Wharton Professor Peter Fader on Managing Your DTC Business Around Your Customers

Listen and nerd out on: Apple Podcasts | Spotify

Drew Sanocki and Michael Epstein are joined by the legendary Professor Peter Fader from the Wharton School of the University of Pennsylvania. They dive deep into the world of customer centricity and how to run businesses that are all about pleasing the customers.

Guest Speaker: Peter Fader

Peter Fader is a Marketing Professor at The Wharton School, University of Pennsylvania. He believes that marketing should not be viewed as a “soft” discipline, and he frequently works with different companies and industry associations to improve managerial perspectives in this regard. His work has been published in (and he serves on the editorial boards of) a number of leading journals in marketing, statistics, and the management sciences. He has won many awards for his teaching and research accomplishments.


- Follow Peter on LinkedIn

- Follow Peter on Post.News

Read the Transcript ↓

Today's guest is none other than Professor Peter Fader from Wharton. He literally wrote the book on customer centricity and managing your business and leading your business in the direction of your customers. His research, 35 years of research, boiled down into three things. Number one, every business has good and bad customers. Number two, the good customers drive the business. And number three, therefore, you as a leader of a business should orient the business around those good customers.

This is kind of what I talk about all the time with whales and minnows. So it was a great conversation. We touched on Bonobos and Warby Parker and all these sort of darlings of DTC that came out of his program at Wharton. And what you should do today when you, I guess, start thinking about customer lifetime value and managing for customer centricity. So without further ado, Professor Peter Fader.

Well, Professor Fader, thanks for joining us. You know, I've been a fan forever. We've met a couple of times. I'm remembering a dinner in 2012. 2012, 500 years ago. Right. Put together by Jeremy Liu. And it was like a who's who of D2C brands in New York. And I think we were talking about Warby Parker going into brick and mortar stores. Oh, Drew, bless your heart. You're so right. And I'm so glad someone remembers that because I've been shouting about that since the day that the Warby guys were sitting in my office telling them, it's the kind of online glasses thing. I'm not sure about that.

But if you're going to do it, open stores. I'm not sure if Neil and Dave remember that. Why? Because you got to be in all places for all people. You got to show that you're not just DTC, that you're C. And I think it's going to help with acquisition, retention, development, brand building. It's expensive.

But if the unit economics, if the customer loyalty, if the lifetime value is there to support it, then you want to go broad and not narrow. The article this weekend in the Wall Street Journal was about Warby Parker opening stores. And it's something that I think you said at that dinner that stuck with me. It's not just to get in front of more customers. It's to get in front of more of your best customers. Right.Like to really drop that cost of acquisition for acquiring those best customers. That's so true. It turns out that, at least in the early days of stores, those people who are going to go into the store of some brand that isn't broadly known to the mass market, those are going to be your best customers. It's a way to signal to them that you have their best interests in mind and to acquire more like them. And actually Warby, I'm not sure they were the first DTC to observe this. Actually got to give a lot of credit to Bonobos.

The company that's been going through some interesting times as well. I don't know if it was their first CMO, but certainly an early CMO, Craig Elbert, who's had just a wonderful history of his own. We're talking to him this week. Yay! No, Craig was one of my students. And when he started opening up those guide shops for Bonobos, again, we're talking over a dozen years ago, it wasn't just, let's just do this because it's the right thing to do. Let's do it to measure the value of those customers who come through it and how much more valuable they'll be after doing so. And it just made a ton of sense for them. For everybody.They were just the first to really, really quantify and commit to it. On that point, help explain to the audience the difference in value.

First, you talk about this concept of customer-based audience and identifying what Drew and I call like whales versus minnows, your best customers versus your one-and-done's, the people that don't matter as much. I'd love to just hear from you, like your philosophy around that and how it should inform how people think about their business and driving acquisition. You know, it's so weird that on one hand, my philosophy is just, I'm just stating the obvious. On the other hand, which is to say the 80-20 rule exists. Most of your customers are not that great. They're not going to stay with you a long time. They're not going to buy that often. In fact, a lot of your customers don't even think of themselves as your customers.

