← Uncensored CMO
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- [00:00]
A
Foreign welcome back to the Uncensored cmo. Now, one of the buzzwords that's gone around marketing for some time is personalization at scale. Is it actually possible to personalize marketing content to lots of different audiences all at the same time? Well, someone that might know the answer to that is the author of a brand new book called Personalized Customer Strategy in the Age of AI, Mark Abraham, who's written a brilliant guide to how to get it right. Now, I've had lots of bad experiences and imagine you have when companies try and personalise things and get it wrong. So I'm fascinated to talk to Mark about how you get it right and how does AI really give us the potential to genuinely personalize things at scale? Here we go. So, Mark Abraham, welcome to Uncensored cmo.
- [00:49]
B
Thanks for having me.
- [00:50]
A
I think every strategy deck maybe for the last 10 or 15 years has said the big trend this year will be the ability to personalize communication at scale. So tell me why this will be the year.
- [01:00]
B
So it's actually more than 10 years. BCG wrote a perspective in 1989 titled a segment of one marketing where we talked about the potential for personalization. And for 25 years, pretty much nothing happened. But 10 years ago I founded our personalization team at BCG and we've been helping iconic brands personalize their customer experiences ever since. First they were able to harness data and predictive AI, but now in the last couple of years you have the game changer of Gen AI coming and I think putting these two together is what's really going to change the game.
- [01:39]
A
That does make sense. Now the problem with researching a topic like this is suddenly I'm hyper alert to my own experiences. So yesterday for example, I was ordering a new pair of. Well, in fact I wasn't ordering a new pair of jeans. I'll tell you what happened. So on Friday, Black Friday, of course we were recording this after, in fact we're on Cyber Monday I think, as we call it this. But anyway, Black Friday has just happened. I was looking at a new pair of jeans. Now I'm very loyal to one brand, it's called Frame. It's fairly new, a new brand, but I'm very loyal to them because the fit's good and you know, I like the customization. Actually there's a gazillion different washes you can get, so I'm very loyal to it. And of course they sent me their Black Friday deals. I'm on the site and I sort of run out of time so I leave it open. And then yesterday I get that, oh, we noticed you were looking at these jeans. They're low on stock, so click here to buy. So I go through, but my size isn't in stock and I'm like, ah, hang on a minute. So you know my size and you've sent me an alert and my size is already out of stock. So I'm a bit disappointed. Then I think, well, they put a little notice saying I'll click here to notify when back in stock. So I'm like, oh, of course, right. That's the obvious thing to do. So I click on that thing and then it obviously thinks I'm a new customer, so it signs me up for a second time. So I then get two emails from them going, we have signed you up to notify you when these jeans come in stock. So I've now got double the, you know, I need to unsubscribe then. And then it sends me a text, oh, we noticed you're on our website. Here's 15% off the jeans you were looking for. I'm like, well, hang on a minute, the jeans I'm looking for are out of stock, so I don't need the 15%. Anyway, I do go on the site and then I think, well, actually I do have a pair to return that I'd forgotten about. So I then fill in the form to return and I get no confirmation whatsoever that my returns has gone through. I've got no idea about timing or anything. So anyway, that was my Sunday evening. It's just one day, one example. As I was thinking about personalization, there are so many points in that chain that have gone wrong, haven't they?
- [03:35]
B
Yeah, and this is exactly why I wrote the book Personalized. I mean, I see it around me and I have my friends and acquaintances telling me about this every day. I mean, you see the inaccurate, like in clothes. You see it all the time. I bought my sister yoga pants and now I'm getting hit up with women's yoga pants emails all the time. I also see it in the. Just hurtful emails, like my friend's dog died and he still gets emails for recommendations for dog treats six months after his dog's death. So you have stuff like that and then just missed opportunities for personalization. Like when do you go to your doctor and you just get the same damn form and you have to fill out your basic information again and again and again. So you see all these opportunities around you. I think there's also ones that companies just use the information incorrectly. They misidentify people. There's obviously the age old example from Target telling the father that his daughter is pregnant. But you see it in every market in every country around the world. And in fact, when we surveyed customers about this, about 2/3 of customers said they had an inaccurate or invasive experience using personalization.
- [05:03]
A
So let me get that again. So 2/3 of customers said they had an inaccurate or invasive experience. That's pretty bad.
- [05:09]
B
Yeah. And it's not that customers don't want this because actually 80% of customers tell us they would like an experience that's personalized, that's taking into consideration their needs, their data. And as one customer that we talked to told us, I may not have chosen to live in the world where brands have this much information about me, but I do. And I know that when I go on Amazon, I get that experience and I want every brand to use that information about me. So most customers, and this is consistent in every market around the world.
- [05:44]
A
I was wondering about the customer data because personalization is something we probably most of us wish happened. But on the flip side, it can feel a little bit spooky. It's like you'll be chatting to your friend about one day, I'd love to go to Morocco, and then suddenly you're served up a oh, here's a deal for a flight to Morocco, going tomorrow sort of thing. And it can feel a bit invasive. But what does the consumer data tell us about people's kind of openness to personalization?
- [06:09]
B
So, so when there's a clear exchange in terms of your experience will be personalized in this way, and here's why you're giving me that data. The rates actually jump up significantly in terms of customers that are willing to give their information, from 30 to 90% in fact. The key though is the brand actually has to deliver on that. And that's where I think we get into trouble sometimes, where either the data is just not used at all. You'll have maybe your home improvement store ask you or identify you as someone who's moved. Well, then they'd better use that information to give you relevant recommendations and products and recognize that that's the case. Sometimes the data is collected on one end, but the rest of the company doesn't quite know what to do with it.
