Personalized: Customer Strategy in the Age of AI

[00:00:00] You're listening to Retail Disrupted, a podcast that explores the latest industry developments and the trends that will shape how we shop in the future. I'm your host, Natalie Berg.

[00:00:15] Hello and welcome back to Retail Disrupted. Most of you are probably listening to this on your usual channels like Apple or Spotify. But if you wanted to watch this episode, it was recorded as video and is available over on my YouTube channel.

[00:00:27] Today, I'm excited to bring you a conversation with Mark Abraham and David Edelman. Mark is a managing director and senior partner at Boston Consulting Group.

[00:00:37] His teams have accelerated the personalization efforts of over 100 iconic brands, including Starbucks, Home Depot and Google. David is an executive advisor, a board director and a fellow at Harvard Business School.

[00:00:52] And as this is a retail podcast, I should also call out that David is a former CMO of Aetna, which was acquired by CVS during his time there.

[00:01:00] Together, David and Mark have written a fantastic new book called Personalized, Customer Strategy in the Age of AI.

[00:01:07] In this episode, we unpack how customer loyalty is evolving for the digital era.

[00:01:12] We look at why businesses get stuck and why so many end up doing personalization in a superficial way.

[00:01:20] And then we look to the future and how generative AI and technology more generally will unlock new opportunities for retailers and brands.

[00:01:29] I really enjoy this conversation and I'm delighted to bring it to you as the final episode of 2024.

[00:01:37] David and Mark, I am so excited to have you both on the podcast.

[00:01:40] You've just released a new book called Personalized, Customer Strategy in the Age of AI.

[00:01:45] So we're going to talk about personalization.

[00:01:48] We're going to talk about the consumer, data, technology.

[00:01:51] There's so much to explore.

[00:01:53] But before we do that, I'd love to know what led you to write the book.

[00:01:56] And without giving away too much, can you share some of the big learnings or themes from the book?

[00:02:04] Absolutely.

[00:02:04] So this has been a labor of love for David and I over the last two years.

[00:02:10] And we actually started writing the book right after ChatGPT came out and Gen AI changed the world.

[00:02:17] So it's been amazing to explore what personalization leaders are doing, actually define what even personalization is, because it's such an overused buzzword.

[00:02:27] But also find that companies are driving tremendous growth with personalization.

[00:02:33] And that was the biggest learning.

[00:02:35] The top 10% of companies that we call personalization leaders are going 10 points faster than the laggards.

[00:02:44] And that will lead to a $2 trillion prize that they're capturing.

[00:02:49] So personalization is actually the best way to use AI to drive growth.

[00:02:54] So that's the punchline of the book.

[00:02:56] Next.

[00:02:57] Looking it back, just linking it back for a moment to some history.

[00:03:02] I've actually been playing in this space since 1989.

[00:03:06] So actually before the internet became a major commercial thing.

[00:03:10] I was a young consultant to BCG having worked on three projects where clients were asking, what can we do with customer data that we're starting to collect?

[00:03:20] And I thought there was something bigger.

[00:03:22] Came up with the term segment of one marketing.

[00:03:25] Wrote an article and that launched my career.

[00:03:28] It got picked up, conference speeches, getting clients.

[00:03:32] Then the internet came and I started working more and more hands-on with companies trying to get them to figure out how to use digital tools over time.

[00:03:42] The thing though that's really changed though, that led me especially to go and do the book, is less the word marketing and more the word strategy now.

[00:03:55] Because what I'm seeing with the capabilities from AI is that it's not just about tweaking the marketing to get a better response from somebody.

[00:04:05] It's about a whole way to compete.

[00:04:08] It's about changing the customer experience using AI.

[00:04:13] I mean, if you think about Spotify, Netflix, Uber, these are brands now that you're attracted to because of the way they use customer information to help you get value.

[00:04:25] And so that was one of the key things as Mark and I were talking about the book is that this isn't just for the marketing space.

[00:04:33] This is a broader corporate strategy issue.

[00:04:36] And we felt a need to lay that out.

[00:04:38] Yeah, that's interesting. Dave, I want to come back to those disruptors that you just named.

[00:04:43] But first, Mark, I want to ask you something.

[00:04:45] You just touched on defining personalization.

[00:04:49] And I know personalization means different things to different people.