That it's a purely transactional relationship. They gave you money. You gave them a product or service. It was a fair deal. It's done. There's no relationship. And that's okay. Many companies take that personally. Like, how have we failed them? We were at the altar and we didn't get married. And they use metaphors like that. It's a bunch of bull.

Now, on the other hand, other end of the distribution, you got these customers who can go through the gates of hell to stay with you. They get your logo tattooed on their body parts. Not all customers are created equal. You need to understand those differences. You need to quantify those differences. And you need to build a business, an organization, a set of metrics that explicitly recognize these differences. And that's the hard part. That's where a lot of people said, you had me at 80-20, but the rest of it, I'm not so sure about. I'm to fixated on the product. But building the business around the best customers, I guess to get operational, why would you want to do that? And one of the things that Mike and I have seen at our companies is that the cost of acquisition of a best customer or whale is often the same.

Customer acquisition costs for a minnow. So if you want to grow the business quicker? Why not just reorient that spend towards acquiring the whales? Yeah, Drew, you just defined the last five years of roller coaster ride. That wasn't just an observation. There's data there, right? I mean, I was like, what a perfect setup for a softball question. A lot of companies are operating under that notion that let's just acquire as many as we can and then just watch the top line go up hockey stick. Yay.

But they weren't really thinking ahead and say, what's going to happen after acquisition? Can we sustain that hockey stick forever? And the answer was no, that it is going to level off, it is going to turn over and start coming down. And what are we going to do as we start tapping out our acquisition? Until we have a base of profitable customers or do we have to keep kind of turning through new ones? That's exactly the problem with companies that we're not being held accountable for the profitability of their customer base, simply the size of their customer base.

And we just need to make the value of the customers as tangible, as visceral as the cost of acquiring them. And then we would just have a much more balanced perspective about how we do these things. That's the problem. There's a great example that I remember you wrote about with La Perla, the Italian lingerie brand and a retailer that was thinking about cutting the brand. But then when they dove in to the data, they understood it was actually helping them acquire a bunch of brands. Could you elaborate on that story or what you found there?

I think it's a great example for brands to follow. Well, yes and no. First gratuitous, just shameless shout out that comes from the new book over here that you referred to earlier, Michael, the customer base audit. And I have to give credit where it's due. That actually comes from Michael Ross, one of my co-authors on the book, who's done a lot of work with La Perla. In fact, he himself had a startup on what we call that Women's Intimates, a company called Fig Leaves back in the dot com days. So it's a space he knows well. But more importantly, it has nothing to do with just undergarments or garments at all. It just has to do with companies selling things and trying to understand the interplay between the value of the customers and what it is that they're doing or what it is that they're buying from us. Too many companies will look at their catalog and say, well, what stuff is selling the most? Those are the things we need to double down on.

Hey, R&D people, get us more stuff like that. And again, in the old days when the only thing we can measure was product level sales, that seemed good. It seemed like a good proxy for value. But today, now that we can tag and track individual customers, calculate lifetime value, we need to be asking ourselves, what's the value of the people who buy that product? Because we might find that there are some products that don't really sell all that much, but the people who buy them, those are the customers with the logo tattooed and so on. And so we need to double down on those kinds of products instead. Say, what is it that distinguishes our high value customers from the other ones? Let's develop those kinds of products, offer services related to them, do collaborations with other firms that's going to show these customers that we really have their best interest in mind.

We're not just trying to cross-sell and up-sell and hope along the way that the so-so customers will buy that stuff too, but just don't try to turn those ugly ducklings into beautiful swans. I mean, don't mind if we do, but it's expensive and difficult to do that. Yeah, in that case, it was that they were about to cut the brand completely and then that same brand ended up becoming a key growth driver of the whole business, right? Because they were able to acquire so many more high value customers by pushing it. And we see this story over and over again, yet it still tends to be more exception than rule. So another great example of it, same exact story happening at Electronic Arts. When they were kind of, you know, sort of plateau, this is going back about 15 years, and instead of just trying to develop blockbuster products that will be broadly appealing, not there's anything wrong with that, but let's also come up with products that are going to be uniquely appealing to those high value customers to help elevate their value, acquire more like them, signal to them that we really care.