- [07:01]
A
I mean, this must be a big problem. I remember a couple of years ago I bought a new pair of Ray Bans. I'd done quite a lot of research into the style, the color, and I'd finally sel to the ones that I really liked. And it was that moment that I got inundated with targeted ads about Ray Bans. I'm like, hang on a minute, does someone, do they not know I've just bought it because now I want to switch it off? It's annoying now because I'm like, I've already got the ones I want.
- [07:22]
B
I had an even worse one where I got a brand new dishwasher after nine months because it was Covid so it was delayed. And then I got hit up with more ads for dishwashers as well as emails. And by the way, the one I got was broken, so I had to wait for a replacement while I was getting all these emails.
- [07:42]
A
Even more annoying.
- [07:43]
B
Yeah, exactly.
- [07:44]
A
Well, let's talk about the business case. I mean, in your book. By the way, congratulations on the book that's just come out. Thank you. You put a pretty big number out there in terms of business case. You talk about a $2 trillion opportunity. Now I think every year about a trillion dollars is spent on advertising. So this is twice the size. And that's over a ten year period. I think you put in the book five years actually. Five year period. Oh, even better. There we go.
- [08:04]
B
That's right.
- [08:04]
A
How do you arrive at such a big opportunity and can kind of why there is such a big opportunity to get this right?
- [08:10]
B
Yeah. So one of the issues with personalization has been it's an overused buzzword and there really hasn't been a way to measure it. So we came up with what we call the personalization index. So it's a basic score which we did tons of research on and we scored hundreds of companies mystery shopping the experiences across channels and then also looking under the hood of what data, what technology, what processes these companies use. And so we scored all these companies across industries around the world. What we found is that only 10% of companies are personalization leaders. Now the good news is these companies exist today across all industries. So there's pioneers figuring out how to do personalization well in almost every industry, but it's only 10%. So we looked at next, how are these companies performing? And the most surprising result, I think was that personalization leaders are consistently growing 10 points faster per year in terms of their top line revenues than laggards and about six points faster than the average. So you play that out across industries. These companies are taking share, they're growing the market. And that's where we get to these numbers of retail alone, for example, there's a half a trillion dollar opportunity that personalization leaders have to capture share and grow the market and then all these other industries likewise. So it adds up to 2 trillion. That's a big number.
- [09:44]
A
That's a very big number. And can you link, so you're talking about growth rates, can you link that to share price in terms of shareholder value as well?
- [09:49]
B
We actually did the analysis on total shareholder return as well and the number is 15 points. So the gap between leaders and the market average is 15 points of total shareholder return per year. And that has held pretty steady over Covid since COVID and so on.
- [10:09]
A
Now one thing that kind of struck me is do you think that varies by category either in the ability to personalize or the kind of return on personalization? Because if I think my morning experience I'm talking to a financial services company, I expect them to know me and to adapt to my needs. Maybe if I'm buying a can of drink, I'm not so bothered. So are there sectors where the prize is bigger and are there sectors as well where it's being done better?
- [10:34]
B
So certainly so far the digital natives across industries and retailers have captured the most share, usually because they have all these direct customer relationships. They have specific interactions with customers that are quite frequent. But I think what's really changed in the last two, three years, even since we've been doing this research, is more regulated and longer life cycle industries and starting to really take advantage of this prize. Banks are a great example. So you have companies like bank of America, for example, came out with their Erica tool, Genai tool that helps you navigate your financial wellness journey. You have even benefits providers like Voya is a large insurance and benefit provider company. They launched a tool called MyVoyage. They ask you what your retirement goals are and then they give you in depth recommendations on how to achieve them. So in these industries it's more about engaging customers and creating these platforms or moments to engage them beyond just selling them stuff. If you're a bank and all you're doing is pushing mortgages and savings accounts and the next investment product onto your customers, chances are it's not going to land at the right time or with the right customer. But if you are engaging in this ongoing discussion with your customers now, they're going to you throughout their life cycle and chances are you're going to be there at the relevant moment.
- [12:09]
A
It's actually one thing that struck me about your book. You have so much focus on how you create value for the customer rather than thinking how do I sell more? Which is a subtle difference, isn't it? But we often forget because we're so focused on how am I going to push more onto the customer. Whereas the other way around should be how do I use this data to give me intelligence, to make my customers life easier, better, you know, more convenient, whatever it is, kind of thing. That's a really important difference, isn't it?
- [12:32]
B
Huge difference. And you know, one of the examples I love the most is we worked with a large airline, one of the largest in the world, in fact, and they had 50 different P and L owners. You know, you can think of like flight destinations or the credit card product they were selling, or they were selling travel insurance and so on. And all these P and L owners created targeted campaigns to talk to the right customers about their product. And they had a really sophisticated data science team targeting these campaigns. But when you added it all up, the best customers were getting blasted. They were getting like 10 emails a week. And then the not so valuable customers got nothing. So we flipped that on its head and we said, what if you took a Netflix approach? Create a content library just like they have the movies. We had our products to speak about. But by the way, other things too, to engage the customers. Like, oh, you had a flight disruption, here's some service to help you with that. Or preempt your questions and then figure out what is the next best thing to talk about for every customer. And that approach massively increased engagement, increased conversion for the product, with actually sending half the messages.
