
01:00:31,120 --> 01:00:36,480
Speaker 1: service than in healthcare, you know, cable is probably so.

1110
01:00:36,680 --> 01:00:38,800
Speaker 1: I think you're gonna see changes in all of that.

1111
01:00:39,280 --> 01:00:42,800
Speaker 1: And the idea that this retail model has legs that

1112
01:00:42,960 --> 01:00:45,400
Speaker 1: it should appuied to lots of different ways of thinking.

1113
01:00:45,760 --> 01:00:48,520
Speaker 1: I think that we're going to see big changes there.

1114
01:00:48,960 --> 01:00:52,600
Speaker 1: You know, as I mentioned earlier, I am a car guy.

1115
01:00:53,360 --> 01:00:57,480
Speaker 1: The car shopping experience is horrific. Any chance we're ever

1116
01:00:57,520 --> 01:01:00,480
Speaker 1: going to see that improved tesla see SEMs to be

1117
01:01:00,600 --> 01:01:03,800
Speaker 1: making some headway. Yeah, he's an interesting guy, Wharton grad.

1118
01:01:04,560 --> 01:01:07,520
Speaker 1: Oh is he under to say the least? He's an

1119
01:01:07,560 --> 01:01:12,000
Speaker 1: interesting guy. Of all the retail experiences there is, there

1120
01:01:12,200 --> 01:01:15,320
Speaker 1: is none more entrenched in the past than going out

1121
01:01:15,360 --> 01:01:16,840
Speaker 1: and trying to shop for a call. Oh my god,

1122
01:01:16,880 --> 01:01:19,480
Speaker 1: I can't stand it. I just so, why has nobody

1123
01:01:19,560 --> 01:01:21,800
Speaker 1: disrupted that yet? Well, some people have tried to do it.

1124
01:01:21,880 --> 01:01:24,480
Speaker 1: I guess some people like the game of that. I

1125
01:01:24,520 --> 01:01:28,600
Speaker 1: don't know very you know, it's it should be disrupted

1126
01:01:28,640 --> 01:01:30,640
Speaker 1: them that That's what you're looking for, Things that are

1127
01:01:30,760 --> 01:01:33,720
Speaker 1: not pleasant, that people don't want to do. Somebody's going

1128
01:01:33,760 --> 01:01:36,040
Speaker 1: to come in and do it, right you You Wharton

1129
01:01:36,120 --> 01:01:39,520
Speaker 1: students get busy on that. Um, so, tell us about

1130
01:01:39,600 --> 01:01:44,120
Speaker 1: a time you failed and what you learned from the experience. Well, uh,

1131
01:01:44,600 --> 01:01:46,320
Speaker 1: you know, there's a couple of times. They're difficult to

1132
01:01:46,400 --> 01:01:50,720
Speaker 1: talk about. So, but what characterized the times and several

1133
01:01:50,760 --> 01:01:53,919
Speaker 1: points during my life that I failed where something came

1134
01:01:53,920 --> 01:01:55,880
Speaker 1: as a surprise to me. That's what I would say.

1135
01:01:56,640 --> 01:01:59,000
Speaker 1: It's it's a function of mine not being a very

1136
01:01:59,040 --> 01:02:01,960
Speaker 1: good self monitor And what I mean by that is

1137
01:02:02,360 --> 01:02:04,360
Speaker 1: I think I have a lot of empathy, and I

1138
01:02:04,400 --> 01:02:06,240
Speaker 1: can see what's going on and I look around. I

1139
01:02:06,320 --> 01:02:09,439
Speaker 1: see a lot. I can feel people's emotional reactions and think.

1140
01:02:09,760 --> 01:02:13,040
Speaker 1: But what I am not good at is understanding how

1141
01:02:13,160 --> 01:02:16,520
Speaker 1: I come off to other people. So that's called self monitoring.