I just wish that more companies got this and would look at their products through the lens of the value of the customers who buy them. It's inexcusable. And again, that's what you'll go wave in the book around. That's why companies really need to do a customer based audit. It's not cool. It's not sexy. That's the whole point. It should be routine. It should be standardized. I disagree. I think it's very sexy. Oh, well, to people like us, but you know. So Mike and I have been doing this sort of private equity operating partner thing for, I don't know, 10, 15 years, and a lot of them are turnarounds. And that's the first thing we do is that audit for us, it's been RFM. We start there and then just divide the customers into quintiles. What is the top quintile have in common? What is the bottom quintile have in common? There are a couple areas where we drill down. And I'm curious if you've seen this in your research.

Attribution, I would say usually correlates well. And you see a disparity top to bottom. First product purchased or first product experience is another big one. Let me first say the fact that you're building the bridge between private equity diligence and ongoing value creation operations. I mean, that's dream come true. There should be no disconnect between the analyses that we do when we're thinking of buying the company and the analyses we do once we've bought it. It should be the same thing. It should be the CFO and the CMO working together, same data, same metrics, same conclusions instead of, okay, we have this thing now. What are we going to do with it? So first of all, that's amazing. And you've been doing that longer than I have. I'm kind of relatively new at that kind of bridge building CFO, CMO activity. But boy, oh boy, am I sold on it now.

Also, it's just so wonderful to hear, again, people with serious operating experience like you guys just throw an RFM out there casually instead of even having to define what it is. So the point is we're making really, really good progress. And the kinds of things that you talk about there. So the question is, so once we calculate all that lifetime value, what kind of slicing and dicing do we do? Is it based on channel? Is it based on product? Is it based on net promoter score or God forbid demographics? That's a wonderful discussion to have as long as we agree that what we're looking for as we're slicing and dicing isn't just for like where are there more customers, but where's the value associated with those subsets of customers. And again, that's the hard part to get people to really embrace that and run with it seriously. Again, you guys get this.

I just hope that the world will listen and act on it. A lot of our listeners are all, I would say Shopify store owners in the middle market, you know, eight figure businesses. They're all data driven. Everybody says they're data driven. And I think they know about RFM, right? I have seen over time, there's a bigger awareness of that. For that operator, how would you advise beginning with a customer audit? I love that point is we want to begin with the customer audit before we get into all the lifetime value stuff. So I hate to keep doing this again. I'm not here to sell books, but I do want to point out that the subtitle of this thing is that the audit really is the first step. It's kind of odd that this is book number three because the point about the audit is that there's no models. There's no forecast. There's no Greek letters. It is, as my co-authors and I like to call it, unashamedly descriptive.

Let's just look at the data that we have. Let's look at it through the right lens or lenses, as we talk about in the book, and say this is what we have here. Here are the pockets of value. Here are the opportunities. Here are the gaps. Now what? And that's going to drive two things. It's going to drive action to figure out who are those customers to lean into and how to do so. And it's going to drive forecasts. Now that we see the kind of regularity, the kind of presumable predictability in these behavioral patterns, wonder what's going to happen next. And that's where the lifetime value stuff starts to kick in. So first, embrace the data, tag and track those customers, which in the Shopify world is so easy. It happens naturally. There's no excuse not to. And then start to both take action, generate these forecasts.

There should be just natural steps in the Shopify or in general, the DTC playbook. The problem is that too many of the folks who run those businesses took their marketing 101 course years ago and it was all just about the four P's or whatever, which again had this explicit focus just on product, product, product. How should we position the product? This is the product we're selling. Who should we be aiming it at? As opposed to figuring out who are the best customers and what kinds of products should be developed for them. So getting people to kind of do that 180 around the old school way of looking at marketing, that's hard. But once you do it, those next steps, the audit, the models, the execution, isn't that difficult. And you've talked about how traditional demographic segmentation often falls short. And we were just talking about how RFM is really a better way to look at it. Maybe expanding on that for the Shopify brand. For those that aren't super familiar with it, what are the first steps these brands should take?