- [13:49]
A
Oh, that's very interesting.
- [13:51]
B
So it's a great example of how modern marketing can work.
- [13:54]
A
Yeah. I mean, even in that example, one of the things you touched on is maybe the role of partnerships as well. Because the other thing, of course, if you're looking at just the data you have on your customer, I guess the first party data, isn't it, or the zero party data. But if you, if you can build in data from other, other places that starts to build a complete picture of your customer, then you can do some really amazing things.
- [14:15]
B
Yeah, this was a great example of that because they had partnerships with the major banks, even some of the largest retailers, and actually they were using all of this data to get a much more complete picture of their customer.
- [14:28]
A
Yeah. Now I wanted to ask you about speed and scale, Right. Because. Because you break this out as the source of competitive advantage. Just explain a bit about where the competitive advantage lies for businesses.
- [14:38]
B
Yeah. So I think this is the key. Personalization is the way to use AI to drive growth, as we just discussed with the $2 trillion prize and the way to do that is through scale, meaning you need just lots of digital customer relationships and interactions with customers and speed. You actually need to understand the insights from those interactions and then turn around and change the experience, make it a little bit better, a little bit more targeted, a little bit better for each customer. So it's actually those things can be in conflict because big companies, they can have a lot of digital customer relationships and companies that have frequent interactions will have lots of them. But then they need to be nimble. And that's what digital natives, startups, smaller companies are typically better at. So the basis of competition is changing and companies need to think, bring these two things together.
- [15:38]
A
Yeah, it's a good point actually, because if you're small, you're going to be nimble, but not other data. If you're large, you've got the data, but you're not nimble. So in a way there's a race, isn't there, for the small one to get access to more data to make them more informed and the big companies to try and move at speed. Actually talk about AI, because the answer to the first question about why is it now the time that we can do personalization scale, presumably AI is the thing that's making all this possible. That wasn't before. Would that be correct?
- [16:03]
B
I think it's a couple of things. So certainly with AI number one on the predictive AI side, which has been around for a decade or more, we've made huge improvements in terms of the algorithms, the machine learning capabilities across organizations. But then we have Genai on top of that and I think you're going to see the front end interface through which customers interact with personalization change. In the airline example I gave you, it was still the airline pushing personalization on the customer. Well now if you go to Expedia or even just ChatGPT, you can create your own trip or vacation itinerary and you're gonna see that become even more tied to things that you can buy in that experience, recommendations you can get or gift to your friends. And those things will be tools for customers to pull personalization when and where they need it. So that's the piece on AI. I think the other piece that's happened with and through Covid is the massive leap we've made in digital interactions and more digital interactions. The growth of digital channels and the share of digital channels means we have way more data about customers that can be used at scale for this. Then the third piece is, I think some companies, especially the personalization leaders, are finally figuring out how to really create these nimble teams that are able to make rapid progress and every day or every week optimize the experience.
- [17:40]
A
Graham, that's your first point there. I hadn't thought of it from that way around is that I guess you might assume that we want to use our data to personalize our communication to our customer. The first one's quite interesting because basically you're going to where customers are personalizing for themselves with new tools. How can you show up there and be helpful and useful and embedded in what they think? That's a different way to think about, isn't it? From a customer's experience, backwards agnostic of whether they use your platform or not.
- [18:06]
B
So one of the most fun parts of the book to write was the last chapter where we talk about the future of personalization. And I think this is the piece that has yet to play out fully. In our survey with CMOs, we saw 70% of them are using Genai tools to drive efficiencies. Things like content generation or copywriting or translation and the like, where they are not yet threading it through and really scaling it. Is personalization, meaning creating customer facing experiences that fully leverage this technology. It is harder because you've got to have the security right. You need to make sure it's not hallucinating, you've got to set up the data and the content right. But you're seeing the beginnings of this, like L'Oreal Beauty Genius or Expedia's Romy tools are helping customers discover beauty occasions and beauty products, or in the case of Expedia, travel experiences in new ways. I think where it gets even more interesting is when these companies start to really partner and think about ecosystem solutions that solve your holistic beauty needs or your holistic travel needs in one place. And I think that's where the game's headed. Who will first launch those is I think an interesting question. Will it be the big large platforms, tech players, or will it be the brands or will it be brand new startups? You're going to have complete new business.
- [19:35]
A
Models emerge and then you will need partners. Right. Because you won't be able to do that unless you partner with the full supply chain. And you might even have to collaborate with your competitors as well to provide a service that's genuinely useful to customers.
- [19:47]
B
Exactly. It's kind of like a marketplace of experiences.
- [19:50]
A
Yeah, yeah, completely. Just stick on AI before we go into a bit more about personalization. So the thing I find with AI, I speak in my day job, speak to so many companies Right about this. And every big business wants to be leaders in AI. How many of them are actually leaders in AI? Not very many. It's like if I got paid a pound for every time someone said, we want to be leaders in AI.
- [20:13]
B
Yes.
- [20:13]
A
Okay, you and everybody, you know, that sort of thing. And you look under the hood and say, if you actually are. There's a really big difference between those that are genuinely doing and those that want to be doing. What sets out what marks out the companies that really are leading. What are they doing that makes them leading in this space?