[00:04:52] So how do you define personalization in today's digital era?

[00:04:58] So we think that personalization needs to go way beyond just putting a name in an email or offering a,

[00:05:05] if you bought this, then you might like that kind of recommendation.

[00:05:10] And it goes to the heart of what David said.

[00:05:13] This is more than just marketing.

[00:05:15] So what we lay out in the book is a definition that says true personalization is about taking what you learned in one interaction about a customer and making the very next interaction better, faster, cheaper or more convenient.

[00:05:29] So breaking that down, what you realize in order to do that, you need to have enormous data and insight about customers, millions of customers, millions or even billions of interactions as the examples of Spotify, Netflix and Uber illustrate.

[00:05:45] But then you also need speed.

[00:05:47] That next interaction might happen hours or days later.

[00:05:50] And you need to be able to turn around the insights into a better experience.

[00:05:55] Yeah, that's interesting.

[00:05:56] And just to pick up on that, I'd like to get your thoughts on the consumer and mention and to go back to some of those digitally native brands that you just mentioned.

[00:06:04] So Uber, Spotify, Netflix, I would include Amazon there as well.

[00:06:07] All the disruptors, right?

[00:06:08] A lot of their success has been due to a relentless focus on the customer and making that experience as frictionless and as relevant as possible.

[00:06:16] And I think that the customer understands that that kind of experience is only possible if you consent to giving away some data.

[00:06:22] And I'd love to explore this in a little bit more detail.

[00:06:24] So how have consumer attitudes towards personalization evolved?

[00:06:28] And do you think that we now expect a sort of base level of personalization to be baked into most brand interactions?

[00:06:36] Yeah, there's research that we've done.

[00:06:40] BCG does research every year on consumer attitudes towards information use.

[00:06:45] And over 70% of people say they do expect companies to use information about them appropriately.

[00:06:54] And that's an important word in the delivery of service and that they are favorable towards brands who do.

[00:07:01] But on the flip side, 75%, probably a lot of the same people have said they've stopped doing business with brands who have not used their information appropriately.

[00:07:12] And so there's a line there.

[00:07:15] And that really requires you to think about how will this experience be looked upon from a customer's perspective?

[00:07:23] Is it clear what information we're using?

[00:07:27] Is it something they would expect us to have and use to help them?

[00:07:32] Do they feel manipulated?

[00:07:34] Do they feel bombarded?

[00:07:36] Or is it truly adding value?

[00:07:39] And so that's a set of questions that a lot of marketers actually struggle with.

[00:07:44] Because now with AI, it's so easy to spin up content.

[00:07:48] It's so easy to find triggers to bombard people that you can get overwhelmed as a consumer with nonstop pitches for something you do.

[00:07:59] For example, I just, I bought, I've moved recently, bought an espresso coffee machine, wanted to get a nice coffee maker.

[00:08:06] And it comes with a hundred pods.

[00:08:09] Two days after I got it, I'm getting bombarded with ads to buy more pods.

[00:08:13] Like how much coffee do they think I drink?

[00:08:17] If they think I'm a small business, they should ask me.

[00:08:20] And then within two weeks, they're pitching me a second machine.

[00:08:24] That's just crazy.

[00:08:25] And just because they can do that doesn't mean they should.

[00:08:29] And I've unsubscribed.

[00:08:30] It's just too much.

[00:08:31] So less is more.

[00:08:33] And we've got to use the information to be a lot smarter about the interactions.

[00:08:38] If we're really going to have customers build the kind of bond that we expect from personalization.

[00:08:46] Yeah, it's really interesting.

[00:08:47] The retail industry has been talking about personalization for years.

[00:08:50] And, you know, it is essentially the crux of retailing, right?

[00:08:54] You have to know what your customers want and then deliver it to them in a way that is superior to your competitors.

[00:08:58] I mean, that is the, you know, sometimes we overcomplicate things in retail.

[00:09:02] But traditionally, it was kind of the smaller independent stores that knew their customers best, right?

[00:09:07] They were closest to their customers, potentially on a first name basis.

[00:09:11] But now, of course, thanks to technology, huge corporations are able to replicate that to varying degrees, right?

[00:09:19] But when we think about the evolution of personalization, what sort of role has technology played in all of this?

[00:09:25] Would you say that technology has been the biggest driver of change?