Okay, history lesson. When the world was created, which is to say about 60 years ago, you know, marketing as we know it today, and we needed to kind of put our customers in buckets and we needed to understand some difference across them. The only ways we could do that would be to look at them. Demographics, that's the best we can do. At the time, it made sense. But here we are 60 years later. And first of all, we have much, much better data to characterize folks. And we shouldn't be just using those same kinds of practices that were that were prevalent back then. And then our forefathers in direct marketing, again, a domain that the two of you have such great appreciation for. A lot of our DT C folks don't realize the giants whose shoulders we stand upon, Lester Wonderman.

If you don't recognize that name, look it up, the father of direct marketing. And basically, they did some data mining, you know, 40, 50 years ago, to say instead of like who these people are, what would be behavioral aspects of folks that basically sort out the presumably high value from low value. That's where we came up with recency, frequency, monetary value. Today we can go one step further, because while those are still a much better way to characterize customers than, you know, income, age, gender, race, instead of doing it purely on RFM, let's go one next step and do it on the basis of projected CLV, which is going to be like RFM, but even better, more predictive, more granular, more specific. And let's start using that as the way to bucket people.

Let's create deciles on the basis of either exhibited or projected value and then start to say what makes the top decile different from the bottom decile? And how can we not just send different messages to them or not just what products can we develop for them, but to make it an organization wide strategy, whether it comes to customer service, supply chain aspects and accounting and finance, basically build the whole business around those meaningful behavioral customer differences. How do you get to predictive CLV? We look at recency, for example, and how recently someone's a customer predicts certainly how likely they are to come back. But I imagine the models are much more advanced now. So first of all, let's emphasize that we call it RFM for a reason. Recency is more important than frequency, is more than monetary value.

And it's important to emphasize that because when people are creating their dashboards, a lot of them will have a frequency metric on it. Who are the most common buyers? They'll have a monetary value metric. Who are the ones who spend the most when they buy? But very few companies have any kind of recency KPI on their dashboard, which is ironic because it's the most predictive one. And it complements the other ones. And so that's a little unfortunate. So that's why I want to kind of jump to the next step, which is let's run these models, which are pretty easy to do. That's my job. If anyone wants to know and they're not already familiar with my work, contact me. I'll send you the CLV starter kit, videos and spreadsheets and our code and all sorts of things that show us how we can take the simple observable RFM data and link it directly to predictive CLV then to use that for the bucketing, for the targeting, for the evaluation of the programs that we run. It's just going to be, it's going to be like RFM. It's just going to be more effective and weirdly more actionable as well.

In that office, you had the Warby leadership team. You probably had Craig Elbert from Bonobos at some point. All these companies are giving lip service and certainly talking about customer centricity. And yet some of them aren't doing as well as others right now. I know Warby seems to be doing well, but Bonobos been up and down. I guess where do these companies go off the rails? If they say the right things about customer centricity, where are they stumbling? So frustrating. So,  while they're in this office or God forbid, while they're in my semester, long course, just being hammered with this stuff, poor souls, they, they get it. They're committed to it. They actually start practicing this stuff. And that's wonderful. Then, two things happen. They're both, both closely related. They grow. So one is they, they start bringing in the investors, the VCs. And for them, it's going to be kind of, you know, a growth at all costs. It goes back to what we said before, just acquire, acquire, acquire. And the whole product led growth notion, which conceptually I'm fine with, but the way it tends to be executed, it's more about volume than value.

And the organization itself grows and we start bringing in a broader mix of people. And you know, I'm kind of naive about this stuff. If you haven't picked it up by now, I'm a hammer looking for nails. Like, hey, here's the CLV thing. Bang, bang, bang. But actually, as the organization grows and we're bringing in lots of people who didn't have the pleasure or pain of taking one of my courses, they're going to be falling back to the traditional product oriented way of thinking about marketing. I'm actually working on book number four right now, which is what I call, "The Five C's," creating a customer centered corporate culture. I'm not a corporate culture guy. Okay. I don't fully understand that stuff, but every day I'm having a much greater appreciation of it. Then until we can build that culture, until we can build the right kind of organization that really is putting customer heterogeneity at the center of everything we do.