- [20:29]
B
One of the things we advocate in the book is really aligning on the vision. And I think that's critical with AI as it is with customer experience. Because typically I talked to so many companies. Like I was talking with a bank where they said, we have 400 AI use cases across the company that we're launching. And I asked, how many have you scaled? Zero. I think that's a really typical response because there's a lot of innovation and good work happening. But what is the vision? What are the big bets we're making? And how do you align the cio, the cmo, the Chief analytics officer, chief Data Officer around that? Vision is really critical because you need to focus resources. So that's number one. Number two, having someone that is owning the roadmap is super important. I was just in a workshop here in London a couple weeks ago, and one of the big AHAs as we engaged with clients across sectors was only one of the 10 companies at the table had an owner owning the roadmap. It's not that that person controls all the resources, but they need to be able to hold organization accountable. We said we would launch this by this date, and we did or we didn't, or we will or we won't. And flagging those things, raising it early, holding the organization accountable not just for the milestones, but the financial results, because these are huge investments. And the cfo, if they don't see results, rightly won't be funding the next phase of the journey. So that ownership is key. And then lastly, I think most companies still struggle with the unit of the team to make this happen. Agile is an overused word as well, just like personalization. But most often where I find companies triple up over this is they'll launch an Agile team and then it becomes 50 people across functions trying to work together, and they can't even get a meeting on the books to talk about stuff, let alone make progress. How do you whittle that down to a two pizza team, as Amazon would call it. Right. And eight to 10 people who are doers who are making progress, key KPIs. And yet a size of prize for that team to go after that's going to be meaningful enough so the investments pay off.
- [22:57]
A
Yeah, I think so much of the answers here are often, they're not technology. They're often organizational, aren't they? That's often the blocker. It's not that you can't do it, it's that have you set yourself up in the right way and given permission and put in the resources in the right place to make it happen.
- [23:11]
B
And that's why in the playbook we lay out for personalization in this book, we really encourage companies to start with that customer problem. How are you trying to empower customers? Is the first question we ask and then thread all the things around data, technology, people, the processes against that.
- [23:32]
A
Yeah, well, I found this very helpful, actually, when I was reading the book, because I think so much, it doesn't matter what the technology is. So many companies go, we want one of those. We've got to do something in AI, isn't it? And they almost start with a sort of the supply of it rather than demand of it. It's like, well, what problem are we solving for the customer that this can be the answer to? Rather than going, we can build it. Who wants to buy it? This is like the opposite way of thinking.
- [23:55]
B
That's right. And that's why I say, ask yourself, what are you trying to use personalization for? And I think every company that uses personalization ultimately makes a promise to the customer, in fact, a set of promises to the customer, and they've got to hold themselves accountable to whether they're delivering that.
- [24:17]
A
Now, in the book, you usually kind of break out five areas, don't you, in terms of how to build the framework for personalization? What are those five areas exactly?
- [24:26]
B
So, great segue because these are the five promises of personalization that companies have to deliver on in order to do great personalization. And it starts with empower me. So take Spotify as an example. You know, they're promising that you will have a great music experience and you're going to find the right tunes for you for that occasion. So that is the promise they're making. Second, you need to know me. So Spotify needs to tag not just me as a listener, but all the data they have in their music library around what genre is it? What, what's all the metadata around that song? How much did I listen to it did I skip that song, et cetera. To really know me as a customer. Next, they need to reach me. So what channel, what time should I contact that customer? This can be in the app in the case of Spotify, but they might also notify you via an email or a push notification if your favorite band is in town for a concert. Next, they need to show me. So Spotify is a great example. Again, with their giant music library. They have rich content, more content than customers could possibly ever listen to. So companies need to think about that if they're truly going to personalize the experience. They need to adopt this Spotify or Netflix approach of creating a content library that's actually bigger than their customer base. Then lastly, and this is the most important promise, delight me. This means you're making it better every time. So Spotify as an example again launched DJ Xavier, which is kind of their next generation of genai tools built into Spotify. And it more than just recommends the song in the app, it actually introduces why it's recommending a song. It might say here's something you listen to a lot two years ago you haven't listened to in a long time. Or it might ask you for your feedback right in that moment and then adjust what it's delivering for you. So how do companies create that kind of built in optimization, both in the tools as well as the way their team works behind the scenes?
- [26:46]
A
Yeah, that's a lovely framework. I like how that flows. Let's break it down a little bit. So if you start with empowerment, this is all about how do you create information about the customer that could be useful? So how would you go about getting that information? Where is that information, what is it? And there's a raft of like zero party to third party data. So where do you get the information? How would you get that together to give you the kind of insights that enables that?
- [27:09]
B
So what I advise clients is most companies have a wealth of data about their customers and in fact you can find natural pathways that customers are taking in their journey with you as a brand. So take a beauty retailer for example, we worked with. They found there were less engaged customers that were shopping across a bunch of brands. They were really only coming in for the holidays. You could see this in the customer data they had from just their store, transactional data. Next we found a group of customers that were coming in more regularly throughout the year. They were buying less on promotion, they were shopping one category. Then you found people that were shopping multiple categories, not just hair, but lipstick and other products. Next, you found customers that were members of the loyalty program and had the app downloaded and visited with their friends. And each of these customer segments basically formed an engagement ladder when you put it all together. So as you stepped up the ladder, you had lower churn rates, higher loyalty, higher spend. That's a great example of how companies can mine their customer data to come up with where can personalization really help nudge customers and to hire brand love, but also higher revenues for the company. And I think those are the ways that personalization can really help.
- [28:42]
A
Yeah, One of the challenges, I imagine you got this slightly amusing example in your book of where in different data sources integrated and they couldn't even work out the gender, could they? Which is quite shocking. But actually share that example is quite a funny example.
