Retailers are sitting on a goldmine of data, but with only 20% leveraging it to its full potential, can AI bridge the gap between potential and action, and drive measurable revenue growth?
Today, we’re joined by Cédric Chereau, Managing Director at EagleAI, an industry leader specializing in loyalty, personalized promotions, and omnichannel marketing solutions for retail, travel, and hospitality brands. With extensive expertise in optimizing marketing spend and driving customer loyalty, Cédric has been at the forefront of leveraging predictive AI to transform data into actionable insights that deliver tangible business growth.
About Cédric Chereau
Cédric Chereau, Managing Director at EagleAI is an industry leader in loyalty, personalized promotions and omnichannel marketing solutions for retail, travel and hospitality brands. From optimizing marketing spend to driving customer loyalty and increasing revenue, Cédric can share valuable insights on the financial impact of AI on retail marketing as well as how retailers can effectively close the implementation gap, and the significant returns on investment (ROI) that AI is already delivering for forward-thinking retailers. Alternatively, we can develop a contributed article on the topic, “The ROI of AI: Assessing the Financial Impact of AI in Retail”.
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Transcript
Note: This was AI-generated and only lightly edited
Greg Kihlstrom:
Retailers are sitting on a goldmine of data, but with only 20% leveraging it to its full potential, can AI bridge the gap between potential and action and drive measurable revenue growth? Today, we’re joined by Cedric Chereau, Managing Director at Eagle AI, an industry leader specializing in loyalty, personalized promotions, and omni-channel marketing solutions for retail, travel, and hospitality brands. With extensive experience and expertise in optimizing marketing spend and driving customer loyalty, Cedric has been at the forefront of leveraging predictive AI to transform data into actionable insights that deliver tangible business growth. Welcome to the show, Cedric. Absolutely. Good to have you here. I’m looking forward to talking about this topic with you. Before we dive in, though, why don’t we start with you telling us a little more about your background and your role at Eagle AI?
Cedric Chereau: Absolutely. So about my background, I have more than 20 years of experience now, probably more than I thought I had, always helping retailers to make the best out of the data that they’re collecting, essentially from their loyalty program. First, I was a consultant for 15 years, helping retailers, mainly grocery retailers, by the way, and health and beauty retailers. In Europe, I’m from France, as you can probably guess from my accent, but also in North America and Canada and in the US, where I helped Walgreens or Target to make the best out of the data that they were collecting through their new, what was new at the time, literacy program. And today I am the managing director of Eagle AI, and Eagle AI is the data science department of the Eagle Eye Group. And what Eagle Eye is doing is creating, building completely personalized offers from the loyalty ecosystem and also promotions, and executing those personalized offers for retailers around the globe. Eagle Eye is operating the loyalty programs of Loblaw in Canada, for instance, Woolworths in Australia. or Asda in the UK. So the most advanced grocery retailers in terms of personalization are using the Eagle Eye platform to operate their local program.
Greg Kihlstrom: Great, great. So yeah, you’re the right person to talk about this topic with, then, for sure. So let’s dive in here. And I want to start by talking about just the power of predictive AI in retail. And despite the benefits, and I’m sure those listening, they’ve read plenty of statistics about the power of data, the power of analytics. But despite those benefits, only 20% of retailers are using data analytics to its fullest potential. Can you describe what are those 80% missing?
Cedric Chereau: I would say that what is interesting is that they’re not doing nothing, the remaining 80%. They’re not doing nothing. They’re probably just using AI on some pieces of the puzzle. And the problem is, if you don’t look at those use cases where you want to use AI as an end-to-end pipeline that you want to cover, it will be as weak as the weakest link in the whole system. So, for instance, if you build the best predictive AI to completely personalize offers for customers, but you can only execute a few hundreds in your POS system, then you don’t need to build the whole very, very smart AI to personalize the offers. And I think that’s where the piece is missing, is most of the retailers are not looking at this, I wouldn’t say problem, but this thing as a global thing and they only do bits and pieces. What is very important, and that’s what we’ve been doing for the last 15 years, is making sure that every time we’re using AI, we’re not slowed down by something at the end in the pipeline. So everything is connected, everything is important, and you need to cover the whole thing as an end-to-end solution to make sure that you can deliver a completely personalized experience for customers.