Then it doesn't matter how powerful the models are. We really need that one. Then a bunch of having people who totally get this stuff and are committed to it and aren't just doing so because the Wharton alum CEO is making them do it and complementing it with the models that can help them do all of these different aspects, marketing, finance, and all the other functional areas more effectively. It's got to be that kind of one, two punch. And it's maybe a little bit late to the party to bring it up, but better late than never. If you're the CMO or the VP of EECOM or whatever it is in the organization, how do you recommend they convince the senior leadership team, the board, who may be starting to either push back or not fully understand some of these principles? What do they say to convince them that this is necessary? It takes us full circle to the early part of the conversation. That's where we start talking about CBCV, customer based corporate valuation. And let's not even ask the CMO to do it. You get our stuff. Okay, it's terrific.

We know that we can make you look like the hero. Okay, fine. You keep doing that. In the meantime, I'm going to go have a little chit chat with the CFO to say, I'm going to help you do your job more effectively. I forget about those folks in marketing. Who knows about them? But let's you and me talk about it. And I can help you project revenue over a long horizon more accurately and with a better diagnostic understanding of why it's plateauing or when it's going to plateau. So I'm going to help you do the finance thing more effectively.

Just so happens that I'm going to be using the same models, the same metrics, the same everything, just a different language that we were talking to the marketing folks about it. Let's win over the finance people instead. And then they'll go to the marketing people say, "hey, you guys ought to check this out as well." And the marketing people say, "Yeah, we're with you."

So let's just start with finance as a way to convince the rest of the C-suite and to build a bona fide relationship between these different functional areas using the models for very different purposes, but in the same way. And when we can do that and we have great things will happen. Now, a lot of the cultural stuff will kind of follow naturally. Love that. We've definitely in our experience seen the need to partner with sort of the CFO and even heard it from boards like partner with the CFO. You get the CFO on board with something, you make the numbers actually make sense. And all of a sudden the organization buys in. It's a lot easier to get the whole organization to buy in. And along those lines, you hit the nail on the head, Mike. It's not only doing it from an internal perspective about just making sure we're running more effectively over longer horizons, but let's do it externally as well. So let's make sure that our stakeholders are kind of banging on the door, not only asking the right questions, but demanding.

Hey, have you done one of these? Show it to us. Can you maybe disclose some of that information on your 10 cues? I mean, that's the that's the windmill that we're tilting at these days. When I say we, I'm referring to my my co-author, my former PhD student and really my kind of guru, Dan McCarthy. This was all his dissertation work. And it's just just amazing as we we talk to companies and get them to start disclosing some of this stuff so people can start to stack us up against maybe our competitors or to stack us up against how we looked last quarter or last year to start seeing those those we're not going to put lifetime value on the on the balance sheet or the income statement. But we can put the kinds of metrics that underlie lifetime value. And let's start comparing ourselves on that basis. That's what we're starting to see more and more first through S1s when companies go public, but even starting to see it in the 10 cues, starting to see lots of shareholder lawsuits around the disclosure or lack thereof of these kinds of metrics.

Let's get accounting standards boards to require them. That's years away. But but but the conversation is happening more and more. In your research and Dan's research, you're starting to see that correlation between aggregate customer lifetime value and share price. Yes, indeed. That's it's always been a holy grail for all marketing professors, not just me. In fact, there are other marketing faculty doing that kind of thing. In fact, we have now a trademark on those words, customer based corporate valuation, there was actually the title of a paper by some academics like 20 years ago.

So a lot of people have been striving for it, but no one's been able to do it in a way to actually have credibility with the CFO, with the VP of Investor Relations and with the board until Dan McCarthy came along, because Dan was a former buy side guy who came back to get his Ph.D. in statistics. And this was the basis of his dissertation is how can we look at aggregate publicly disclosed metrics and link them up both to life, the distribution of lifetime value as well as to to broader corporate valuation and doing that and just watching what's happened, watching more and more companies disclose or in some cases, companies stopping to disclose saying.

Wait a minute, we're revealing too much. We didn't realize that how much we were putting out there. We better stop doing that. We could kind of understand their motivation for doing so. But we want to make that we want to have just even more pressure that they can't get away with that. We definitely see that trend more on the private equity side, where 15 years ago, they just brought capital to a deal. And now I feel like they're differentiating more and more by bringing more value into a transaction. And I think the savvier funds are the ones that they say like in diligence, like give me your transactional data. We're going to run cohort analysis and they have some sort of modeling where they can try to get to evaluation off of that. Or they turn it over to the firm that Dan and I co-founded, Theta, where we'll kind of do all of that analysis, not just in a descriptive way, but in a predictive way as well. And that's great, especially in the DTC, which is the kind of consumer focused sector, where I think we can kind of almost declare victory there.