- [28:56]
B
Yeah. So you go back to my, where I started with the women's yoga pants, I bought my sister that holiday gift and then I get tagged the wrong gender. And in that case it was the first party data. But I've seen clients use third party appends and we've tested that for a specific client where we used one of the common data providers for demographic data. We matched it up against the company's internal first party data and what customer self reported it was about a 60% accuracy on gender. So basically not much better than 50.
- [29:36]
A
50, right?
- [29:36]
B
Exactly. You could have just done a coin toss and it would have been almost as good. And this is data that the company was buying. So really ensuring that you're buying the right data, you're testing it for accuracy is so critical and asking yourself if it's truly that important for the experience, how do you build it in so that customers give you what I call zero party data? So you're asking the customer that question and the flow of the experience again from an apparel perspective, you have Stitch Fix for example, that sends customers boxes of apparel and they start with a style shuffle they call it. So instead of trying to infer does more like trendy clothes or more traditional style clothes, they'll actually ask you in an interface to kind of rate things you like and don't like and based on that determine your style preferences.
- [30:36]
A
What I love about that is that's actually making it fun, gathering data. If you make gathering data fun and then you can make it useful, you get far more likely to get people to adopt.
- [30:45]
B
That's right. And I think too often companies think, well I'll create a preference center over here where customers can go and fill in things. Well, if it's not part of the flow, you find like 1% or 2% adoption rates and then you don't really have enough data to do anything with. So how do you make it part of that flow and make it clear also, how is this going to make my experience better? So in that case, you know that your box that's going to come is going to be informed by the style choices you've just made.
- [31:17]
A
One of the online services I sign up is Buttonup box here in the uk, which is like a home delivery pet food. Basically, first question they ask you is, what's your dog's name? So immediately they're touching on something deeply personal and you know, when's the dog's birthday and things like that. So immediately you got some, you know, got some data that's going to be kind of personal.
- [31:36]
B
And in that context, that's a great question to ask. And as a customer I'd want to give that. I think where brands sometimes get into trouble is if they don't think through the experience. For example, if you went into a store and the shop assistant you've never met suddenly greeted you by name, that would be pretty weird.
- [31:53]
A
Awkward.
- [31:54]
B
Yeah, exactly.
- [31:54]
A
That is weird. Now, with all the data you're gathering together, what kind of intelligence are you, what's the most useful kind of intelligence you're gathering to help you kind of grow and make better decisions?
- [32:05]
B
Well, we now live in a world where we can't rely as much on third party cookies and third party data in general. And so really, in addition to the zero party data that we just talked about, first party data has become really critical. And most companies have a wealth of transactional data. So obviously they need to fully leverage and mine that and connect it in, in the right way. Where I think companies under leverage data is the engagement data. So every day, customers, even in infrequent categories, they might be giving digital signals, they might open the app, they might click on things, they might not click on things. All of that is useful information and it's frankly more data than most companies know what to do with or can even harness and tap. So really thinking through which of those data signals need to be part of the models, building features on that data set and then ingesting it into the models is critical. But again, the key is to be clear, what are you trying to do for the customer? What data would I need to know and how much of that do I actually have?
- [33:14]
A
I mean, a good example I'm reading about was, was Woolworths, the Australian retailer, because I think, as you point out. Anyone who's worked in retail will know you operate on crazily tight margins. So how you use your data is the difference between being profitable and not kind of thing. But they've invested heavily, haven't they, in how they use their loyalty card data.
- [33:32]
B
It's a massive area we're seeing with grocers around the world. Personalized offers is an amazing tool for getting better returns from the billions and billions that are spent on promotions, mostly in a mass way today. In fact, in most markets around the world, only a couple of percentage points of that promotional spend is personalized and most of it is spent on mass events. So what Woolworths has done, and frankly many leading grocers around the world are doing right now is really building personalized offers at scale, both for their own promotions. So now they can have for any given product at the SKU level or brand level or at the store level they can set how much of the discount do they give to this customer in this week? They've even got challenges where they make it fun. They ask you to buy a few things or come a few times or a period of time and then you get more points. And points is a great way to engage customers in many markets around the world as well because people just value points more and they want to see that balance build. One of the key reasons people go to that app in the case of Woolworths, is to check their points balance. So they've gamified that experience and then the other cool thing they've done is they've engaged suppliers in this. So to your question on if I'm selling sodas or fizzy drinks, actually a great use case for personalization is tapping into this kind of capability with a retailer like Woolworths. If you can spend your promotional dollars targeted, the right customers that are going to either discover you as a brand, switch maybe from another brand, or buy you on occasions they might not have before. Those are great opportunities for you to get. In fact, 3x the returns we found in all our work versus just spending it in a mass way.
- [35:36]
A
I had a similar experience actually, client side with Tesco in the uk. Had a bit of a challenge on my hands. I was overseeing Lucozade and we were going through a big sugar reformulation and we ended up with a big backlash. And what was interesting is my club card data. Tesco club card data was immediately reflective of the problem we had. My brand tracking data was six months behind and it was really fascinating. So I, you know, I could see in the club Card data because it updates daily. I can literally see people not responding to the normal promotion, where they were, who they were, you know, what they're buying, habits, what they're also buying. So when it came to do something about our issue of having lost a big chunk of our customer base, we could be super targeted in who we're targeting, where they are, what kind of offers would get them back. And I found that the club card data, back to your speed point, we could operate so quickly and we could adapt our kind of promotion to suit it. Compared to the traditional brand tracker, I think it was about nine months before it even suggested we had a problem.