Greg Kihlstrom: Yeah, so approaching that end-to-end, approaching that in an end-to-end way, what are some of the barriers that are getting in the way of companies achieving that?
Cedric Chereau: I think it’s a question of prioritization. Retailers, they want to build everything or they want to control everything. I think it’s a question of being able to choose the most important battles. It’s not make or buy. I think at the end, all retailers should make and buy. When you have very strategic topics, very very important and strategic thing that you want to do as a retailer, then of course you need to build it to protect what you think is the most important for you as a company. But sometimes it’s very important to go as quickly as possible, and therefore buy the solution that is already available, that has been developed by experts on the matter, on solution that will deliver within a few weeks, what you will be able to deliver within a few months or years if you start from scratch. So it’s just a question of balance. I think for those retailers, what is very important is to understand which pieces are the most important and where they should focus their investment and attention, and which other pieces are also very important, but a little less strategic, and maybe they just need to move faster. And I think that’s the most important thing. I think the best retailers are making the right choices in terms of make and buy regarding AI solutions.
Greg Kihlstrom: Yeah, that’s great to hear. Because yeah, I think there are there are a lot of retailers out there that I mean, they, they understand that they read all the statistics and all these things, but actually moving from, you know, interest to actual adoption, you know, is cut is a different thing. One other one other aspect of this is, you know, AI is talked about everywhere. I make a joke that we have to talk about it on every episode, and sure enough, we do. AI is, as we all know, it’s a blanket term for a lot of things. I think a lot of what’s been talked about lately is generative AI with ChatGPT and many others. But predictive AI is a very powerful, uh, maybe not as, as new as, as generative AI, but very powerful thing. That’s been around for awhile and, and, and is a game changer for, for retailers when, when done, um, done well for those that just kind of say, Hey, I want AI, you know, in a more broad, how do you differentiate and, and. kind of articulate how predictive AI can benefit and as different from generative AI in terms of like functionality outcomes and things like that.
Cedric Chereau: I think predictive AI is less cool than Gen AI, obviously, because it’s less new, as we just said. But I think it’s more important, especially when we’re talking about personalizing offers, personalizing experiences, personalizing key deals for customers. Because what predictive AI does is helping us to predict how the customer will behave in the future. And because we understand better how the customer will behave, then we can personalize the offer to drive the behavior we seek as retailers. GenAI is very cool because it will create content. It can be text, it can be pictures, it can be videos. But as a retailer, you’re not here to tell, I would say, to tell stories. Of course, you can personalize the image. Of course, you can personalize the message that you’re sending to customers. But if you personalize the promotion that you’re sending to your customer, that’s where the money is. That’s where the profitability is. That’s where you can make a success out of the personalization. So that’s why I think predictive AI is more important, even if it’s a little less cool, than gen AI. That said, GenAI is new. GenAI is bringing something new, different, and it’s also making a difference. If tomorrow, as a retailer, I’m able to send offers that are completely personalized in the parameters of the offer, how many products will I need to buy to get the reward or get the discount that is personalized to me? And if on top of it, I have a picture of that product that I really like, that is adapted to what I can react to, it’s even better. But the basic is in the predictive AI, I think.
Greg Kihlstrom: Yeah, I think, I mean, to build on what you’re saying, I mean, you know, as someone in my consulting, I’ve spent a lot of time thinking about, you know, next best action, next best offer, things like that. What I was most excited, I use Gen AI tools, you know, from, you know, in my daily grind, so to speak, but what I was really excited about was, Okay, now we can actually we know what the next best action is for our offer or whatever from predictive. Now we can actually personalize, you know, we’ve been talking about personalization for decades, but doing it at scale was also a challenge. So now we can, you know, have propensity or churn or whatever, whatever we’re trying to predict, matched with personalized content. Like to me, that’s that seems like the game changer. Is that would you agree?
Cedric Chereau: I completely agree. But I think things have to be done in the right order. You could do Gen AI without Predictive AI to personalize. Once again, I’m focused on promotions and loyalty offers and all these things. If you do Gen AI, you will do something that looks cool, that looks nice, but it’s probably a little less efficient than Predictive AI. For me, being able to personalize the parameters of a coupon might be a little less sexy, but much more effective than being able to adapt the right visual to each customer. But you’re right, the combination of the two is the holy grail. I mean, that’s how you completely personalize something for a customer.