1142
01:02:16,640 --> 01:02:20,200
Speaker 1: I don't anticipate maybe if I get angry, how people

1143
01:02:20,240 --> 01:02:23,760
Speaker 1: will what people will feel about that, or if i'm

1144
01:02:24,120 --> 01:02:26,280
Speaker 1: you know, short, tempt you know, or say something very

1145
01:02:26,400 --> 01:02:29,000
Speaker 1: in a quick way. I don't appreciate that, and that's

1146
01:02:29,040 --> 01:02:32,400
Speaker 1: gotten me into trouble to not like understand. It's not

1147
01:02:32,760 --> 01:02:35,680
Speaker 1: just what I see, but it's how people see me

1148
01:02:37,040 --> 01:02:40,560
Speaker 1: that that that's intriguing. I will plead guilty to that

1149
01:02:40,680 --> 01:02:43,760
Speaker 1: as well. Um, what do you do for fun when

1150
01:02:43,760 --> 01:02:45,480
Speaker 1: you're not in the classroom? What what do you do

1151
01:02:45,640 --> 01:02:49,040
Speaker 1: to to kick back and relax? You know? The more

1152
01:02:49,320 --> 01:02:51,800
Speaker 1: the older I get, it's interesting for this, The more

1153
01:02:51,880 --> 01:02:56,560
Speaker 1: important I find running, working out, being outdoors walking. I

1154
01:02:56,640 --> 01:02:59,440
Speaker 1: could spend when I was younger, long times at a desk. Now,

1155
01:02:59,560 --> 01:03:03,000
Speaker 1: if I do that crazy, I just can't stand it.

1156
01:03:03,440 --> 01:03:05,560
Speaker 1: That's why I'm glad I teach, because you walk around

1157
01:03:05,600 --> 01:03:08,960
Speaker 1: the classroom. But I really like the outdoors. I like running.

1158
01:03:09,040 --> 01:03:12,520
Speaker 1: I like working out. So you have a fitbit and

1159
01:03:12,720 --> 01:03:15,000
Speaker 1: an Apple Watch on the same hand, at least I

1160
01:03:15,080 --> 01:03:18,120
Speaker 1: have things on two different hands. Why bo I like

1161
01:03:18,560 --> 01:03:20,480
Speaker 1: I like when I'm working out to monitor, you know,

1162
01:03:20,560 --> 01:03:23,840
Speaker 1: self quantify, so they measure different things. So I have

1163
01:03:23,960 --> 01:03:27,120
Speaker 1: social networks that are connected in different ways. I compete

1164
01:03:27,160 --> 01:03:29,120
Speaker 1: on all of this stuff. I love it. I love

1165
01:03:29,200 --> 01:03:31,520
Speaker 1: to see how my heart rate was today, how well

1166
01:03:31,600 --> 01:03:34,400
Speaker 1: I slept. All of that stuff. My wife wears it

1167
01:03:34,560 --> 01:03:37,560
Speaker 1: when she sleeps. I hate having something on my wrist

1168
01:03:37,600 --> 01:03:41,480
Speaker 1: while I'm sleeping. It's a distraction. Um So is it

1169
01:03:41,560 --> 01:03:45,280
Speaker 1: an accurate monitor of your sleep? Pause? Oh? Apparently you know.

1170
01:03:45,440 --> 01:03:47,680
Speaker 1: I guess I take it. It works for me. So

1171
01:03:47,840 --> 01:03:51,080
Speaker 1: you work with millennials and young people. If someone were

1172
01:03:51,120 --> 01:03:52,840
Speaker 1: to come to you and say they were interested in

1173
01:03:52,960 --> 01:03:57,360
Speaker 1: exploring career in marketing or digital brands or retail, what

1174
01:03:57,520 --> 01:03:59,760
Speaker 1: sort of advice would you give them. Well, one of

1175
01:03:59,800 --> 01:04:02,120
Speaker 1: the thing, you know, when I was the dean of Miami,