- [36:37]
B
Not only are you seeing that data faster, but I think what's changed even in the last 12 to 14 months with these retailers is we've seen them scale the content and automate it. So now big grocers can launch hundreds of thousands of variants of these promotional vehicles and actually change that every week to who they're targeting based on the data. And that's where you could never do that with a mass promotion that you've printed on all the labels and the signs in the store.
- [37:11]
A
Well, this is going to be my question because before that or back in the day, you'd often be at the till and then it would print out a coupon right at CVS in the.
- [37:22]
B
US it actually prints this mile long receipt with all your coupons.
- [37:27]
A
The crazy thing about it is I've never been more excited to have 10p off carrots. You know, I mean, it didn't matter what the offer was. The physical experience of being handed this, this long strip of multiple offers on random things anyway, bit of nostalgia, but sometimes the way it's delivered, it doesn't matter how much. Discount is just the theater in which you deliver. It can be important. But you touched on a really, really good point. Because if we set up organizations to allow us to change our message to every consumer on every occasion, in every moment or whatever, suddenly the marketing department has got a challenge on their hands. Because suddenly the campaign they created, their single campaign, has now got to be adopted thousands, maybe even millions of times. So how do you kind of connect those two things together without kind of losing the quality of what you're doing? Because I guess the danger is you end up dumbing down to lowest common denominator, just changing the kind of headline. But how do you kind of solve for that problem of now? We need to communicate lots more messages to lots more people and still with the kind of engagement levels that we might have done before.
- [38:29]
B
So this is one of the first problems we solved when I launched our personalization team. Starbucks at the time had their Frappuccino happy hour offer right in May. We always talk about Frappuccinos to everyone and I think that's emblematic of most organizations. Category teams will try to push their products. Well, only about 30% of Starbucks customers actually ever want to buy a Frappuccino. And so you're really sending an irrelevant message at best to the other 70%. And this is where if you can create a flexible, templated, dynamic message that actually has space in it for every product. In the case of Starbucks, there's 87,000 plus products you could talk about, maybe with an offer or maybe it's just a recommendation. You multiply that out, you could have hundreds of thousands of variants from dynamic messages going out to customers. And it's actually, I mean, this has been possible for a decade now to do this with technology, with Gen AI, it's even easier because you can even have the images varied and the Persona of the customer come into the email you create or the ad you create. And that's what companies are doing. And again, with that approach, we have seen triple the ROI on promotional investments, ad investments in this area.
- [40:01]
A
It makes sense because actually my local barista knows that there is no temperature that's so cold that I won't also have a Frappuccino. So honestly, if you're advertising Frappuccinos in May, I was buying them in the middle of winter, you know, it was minus 10. So I'm living proof that that's the case.
- [40:18]
B
Yeah. And actually it's interesting, the whole coffee market has moved towards cold and more indulgent beverages in that regard. So part of it is our ability to discover all these beverages.
- [40:29]
A
It's like the macro versus micro, isn't it? At a micro level, of course, Frappuccino. Frappuccinos peak in summer, of course, you know, but then there'll be a whole bunch of, you know, people like me that are very happy with Frappuccinos in the winter.
- [40:39]
B
Yes. And young people now order cold drinks throughout the year. Yeah, on average.
- [40:43]
A
Exactly.
- [40:43]
B
But then by individual, it could be different.
- [40:46]
A
It's good. Good to see I'm on trend then. Exactly.
- [40:48]
B
There you go.
- [40:49]
A
But also actually, in my day job at System One, there's some good evidence for how this works as well. I mean, nowhere near complexity you're talking about, but we did this project for a regional airline in the UK called Jet2, and we measured the Emotion that people felt looking at something that was generic, so targets everybody. Something that was regionally targeted. Regionally and personally targeted. So imagine, I mean, in fact, they've got a great, They've got a really good campaign. It's kind of a couple going on holiday. It's actually filmed from the first person. So you see the girl dragging the boy's arm into the pool to the restaurant down the shops. So it's her perspective looking at him kind of. So it's beautifully done, it's got a great soundtrack. And then these are round numbers, so I won't give the precise numbers, but we got a five point scale.
- [41:34]
B
Yeah.
- [41:34]
A
And they got three star, which is pretty good for the generic ad. When they then, I think they then went regional and said, oh, now flying from Leeds Bradford Airport and then served it in Leeds. Right. Went to four star. And then when they targeted young couples, because they had, in fact they had loads of different versions of this. There was an older couple, there's a family, there's the, you know, they had lots of different version execution. So when you then married the audience who saw themselves in it, the airport they live near to and the time they want to go on holiday, which actually is the winter. So advertise holidays in the winter because that's what everyone's thinking. You know, I'd want to get away from here. All those things took it from three star to five star. So, you know, there's a power in terms of, you know, making a correct emotional response. The memory that comes from getting this right.
- [42:20]
B
That's so funny because we did the exact same thing with Asia Pacific Airline and we saw 20% increase in conversion from those exact things where you were flying to and what type of Persona were you, a weekend warrior or family. And the background, et cetera, it makes a huge difference.