[00:09:29] So, number one, yes, I think you're spot on.

[00:09:35] Scale matters.

[00:09:36] And it's specifically the scale of digital customer relationships.

[00:09:41] So, take restaurants as an example.

[00:09:44] You know, your mom and pop local restaurant knows you by name if you're coming there frequently.

[00:09:49] But now, you know, brands like Starbucks or McDonald's or, you know, the salad chain Sweetgreen, they do a great job of creating these digital touchpoints, getting you to come to the app, to put in your mobile order.

[00:10:03] And so, you know, the customer, each of those touchpoints generates a piece of data about where the customer is, what their context is, what their favorite products are, which offers they engage with.

[00:10:13] And these companies have built the infrastructure and the data and technology to be able to capture that as insights.

[00:10:20] Now, I think what still gets in their way sometimes is you also need the people, the human element in this.

[00:10:28] And that's where a lot of retailers especially are set up with product silos and product P&Ls to manage and deliver against every quarter.

[00:10:38] And that's where you get into sometimes a bit of trouble if you're trying to market products instead of really thinking about what that customer needs.

[00:10:50] So the best companies have set up customer centric teams, agile pods that bring together marketers, technologists, analytics folks to really deliver against each of these use cases and personalization.

[00:11:05] Yeah.

[00:11:06] And just to give an example of that, I've gotten to know some folks at Sephora.

[00:11:12] And like Mark said, Sephora is a retailer who had a lot of different categories, everything from fragrances, skincare, cosmetics, all different ones, all of which are pretty much using the same lists to go after the same customers.

[00:11:29] And so from the customer's perspective, you might get emails, texts, pop-ups on the website, even direct mail that doesn't seem coordinated.

[00:11:42] That's all over the place.

[00:11:43] And they started recognizing that.

[00:11:45] They saw that the actual open rates and the use of their promotions was going down.

[00:11:51] And so they decided to create a much more coordinated approach.

[00:11:56] So besides the technology involved in capturing that data, they also use technology to combine the data.

[00:12:04] So generative AI can write code and it can write the code to help you look at one data set, understand that schema, look at another data set, understand that schema,

[00:12:15] and then be able to actually write the code to bring it together in an integrated repository and normalize the data.

[00:12:23] There are services like there's one from narrative.ai called Rosetta that's very popular right now.

[00:12:30] And so bringing that data together across the channels, across the different categories was not a small job, but they brought that together.

[00:12:38] And then they also centralized more of the customer management and made sure that when you saw a specific offer in an email, that's the same thing you're going to see on the website.

[00:12:51] That's the same thing you're going to see on the mobile app.

[00:12:53] If you walk into a store and show a loyalty card to a rep, same thing that's going to come up.

[00:12:59] And so the information is coordinated across all of that.

[00:13:04] And that's totally turned around the receptivity that they've had to their offers and their engagement.

[00:13:09] But it does take both engineering from a data perspective and the operations changes that Mark talks about.

[00:13:18] Yeah, yeah.

[00:13:19] And that is the Holy Grail, isn't it?

[00:13:20] It's unifying that experience for the customer because the customer's channel agnostic, their device agnostic, and they do just want that seamless experience.

[00:13:27] I want to pick up, and we're going to come back to AI, but I want to pick up on a point that Mark just mentioned around culture.

[00:13:33] Now in retail today, the word relentless comes up a lot in terms of describing the pace of change, but also the kind of culture that retailers need to adopt to stay relevant.

[00:13:42] So we talk about relentless focus, relentless innovation.

[00:13:45] And I'd love to get your take on the cultural shifts that are required for retailers or businesses more generally.

[00:13:52] And I wonder what you think about failure as part of all this, because if we're innovating all the time, not everything's going to stick.

[00:14:01] And I think when we look at who does this really well, you know, the best retailers fail fast.

[00:14:06] They take the learnings and they move on.

[00:14:08] But that requires a very different mentality for a business.

[00:14:11] So I'd love to get your thoughts on this, on culture and on failure more generally.

[00:14:15] I love that point because it cannot be overstated.

[00:14:22] You have to shrink the cost of failure, but you also have to embed this culture of it is okay to fail.

[00:14:30] What you do then is you learn and you quickly improve the next test and the next experiment and you scale that.

[00:14:37] I think one example around this is what I'm seeing around the world.