1176
01:04:02,280 --> 01:04:04,640
Speaker 1: I talked to a lot of successful deans, always talked

1177
01:04:04,640 --> 01:04:07,640
Speaker 1: the successful alums, and I asked around, like what advice

1178
01:04:07,680 --> 01:04:10,840
Speaker 1: would you give students? And from talking to all those people,

1179
01:04:10,920 --> 01:04:13,320
Speaker 1: I came up with three things that they said really

1180
01:04:13,360 --> 01:04:15,680
Speaker 1: made a difference. The first one and they seem obvious,

1181
01:04:15,760 --> 01:04:18,440
Speaker 1: but sometimes people don't know this. The first thing is

1182
01:04:18,800 --> 01:04:22,720
Speaker 1: work hard. You know, don't take it for granted. You're

1183
01:04:22,760 --> 01:04:25,120
Speaker 1: given a job, a job that maybe you like, work

1184
01:04:25,200 --> 01:04:28,240
Speaker 1: hard at it. The second one is be nice to people.

1185
01:04:28,400 --> 01:04:31,560
Speaker 1: Be nice to everyone. You know, from the receptionist all

1186
01:04:31,600 --> 01:04:34,720
Speaker 1: the way down up to the CEO. Pay attention because

1187
01:04:35,080 --> 01:04:37,920
Speaker 1: people watch that behavior, and you know, going back to

1188
01:04:38,000 --> 01:04:41,320
Speaker 1: this notion of self monitoring, understand how you come off

1189
01:04:41,400 --> 01:04:43,960
Speaker 1: to all these other people, and that matters. And the

1190
01:04:44,120 --> 01:04:46,400
Speaker 1: third piece of advice that people said over and over

1191
01:04:47,000 --> 01:04:49,800
Speaker 1: was don't just learn what you do. Learn what your

1192
01:04:49,840 --> 01:04:52,520
Speaker 1: people on both sides of you do also, so learn

1193
01:04:52,640 --> 01:04:54,800
Speaker 1: other skills. And then when you do that, you're in

1194
01:04:54,880 --> 01:04:57,760
Speaker 1: the right place at the right time for potential promotion.

1195
01:04:58,080 --> 01:05:01,400
Speaker 1: Because a lot of movement and firms are not so systematic.

1196
01:05:01,760 --> 01:05:04,320
Speaker 1: It really is an accident or somebody got hurt and

1197
01:05:04,400 --> 01:05:07,040
Speaker 1: someone needs to step in and do something. These things,

1198
01:05:07,120 --> 01:05:10,000
Speaker 1: these opportunities come up, and you know, they say luck

1199
01:05:10,160 --> 01:05:12,240
Speaker 1: is you know, hard work or however they say that

1200
01:05:12,400 --> 01:05:15,040
Speaker 1: you know something, someone's lucky, was working hard for that

1201
01:05:15,160 --> 01:05:19,600
Speaker 1: lucky opportunity, opportunity or something like that. Yeah, yeah, I'm

1202
01:05:19,640 --> 01:05:23,200
Speaker 1: angling it too, but it's that's the idea interesting and

1203
01:05:23,280 --> 01:05:26,160
Speaker 1: our final question, what is it that you know about

1204
01:05:26,200 --> 01:05:29,960
Speaker 1: the world of retail and marketing today that you wish

1205
01:05:30,040 --> 01:05:33,160
Speaker 1: you knew twenty plus years ago when you first started

1206
01:05:33,200 --> 01:05:35,080
Speaker 1: your career. You know, like I said, when I was

1207
01:05:35,120 --> 01:05:37,800
Speaker 1: writing this book, it was shocking to me that I

1208
01:05:37,920 --> 01:05:41,160
Speaker 1: have been teaching marketing for a hundred million years and

1209
01:05:41,320 --> 01:05:45,200
Speaker 1: we always achieved these principles of customer value, differential advantage,

1210
01:05:45,200 --> 01:05:47,960
Speaker 1: and the third one is selectivity and concentration, which has

1211
01:05:48,000 --> 01:05:51,360
Speaker 1: to do its segmentation. And that I did not realize

1212
01:05:51,600 --> 01:05:53,640
Speaker 1: until I sat down and wrote this book and thought

1213
01:05:53,680 --> 01:05:56,840
Speaker 1: about what Amazon did, that retail was not customer focused.