- [42:39]
A
Yeah, it really does. It really does. Now, let's talk about some of the barriers, because as I read through your book, the business case is very strong. Of course we want to personalize, but there are lots of reasons why we don't get this right, don't we? So let's break down some of the reasons. I think the first one that you talked about in the book, which I think is enormously important for marketers out there, is the fact that businesses are siloed in terms of department, because as you've talked about the solutions, the solutions involve more than marketing. So if I'm talking about my crazy development or if I'm talking about my media buy, that's on me. As the cmo. Right. I own that. And what I say can be implemented straight away. You're talking about the customer experience now that touches so much more of the organization. So how would a CMO get through that? Kind of having to align the whole organization behind this?
- [43:27]
B
Yeah, I think that's the critical bit is that personalization is a new way to compete. And so that's not just on the cmo. It's really a CEO level agenda and it impacts the entire C suite. So in the book we go through the role of the C suite and every single leader has a role in this. I mean just think of the cfo, they're underwriting the business case and they need to be able to stage gate this and understand should they release that next tranche of investment. Because we're typically talking millions of dollars in people. Technology, data costs. But then you got the other parts of the organization too. The chief data and analytics officer has to make sure the data is flowing right. There's data governance. There's a common definition of simple terms like who is a laps customer. So many clients I have, they have five definitions and five teams going about it in different ways. You've got a disjointed experience, you've got the cio. There's always a shortage of technology resources and so much of this does depend on technology at the end of the day. So how are they aligned with the roadmap and the vision and allocating the resources against this? Those are just a few.
- [44:39]
A
But there's, I mean again in my experience of system one, actually there's a, there's a magic between the customer person charging customer or CMO and the product development team. So the people that can make it and understand what's possible and how, how to use the data and how it can all turn into products and the people that understand the needs of the customer. I mean, you know, other departments have a really important role and need sponsorship. I found those two. It's almost you need to create an alliance with your CIO and put those two things together. Because often they're one's a supply and one's supply and one's demand and those two don't meet. But I think a lot of this is getting those two departments together, isn't it?
- [45:18]
B
It's so true. And I think it plays out differently in different industries, which is why some companies have made more strides than others historically. And digital native companies, typically you'll have a digital product organization that can build stuff fast and launch as things, things fast and, you know, has that nimbleness built into it. But then they might not think about the marketing or communication aspects of it. So how do you get those teams partnering in a large bank? Typically every channel is put in a different part of their organization and then you've got the matrix of different categories and products against that. So how do you bring that together? In a retail example, you might have the CMO again controlling the customer, but then the digital experience, like the website or the app, sitting on a separate team. And then you might have the core systems even sitting in separate teams. So again, how do you bring that together? I think consistently the answer to me is develop a clear roadmap, align the senior leaders and then break it down into small use cases. This is why we go back to empower me. How are you going to help the customer in the next six months in a scalable, a demonstrable way that actually drives impact for the customer and the business and then align that team against making progress.
- [46:41]
A
And I think almost in every case study you talk about in the book, there is this, we set this vision out, we want to do this. But then there's this test and learn phase, isn't it, where they're kind of experimenting on one thing, learning about it, and that builds confidence in the business, then to kind of roll it out, roll it out and scale it up.
- [46:55]
B
Yeah, for two reasons. One is oftentimes you need to build the case for change within the organization. Just going back to my airline example that I gave earlier, we had to change the way all these 50 product groups were communicating to the customer. That was massively risky. And we knew maybe some product groups actually could communicate less and might be worse off. But even if the enterprise was better off as a whole. So by having this personalization lab approach we called it, in that case, we could test and learn what the impact would be for 5% of the customer base with this new approach where it was much more next best action, leveraging a common content library and then go back to the organization to say, this is the impact. This is how we need to adjust our targets by product. And by the way, we learned a lot about how we need to re engineer the content production process as an example to enable this kind of approach. So when we had to drive the change with hundreds of people instead of a dozen people, we knew what the changes were.
- [48:04]
A
Yeah. Now we often think that the block is technology, whereas actually you had this quite neat 70, 30, 10 rule no. 70, 2010. So I get my maths right 110% would be quite impressive. But yeah, the 702010 rule which actually puts the spotlight on it's often people and process, isn't it that that's the bit you've got to fix first.
- [48:21]
B
Yeah. At BCG we've done a lot of AI transformations and this is the rule. 70% of the time these transformations fail because of people. 20% technology, 10% data. So it doesn't mean data and technology are simple. We'll get to that and there's a lot to get right there. But it does underscore just how complex the people changes and upskilling the people getting them bought into change re engineering these processes for speed.
- [48:53]
A
Now I think probably the other thing that people sometimes worry about in this space is the whole risk data, risk compliance, data quality. There's a whole world of. I mean I know I've been in a few deals with some of our larger customers and it's been months of legal negotiation about who owns the data and when consumer data is transferred between one organization to another, what does that mean and who can see it and who can't see it sort of thing that there's quite a lot to consider, isn't there, in terms of both data quality but also the risk and compliance to the law and so on?
- [49:26]
B
Yeah. So I mean I deal with that all the time. In terms of the data access, I think the key there is obviously there's the regulations that vary by geography and they're constantly evolving. I think what the smart brands are doing is giving customers transparency. Marriott is the example we give in the book, for example, where they make it easy for you to go in your Bonvoy app and see what data they have about you. Every customer has a right to be forgotten under GDPR and many other jurisdictions, but actually giving people an easy place to see what even they have about you is a great way to build that trust with customers. LinkedIn is another example of a company that actually you can go in and download all your data that LinkedIn has about you and easily transfer that and leverage that as a customer. Another way for them to build that trust with customers. I think where it's evolving even more though is Genai. I see a lot of companies taking different approaches in terms of how open they are to innovation around Gen AI and the security around that, the risk management of that. I think the worst thing you could do is like some of my clients have done, implement a blanket ban on these tools. I think companies have to force themselves to find ways to safely experiment with the tools, because the truth is the skills of their own workforce and how relevant they are in the marketplace will be driven by their ability to leverage these tools. And I'm seeing a huge bifurcation in that.