Problem is, and that's great for three of us, but the problem is that's just a teeny tiny part of the overall ecosystem. And if we're using a different set of rules, standards, policies, procedures for one sector versus others, it's going to be harder to really plant roots. So we want to say that we should be doing the same thing with any company that has customers. If you have customers and you like to acquire them and retain them and sell them repeatedly and have them pay more when they do, then you should be doing the same stuff, whether you're DTC, whether you're product or service, whether you're B2B, B2C, whether you're domestic, international. So we want these these approaches to be universal. And it really bothers me when I'm talking to private equity firms.

Oh, you got to talk to the consumer team. Yeah, they'll like that kind of stuff. Yeah, but we're only looking at kind of mid-market technology businesses. And we're serious here. We're not just doing that kind of kid stuff. Well, no, it's just as relevant for you. And ironically, in some of those cases, B2B, it's actually easier to tag and track and build relationships with customers than it is kind of in a more mass market, DTC world. So the models and the strategies and tactics apply just as well, if not better, in some of those more unconventional sectors.

And I think it's important for everybody to embrace it, to embrace this stuff. So we don't simply pull it off the shelf on an occasional basis. So Mike and I are running a software business now. We couldn't agree more. If anything, the temptation isn't there to go down the path of demographics when you're selling to businesses, right, because it's irrelevant. But there's still whales and minnows and they act differently and we acquire them differently and they buy different things when they subscribe. And what's amazing about it is that we can look at an enterprise SaaS company versus a digitally native women's underwear company. The models that will run are completely different. The data that we'd use is completely different. But in the end, when we wave our magic wand of CLV and we look at the distribution, it's still going to be the 80-20 thing.

Still going to be the case that most of the customers, however we define them but then there's always going to be that long tail of really great ones. So it's important to recognize that, again, we're going to adopt the appropriate model for the business. Of course, it'll vary there. But the overall practice is that not all customers are created equal. And if we could kind of build a growth strategy around the valuable customers instead of the volume of customers, that's going to be the path to success for all businesses. Professor, I have to ask because it wouldn't be a podcast in 2023 if we didn't mention AI at some point in the conversation. You know, what's the future of calculating some of these metrics and potentially creating more predictive models and potentially more automated and proactive tools? Like, where do you see this going with the advent of AI?

Great question. So I've got two or three different answers for you. One is the AI umbrella is really broad and very often will include machine learning under that umbrella. So before we even get into the whole GPT-4 thing, the models that I tend to build are actually not I mean, technically they would be ML, but they're not they're not like regression. They're not let's do some kind of random forest neural net deep learning sort of thing. They're actually very simple. They're very principled. They're very parsimonious from a data standpoint. I don't want anything more than RFM. So the basic models are super simple, but ML helps us really, really elevate their effectiveness for us to be able to bring in things like seasonality, to bring in marketing activities, competition, other aspects.

So we'll take the basic models and supercharge them with different kinds of ML technologies. When I send you, if you're interested in my CLV starter kit, we won't touch on any of that. That stuff is still, first of all, emerging. Part of the secret sauce commercially. And it's much harder. You can't just do that in a spreadsheet like you can with the basic model. So first, there's the ML piece. And then there's going to be the true AI piece. So I teach this this nasty course that I've alluded to, and I not only allow, but I invite, encourage my students to actually try doing their assignments, you know, using GPT-4. And at least this past semester, all the time, I have a lunch with them, say, "Did it help you?" And the answer is no. Yeah, it helped me kind of copy edit my paper, but it didn't help me with the analysis at all. So on one hand, there's still a long way to go until those technologies can actually be a real help for the kinds of models I'm talking about.