1214
01:05:57,280 --> 01:06:01,000
Speaker 1: That's like so amazing to me, because that retails about

1215
01:06:01,480 --> 01:06:05,040
Speaker 1: selling to the consumer. How could they not understand that

1216
01:06:05,200 --> 01:06:08,320
Speaker 1: the consumer input is important and it shouldn't just be

1217
01:06:08,440 --> 01:06:12,400
Speaker 1: a push strategy. It's amazing to me. Well, for how

1218
01:06:12,520 --> 01:06:16,680
Speaker 1: long did that strategy work before it's suddenly stop working.

1219
01:06:17,040 --> 01:06:19,200
Speaker 1: It's yeah, if the market gets competitive enough, if you

1220
01:06:19,280 --> 01:06:22,040
Speaker 1: don't have enough competition. And that's why whenever I give

1221
01:06:22,080 --> 01:06:24,200
Speaker 1: a talk on any of this stuff, I asked the room,

1222
01:06:24,320 --> 01:06:26,480
Speaker 1: is Amazon a good guy or a bad guy? And

1223
01:06:26,560 --> 01:06:29,840
Speaker 1: it's always fifty if you're a customer. If you're a customer,

1224
01:06:29,920 --> 01:06:32,520
Speaker 1: you say Amazon is a good guy. If you're a competitor,

1225
01:06:32,600 --> 01:06:34,880
Speaker 1: you your face gets you read and you just hate

1226
01:06:34,880 --> 01:06:38,919
Speaker 1: Amazon because competing against Amazon is so difficult. But most

1227
01:06:39,000 --> 01:06:41,600
Speaker 1: people will agree what Amazon has done is raised the

1228
01:06:41,640 --> 01:06:45,760
Speaker 1: bar for everybody, frost the board across lots of different industries. Huh.

1229
01:06:45,960 --> 01:06:49,920
Speaker 1: Quite fascinating. We have been speaking with Professor Barbara con

1230
01:06:50,160 --> 01:06:54,160
Speaker 1: of the Wharton School of Business. If you enjoy this conversation,

1231
01:06:54,240 --> 01:06:55,880
Speaker 1: we'll be sure and look up an inch or down

1232
01:06:55,920 --> 01:06:58,600
Speaker 1: an inch on Apple iTunes and you can see any

1233
01:06:58,680 --> 01:07:02,840
Speaker 1: of the past two hundred plus conversations we've had previously.

1234
01:07:03,520 --> 01:07:07,480
Speaker 1: We love your comments, feedback and suggestions right to us

1235
01:07:07,640 --> 01:07:12,280
Speaker 1: at m IB podcast at Bloomberg dot net. I would

1236
01:07:12,320 --> 01:07:14,680
Speaker 1: be remiss if I did not thank the crack staff

1237
01:07:15,040 --> 01:07:18,840
Speaker 1: that helps me put together these conversations each week. Attica

1238
01:07:19,120 --> 01:07:22,920
Speaker 1: val bron is our project manager. Medina Parwana is my

1239
01:07:23,160 --> 01:07:27,680
Speaker 1: producer slash audio engineer par Excellence. Taylor Riggs is our

1240
01:07:27,720 --> 01:07:31,160
Speaker 1: booker slash producer. Michael Batnick is our head of research.

1241
01:07:31,920 --> 01:07:35,320
Speaker 1: I'm Barry Ritults. You've been listening to Masters in Business

1242
01:07:35,640 --> 01:07:36,720
Speaker 1: on Bloomberg Radio