- [51:08]
A
That's really interesting because I've spoken to a lot of the world's biggest tech companies, all of whom want to lead on AI, most of whom ban the open source AI platforms as well. So there's a conflict coming there presumably, isn't there, in terms of who's going to win out and who's going to. I suppose they're all playing a game of, you know, that they're backing their horse, aren't they, to be the winner. But presumably only one or two platforms will end up being the dominant in the future.
- [51:34]
B
Yeah, there's definitely a network effect here. I think fundamentally though, here there is a piece on the LLMs can be leveraged for understanding English language or whatever language requests. But then the source of that data needs to be the company's proprietary data in many cases when you get to the specific use cases. So if you're wanting your customers to discover products for your beauty needs or travel needs, well, what is the source of that inventory of products, experiences that you're serving up to them? That should come from proprietary content and data systems that the companies have. So it's architecting those in the right way where you can resolve some of these concerns about security, safety, etc.
- [52:28]
A
Yeah, but back to your previous point, the opportunity might be then collaborating with other systems as well and then also where the future may go to which is more open source or people creating their own personalized experience and you need to be part of it rather than pulling everyone onto your own.
- [52:43]
B
Yeah, and that's where I think just working with companies, for example, in the entertainment domain, there's very much clear concerns from artists and others creating content around how is Genai going to be used to infringe on their copyright and all the work they've done into their products. So some of the companies are taking very conservative approaches to these tools. I think how you get around that is to say, well, you can use your LLMs to the large language models to understand the requests. You know, here's what I'm asking the tool, but then again, query the actual copyrighted content and database underneath.
- [53:29]
A
So funny question, you've written the book on this. You've had over 100 customers, I believe, kind of BCG has partnered with over 100 customers, deliver personalization programs globally. What would be your advice to somebody that's listening to this thinking I need to do this better, I need to lean into this. What should they be thinking about? What should they do? Obviously read the book and give you a call that's taken as red.
- [53:52]
B
Yes. But also ask yourself the questions in the book we tried to make it really practical and in each chapter that goes through the five promises, we arm you with questions to ask yourself and ask your team. Because most companies I find say we're already doing personalization. But when you ask yourself those questions, I think you might find maybe there are some things to do better. And that's what the personalization index results results suggest as well. I think the most critical ones are do you have a clear roadmap and is it broken down into these six month chunks or more often where you can show real business value as well as customer value to fund the investments and then what are you doing next and what are you doing now? There's no shortage in any client that I go to of ideas for how to do more personalization. Typically we'll get a cross functional team in a room and within a couple of hours we'll have the entire wall full of stickies with use cases and ideas. But which of these are truly going to change the customer experience? Where is personalization really critical in that journey for the customer and which of these will drive material business results so you can fund the journey? Those are the questions we ask and I would say pick those few big wins and get started on them now once you build the momentum. And most companies are already on this journey but some of them have lost a little bit of the momentum because maybe those first use cases just weren't big enough, material enough, or they didn't make progress on them fast enough. So I think there is to your where you started this whole discussion, some CEOs I talked to are jaded with well I heard about this personalization effort the last five years and we've spent all this money but what have I gotten for it? I think that's where again, having that clear owner who's holding the organization accountable can be a game changer.
- [55:57]
A
Yeah, well, it's a bit like the barcode 10 years ago. Sorry, not the barcode, the QR code 10 years ago everyone was saying it's going to be the big thing. We then went off it and then pandemic hit and suddenly everyone's using it sort of thing. So there's definitely a timing element, isn't it?
- [56:11]
B
And I think the same risk exists with Gen AI. If we only focus on using AI to drive efficiencies and cost savings. I think we will tire it of it very quickly. So how do we use it to drive growth to improve the customer experience and personalization is the way.
- [56:30]
A
There you go. Well, couldn't put it better myself. So what a great place to end. Mark, thank you so much. Really appreciate it. Thanks for your book, of course, and thanks for sharing your wisdom on the podcast.
- [56:38]
B
Thanks for having me and excited to share it with the world.
- [56:41]
A
By the way, it's also bright yellow which is a color that I endorse heavily.
- [56:45]
B
Yes, I love walking around. We just launched in all the Hudson's bookstores across the airports in the us so wherever I fly around the country, you can't avoid it.
- [56:54]
A
It's like a big highlighter pen through the bookstore, so all my friends are.
- [56:58]
B
Sending me texts with it. So it's super fun.
- [57:01]
A
Brilliant. Well enjoy. Take care. Thank you very much for listening or watching Uncensored cmo. I hope you enjoyed that. If you did, please do hit the subscribe button wherever you get your podcast. If you're watching, hit subscribe there as well. I'd also love to get a review. Reviews make a big difference on other people discovering the show, so please do leave a review wherever you get your podcast. If you want to contact me, you can do I'm over on XenSoredCMO or on LinkedIn where I'm under my own name, John Evans. Thanks for listening and watching. I'll see you next time.