[00:14:42] We're doing work with the largest grocers everywhere from UK, France, Canada, US.

[00:14:47] The largest grocers are cracking the code on personalizing offers.

[00:14:52] And that is one of the best use cases to both drive incrementality for the business and the P&L, but also deliver value for customers, especially in this season, holiday season, as well as environment where inflation is high.

[00:15:07] Customers are very sensitive to price and seeking out deals.

[00:15:11] Now, to really personalize these offers where you have hundreds of brands, thousands or tens of thousands of SKUs, different offers based on points based percentage based dollar off, multi-step offers that can work for certain segments.

[00:15:29] You need a vast number of experiments and automation and technology that enables that, but also a team and an operating model that can learn fast.

[00:15:42] And the key to that is measuring quickly.

[00:15:46] Too often when you lay out the process, it can take 10 to 12 weeks to launch a campaign, whether it's a personalized offer or a personalized recommendation.

[00:15:55] And you can shrink that to a day or less now, but with modern technology.

[00:16:00] So when you do that, you can run hundreds of experiments in the time it took to run a single one.

[00:16:07] So the cost of failure has gone down dramatically.

[00:16:10] And then leaders need to instill in their teams that it's okay to fail.

[00:16:14] It's okay to have an experiment that you learn from and move on.

[00:16:17] Yeah. And what are you seeing with the grocers? Because I agree with you.

[00:16:21] I think this is where there's such a huge opportunity to better personalize that experience and to do it in real time.

[00:16:27] I think that's really key as well.

[00:16:29] So we've talked about hyper personalization for a long time in the grocery sector.

[00:16:34] So I'm just curious to know what you're seeing and what opportunities you think are out there for retailers.

[00:16:38] So I see the best grocers and retailers, and this is true in restaurants as well, now going from segments of 10, 20 to hundreds of thousands of variants, being able to be run through these personalized offers.

[00:16:57] And that takes a bunch of engineering work in the background and unlocking bottlenecks like coupon codes and the like.

[00:17:02] But what it does is you do find that incremental bit, you know, oftentimes people are skeptical as hyper personalization really that much more valuable than just segmentation.

[00:17:13] Well, the answer is it is you go from 2x the ROI for a mass versus a segmented campaign to around 4 or 5x the ROI on truly hyper personalized offers.

[00:17:26] And so there is not just business value here, but also what it does, it drives engagement into the digital channels for these retailers.

[00:17:38] So especially something like multi-step offers, gamified offers that we are seeing more and more of, for example, come in three times over the next month and unlock a coupon or additional value.

[00:17:50] Those kinds of things bring people back into things like the app.

[00:17:55] And now you've got additional signals you can use to personalize both the offers as well as other experiences for customers.

[00:18:03] Interesting.

[00:18:05] Now, David, I'd love to get some thoughts, some of your thoughts on, on AI.

[00:18:09] And I'm personally fascinated by Gen AI.

[00:18:12] I think that's where, you know, there's been such interest.

[00:18:15] You know, you talked about ChatGPT at the start of the conversation.

[00:18:19] How do you see Gen AI impacting the experience and what are the opportunities for personalization?

[00:18:26] And I guess before you answer that, just to share a couple of things that I'm seeing, you know, Gen AI chatbots, for example,

[00:18:31] are going to be so much better than the chatbots that we have now, a lot more intuitive.

[00:18:35] You talked about at the beginning, the whole, you know, if you like this, you might like that.

[00:18:40] I mean, there's so much more I think retailers can be doing to better customize that experience.

[00:18:45] And also we're seeing a lot of innovation, a lot of experimentation around AI powered shopping assistance.

[00:18:51] Bill Gates has even said that in the future, we'll never need to search on Amazon or Google again,

[00:18:56] because we'll have these shopping buddies and they'll ultimately become the gatekeeper to us as the customer.

[00:19:03] And sometimes it is hard to separate hype from reality, but I'm curious to get your thoughts on how much of a game changer do you think these things will be?

[00:19:10] Is this something that can really move the dial in terms of customer experience and personalization?

[00:19:16] No question.

[00:19:17] And we're already seeing experimentation and capabilities starting to be built.

[00:19:22] So, for example, again, I just moved.

[00:19:26] So I moved house, I just moved into Cambridge, Massachusetts.