It's inevitable that it's going to happen. And I can't wait till it does. In fact, a bunch of people on my team at Theta actually did try running through all the different platforms, GPT-4 and BARD and a couple of the other ones, just to see what they would say with how they would write code for these kinds of models. I was just putting a blog post out about it because it's actually kind of laughable how bad they are right now. They try, but they're not that good. But it is inevitable that technology will improve in leaps and bounds. It could be by the end of the year. They're writing that code and diagnosing the models better than our experts can. And I'm good with that. I'm 100% good with that because once these models are super accessible, that you can have faith in them and you can use them for a broad variety of use cases. That's great. Because as much as I enjoy doing this stuff commercially, I get my day job here.

I'm a professor and I want to profess and I want to spread the gospel and nothing will do that more effectively than just a really well-tuned AI engine. I had one I wanted to go back to that just occurred to me when we were talking about brands moving into traditional brick and mortar. What we see a lot now, especially in CPG, are brands that start online and then they move into non-branded traditional distribution, Target, Walmart, Whole Foods. I guess, how do you think about that from a customer centricity's? It's still, I guess, getting in front of their whale customers. They should be doing that analysis, but then they lose the customer data. Exactly. And that's such a good point. So it's an important step to take for a variety of reasons. One, to be everywhere that your customers want you to be. It helps give you more leverage and more capital to actually go out there and start building your own stores and kind of owning the relationship.

So it's an important step, but it's not the ultimate step. And especially these companies that I handed off to, you know, FBA to hand it off to Amazon to say, here you go, go run it. We can't, we can't figure this stuff out. That is so grossly irresponsible. It's one thing to distribute through Amazon, but it's another thing to be beholden to them. So it's really, really important to manage to maintain the tagging and tracking capabilities and the relationship with the customers. I mean, the ultimate example of it, while, you know, your Shopify businesses aren't there yet, but their aspiration is to do what Nike has done. And for those of the folks listening to you, who aren't aware I built company number one out Zodiac to bring these lifetime value models to life at full commercial scale. Nike bought that company a few years back and, and their main motivation to do it is because they didn't want to be beholden to their distributors, the, the footlockers and the Walmarts of the world.

They wanted to own the relationship. And that's why they needed to be able to calculate the value of each and every customer and understand how that's going to drive the tactical things that they do and drive the negotiations with their channel partners. So, so you really need to, to own that channel relationship. And companies tend not to look at that in a strategic investment oriented way. They look at it in a cost way. What is this going to cost us? How much are we going to save instead of what is that data worth it to us? What are those relationships are worth to us? That's clearly the right way to be looking at it. And again, we're just getting there with that. I think that the Nike story is really should be the kind of North star aspiration for every company.

I agree on the flip side, we run a direct mail platform for e-commerce. And what we've seen are brands mining their, their Shopify data, their first party data in order to market and acquire audiences to drive and to purchase in a whole food. So it's still, they may not own the customer there, but they can use their first party data, what they know about the customer through their Shopify store in order to develop an audience to push there. It's almost an argument. Like if you're, if you're a traditional brand and you only sell through third party distributors, set up a Shopify store, start getting some first party data. That's right. And work with some of the third party providers, like some of the credit card panel firms. For instance, I love the folks over at earnest analytics to bet to kind of augment some of that, that first party data. Oh boy, this is tough, find a way to build such a strong relationship with your customers.

Some of your customers that they want to self identify, you know, Hey, I made this purchase over at Whole Foods, but I want to make sure that you have it on the record so that you can treat me better. So whether it's loyalty programs, mobile apps, just, just other ways that you're creating bona fide value for those customers, but they want you to know that you've made those purchases with them, even if you didn't make it through them.  

I really appreciate you taking the time. I could talk about this stuff all day long. You know what? And let's talk about it all day long. Let's get this session out there. Let's shout it from the mountain tops because again, the three of us are all literally finishing each other's sentences and now we just need to get the rest of the world to do so. So I really do appreciate the opportunity to talk with you guys and to, and to keep this broader conversation going. Absolutely. This is great Peter. Yeah. Shaped our whole philosophy throughout our career. Really appreciate it. The man who literally wrote the book on customer centricity. Appreciate it. Good talking to you guys.

Ready to increase your revenue?

Join thousands of ecommerce brands using PostPilot to acquire more customers & keep them coming back again (and again).

Try it risk-free
5.0 Shopify Rating

No contracts. No minimums.