[00:19:29] And when I moved, I got bombarded by offers from Home Depot just simply because I moved.

[00:19:38] But the reality of what I would want is the first project I really want to do is renovate a bathroom.

[00:19:46] So give me the opportunity, Home Depot, to take a picture of the current bathroom from that picture, actually deduce the dimensions and the location of pipes.

[00:19:58] Have me upload maybe a few pictures that I saw on Pinterest or elsewhere from a style perspective.

[00:20:05] Give a budget, talk through main features that I would like and then say, come back to me with five different designs with their price tag.

[00:20:15] And then I'll pick one and you coordinate the installation.

[00:20:19] They are working on that.

[00:20:22] That is real in terms of the development pathway of doing that.

[00:20:27] There's a lot in there, though, from a capability perspective that I just want to pull out for a second.

[00:20:33] I mean, one is just simply the notion of you're not searching.

[00:20:37] You're putting in what you want from a chatbot perspective, even uploading multimedia pictures as well.

[00:20:44] And they are drawing inferences from those pictures that you're putting up.

[00:20:50] The other interesting thing is that they are providing a solution, not just a product, not just a link, but a solution, a personalized solution, which also means they can't do it themselves.

[00:21:05] So the other part of this that Gen.ai is enabling is companies to work together to drive an integrated solution.

[00:21:14] Gen.ai, and I mentioned this before, allows you to combine, learn how to combine data sets.

[00:21:23] It can also just in general manage the flow of data across parties, keep track of where data is going, manage privacy and access to particular data.

[00:21:34] And so you're going to see larger players, Home Depot, Marriott's doing this as well for travel, create ecosystems where they can coordinate the flow of data across parties to enable consumers to come in and just ask for a solution.

[00:21:53] And they would coordinate that.

[00:21:55] And they would coordinate that.

[00:21:56] And that's where, if you look forward in one of the most fun chapters in the book that Mark and I wrote is when we start looking at what's going to happen by 2030.

[00:22:03] And we already see this, the combination of Gen.ai, agent, agentic AI, being able to actually execute things.

[00:22:14] Those are start, the experiments are starting, the tests are starting, and there is a commitment and a strategic thing about this notion of coordinating ecosystems.

[00:22:25] So I think we're going to see some reshaping of how brands position themselves and the concept of a destination retailer.

[00:22:34] That's on the horizon.

[00:22:36] And just to put a point on it too, this is not just speculation.

[00:22:40] Some of these things are happening today.

[00:22:41] Like take L'Oreal's Beauty Genius.

[00:22:44] They already launched it in the US.

[00:22:46] It's a tool where you can interact and say, I have an occasion.

[00:22:50] It's a holiday party.

[00:22:52] I'm going to offer me ideas for the look and it will recommend the specific products for you to buy.

[00:22:58] In that case, from L'Oreal to start, I think what this is going to go though to David's point is they'll have to solve the entire beauty occasion and need of the customer, which probably will mean more than just L'Oreal products.

[00:23:12] So there's a real imperative here for retailers and brands to think about holistically, what does that customer need to be solved?

[00:23:21] Because if they don't solve it, then the platforms will solve it for them.

[00:23:25] And you'll see even more power shift to some of the largest network platforms in the world.

[00:23:31] Yeah.

[00:23:32] And just building on one very important point for retailers coming off Mark's thing is the importance of product data.

[00:23:39] Because in order to provide a solution, to provide an answer, it's not just interpreting what the customer provides you and is asking.

[00:23:48] It's being able to use a knowledge base of the products you're selling to figure out what works.

[00:23:54] And that requires a lot of descriptive data, metadata, retailers working with their suppliers to get that data at the right level of granularity and to think about things of what certain data, data items, product items are appropriate for.

[00:24:14] So very specifically managing that whole supply chain of data about products is going to become much more critical.

[00:24:25] I want to get your views on what happens if you don't do all of this, because at the start you talked about a $2 trillion personalization prize.

[00:24:34] So let's talk about the cost of not investing in personalization.

[00:24:37] I think if you ask any retailer, they're going to tell you, of course, personalization is important.

[00:24:41] But as you say in the book, most companies pursuing personalization are doing it in a superficial way.

[00:24:46] And we all know that that can backfire. It can turn customers off. It's a waste of time and money.

[00:24:51] They're missing opportunities. And also they're letting their competitors do it better.

[00:24:55] So I'd love to get your thoughts here. What are some of the mistakes that retailers make about personalization?

[00:25:01] And what's the risk of inaction?

[00:25:05] So two points. We're not saying that personalization can replace getting the, what I would call, brilliant basics right.

[00:25:14] So clearly all retailers have a tremendous trade off discussion going on right now in terms of all their tech priorities.

[00:25:24] And they do need to fix the supply chain and get the products on the shelves and make the make sure the associates are on the floor to service the customers.

[00:25:34] And the brilliant basics are in place. And many of them have real issues to shore up coming out of the pandemic and changes in technology and re-platforms and mergers that have happened in recent years.

[00:25:46] So that is real pressure that retailers face.

[00:25:50] I think our advice would be that you really need to lay out the customer journey and your channels and pick where you're going to really make a stride in terms of improving that customer experience.

[00:26:05] What is really important for you, given your business, given what you're trying to do with the customer to make the right investments?

[00:26:14] If you're in home improvement, which is a very project based business, you really want to identify when those customers are starting that bathroom remodel or that kitchen remodel and then connect in your data accordingly and the various channel tactics or even your retail media business into that.

[00:26:32] Versus if it's really about in restaurants, getting digital orders flowing through in an accurate and speedy way.

[00:26:41] You know, you want to line up your personalization accordingly, but maybe also include a human touch with that.

[00:26:47] Like Starbucks recently announced when they said we're going to start writing names on the cup again.

[00:26:52] And that's a critical form of personalization that we can't forget about the human touch as well in this, even with all the focus on digital.

[00:27:00] Yeah, definitely.

[00:27:01] So pick your battles would be my guidance.

[00:27:04] Nobody's doing it all.

[00:27:06] Yeah, yeah, that's a really good point.

[00:27:08] And technology doesn't solve every problem.

[00:27:11] Sometimes it is about going back to basics, as you say.

[00:27:13] Do you think, I'm going to ask you a somewhat controversial question here, but do you think that retailers can go too far with their personalization efforts?

[00:27:20] And I know your points so far have really been about that most retailers aren't going far enough, and I would agree with that.

[00:27:27] But I wonder what the risks are of getting a little bit too personal with shoppers, because I think there's this fine line between creepy and convenient, and that's going to be a personal preference, right?

[00:27:38] So for me, we just talked about grocery shopping and kind of, you know, if I'm buying a bottle of wine and suddenly my phone starts buzzing with offers for things like cheese and crackers.

[00:27:49] I mean, I'm massively simplifying things, but you know, I think that would be helpful.

[00:27:53] I would welcome that.

[00:27:54] But if I was to walk into a clothing store and a sales associate greets me by my first name, I would find that a little bit creepy.

[00:28:01] And I should preface, before I go any further, I should preface this by saying there's huge cultural differences here as well.

[00:28:09] But, you know, how far can we take clienteling?

[00:28:11] How far can we take personalization?

[00:28:14] I think a key point is that shoppers need to be able to opt in and select the level of personalization that they're going to get.

[00:28:20] You almost have to personalize your personalization.

[00:28:25] So what do you make of all this, and how can retailers manage this complexity?

[00:28:30] I don't think there's a clear line.

[00:28:33] And I also think personalizing personalization, just the complexity of that gets to be quite a challenge.

[00:28:40] This is why we have to come back to something Mark was talking about earlier, which is the rapid, the ability to do rapid test and learn.

[00:28:47] And so you've got to try things.

[00:28:50] And the beauty of retailers is they have geographic spread.

[00:28:53] They can pick a city, Columbus, Ohio, for example.

[00:28:57] When I was at Edna, we always tried things in Columbus, Ohio.

[00:29:00] That was just always our target market.

[00:29:03] And so you can try things and see what works and what doesn't.

[00:29:07] It's fairly low risk.

[00:29:08] It's isolated to a geography.

[00:29:10] But you have to have the ability to do that, to be able to measure it, to be able to control it.

[00:29:16] And it's going to take some testing.

[00:29:19] It is going to also take testing from your own perspective.

[00:29:23] You've got to have the customer's viewpoint.

[00:29:26] And also, I think retailers underestimate the value of their own employees as potential customers and focus groups and areas where they can get feedback, testing it to see how their own employees would react.

[00:29:41] So there's a number of things retailers can do.

[00:29:45] There's no question a lot of this could get creepy, but the line does vary.

[00:29:51] And I think it's just something you've got to learn as you go, but tread carefully.

[00:29:56] I would also add in the book we advocate for the notion of zero party data.

[00:30:02] And I think where retailers have gotten themselves in trouble over the years is when they incorrectly infer from first party or third party data.

[00:30:11] Things like someone is pregnant and so I should recommend them this or the like those really sensitive things.

[00:30:21] I think when you ask customers and you get an answer back, then you can personalize a lot more, both with permission as well as more depth.

[00:30:33] But I think there's another key point there, which is once you do ask for that data, you've created that expectation of personalization and return.

[00:30:41] And we find in our research the rates of customers willing to provide personal data go up from 30% to 90% when they're getting a personalized experience in return.

[00:30:55] And that can be an offer, some better value, but it can also be just a more convenient experience.

[00:31:02] But again, are you delivering on that then as a brand every time?

[00:31:07] Yeah.

[00:31:07] And you've just reminded me of there's an example.

[00:31:10] I think it's from here in the UK where a woman didn't know she was pregnant and turned out she was, but the retailer figured it out before her.

[00:31:17] So that probably bears on the creepy end of all of this.

[00:31:21] Yes.

[00:31:22] In the US, we had one when her father learned about it before she called him from the retailer's email.

[00:31:29] So that's even worse.

[00:31:30] Yeah.

[00:31:30] Yeah.

[00:31:30] I can imagine.

[00:31:33] So I have one final question for you.

[00:31:36] What's your vision for the ultimate personalized retail experience and how close do you think we are to achieving it?

[00:31:43] I think we're quite a ways still because with Gen.AI, a whole nother field of possibilities has opened up.

[00:31:50] One of my CPG clients actually told me that they're investing in a giant way in Gen.AI right now, and they predict that in three years or so, a third of their marketing spend will be marketing to a Gen.AI.

[00:32:07] So this notion of virtual assistants or shopping buddies that are going to be informing and driving a lot of our purchases and will be the one-stop shop for us.

[00:32:17] So, and I think that's not a far-fetched assumption.

[00:32:21] Now, in order to get there, I think you need not just chat, but voice, video, image-enabled personalization assistance that can really help customers navigate things like holiday shopping.

[00:32:36] What if I could go to one place and get inspiration ideas, but then also go through the actual conversational commerce and click a one-stop shopping button to get it all delivered in time for the holidays.

[00:32:52] I think that's the technology is already here.

[00:32:56] I think what's missing often is the operational rigor, the ways of working, and then also some of the partnerships and collaborations across companies that are required.

[00:33:07] And justifying that investment as well, right?

[00:33:10] That's always a challenge for retailers.

[00:33:13] Yeah.

[00:33:14] I think the solution-oriented chat capabilities that I talked about earlier are starting to come out, but I think they're also going to have new ways of distribution and access.

[00:33:30] So, imagine, you know, a personal assistant, you book a trip to Iceland, and then the assistant suggests, do you want a packing list?

[00:33:40] Do you want to go to L.L. Bean or someplace like Eddie Bauer and get what you need for the hiking you're going to?

[00:33:48] What are the things you were planning on doing in Iceland?

[00:33:50] Do you want to make sure you've got the stuff to be able to do it comfortably?

[00:33:55] So, I think we're going to see those kinds of suggestive capabilities that, because they're through tools that you're comfortable with using, will pop up.

[00:34:06] But again, that has an ecosystem aspect to it of, you know, L.L. Bean playing with that particular shopping agent, maybe even linked to an airline to suggest things or to Marriott, for example.

[00:34:22] So, the solution-orientation of retail has still got a ways to go.

[00:34:30] But the capabilities are all the building blocks are there.

[00:34:35] And I think we're going to see more and more experimentation and offerings coming out, probably as soon as, I think, by the holiday season next year, no question.

[00:34:45] Yeah, the future sounds really exciting.

[00:34:47] So, David and Mark, thank you so much for coming on the podcast.

[00:34:51] It's been great to get your views and best of luck with the book.

[00:34:55] Thank you.

[00:34:56] Thanks so much.

[00:34:59] Thank you for listening to Retail Disrupted.

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