Greg Kihlstrom: Let’s talk more about driving revenue and driving revenue through these methods. Studies suggest AI-driven personalization can increase revenue by 40%. What specific aspects of personalization make such a dramatic impact possible?
Cedric Chereau: I think the impact is huge because now, thanks to AI, we’re able to make sure that every offer, every coupon, every personalized challenges, because this is what we’re doing, building personalized challenges for customers. are now driving profitability by design. Before, it was very difficult to know exactly how efficient was a promotion. You were more or less shooting in the dark. Let’s say that we offer a 30% discount on that bottle of soda. It will work for some customers, it will work for some stores, but At the end, we don’t really know how well it will work. And sometimes it doesn’t work, by the way, but we don’t really know. The great thing with predictive AI is that we can really measure very precisely that customers would have spent $5 on that product. His natural behavior, thanks to predictive AI, is $5 next month on that soda. But I also understand that he has the ability to spend a little bit more because he has the potential to spend a little bit more. And that, once again, is given by the predictive. I will say, well, he spent already a little bit more in the past. So he has this ability to go one step further. If we give that specific customer on that specific product, an offer that will say, well, natural behavior is $5, but if you spend $8, then you’ll get $1 discount. Then it is incremental by design. And therefore the whole offer is, is a win-win for the, for the, for the customers and the retailer and the brand, by the way, everybody’s winning in this situation. And that’s how you, you. duplicate completely the performance of those campaigns because customers will receive nothing unless they do a little bit more. And by default, they have to do a little bit more, all of them on all offers, on all coupons, on all brands. And that’s how you make sure that you hit the target and that you you reach the level of performance that is unheard of. For instance, with the personalized changes that were operating for Carrefour, for Leclerc in France, for Tesco in the UK, for every dollar that is distributed to customers as a reward, it will generate at least $7 of incremental sales. And if there’s no incremental sales, then there’s no reward. So the main risk that they’re taking is it will do nothing, but it will cost nothing. At the end, we know that it’s working, and that it is generating incremental sales. And for a fraction of the costs, that was the promotion in the old times, I would say.
Greg Kihlstrom: Yeah, I mean, to that point, and maybe even to oversimplify here, but to me, this begs the question of using the right metrics, right? So in other words, if our metrics were coupon adoption, right, then you could be off the charts but lose a bunch of money, you know, again, to oversimplify things. So yeah, I mean, so using predictive analytics, if I’m, if I’m hearing correctly, you know, that not only are you safeguarding against, you know, potentially, you know, losing losing profit, but also, you know, the, the only the only thing to lose is, you know, some potential revenue gain, right?
Cedric Chereau: Yeah, no, absolutely. You’re right. I think one of the toughest thing that we’re doing right now is to explain how we measure things. And sometimes it can be sophisticated. I wouldn’t say complex, but it can be sophisticated. And it’s a challenge to explain to the retailer that we’re talking to. What is our statistical approach? Why we’re doing things like this? Because we know that the way we measure is more precise than what was done in the past. And it is a challenge. And I think we’re educating the retail ecosystem in that direction, but it’s very important because if we know how to measure things, then we will be able to evaluate much better everything that we’re doing together.
Greg Kihlstrom: Yeah, and I think this speaks to just the idea of being ready for AI and being, I would even say being ready to be data driven, right? Because again, in my very simple example, if your goal is to make sure people use coupons, they could be for anything and have some adverse effects in the short term at the very least. But if your goal is to maximize adoption plus revenue and profit than whole other scenarios. So to be ready to not only be data driven, but also to be AI ready, what advice would you give to an organization to start moving in this direction?
Cedric Chereau: That’s a very good point. That’s a very, very good point. I think the the magic will work when the AI-based solution will leave the control levers in the hand of the retailers or the brands. Because you can do plenty of things with AI. So exactly what you said, you could say, well, I want to maximize recruitment of new customers on that specific brand or product, or I want to maximize profitability. It’s two different things. I’m not saying one is better than the other. It really depends how you want to… act on your product or your customers, on your stores. And that’s, for me, that’s the right way of building solutions is to make sure that it’s not a black box, that the final users, and when I’m saying final users, it’s usually the marketing guys, are able to say, well, this month I want to do this with this brand, with this category. I want to push that button a little further. I want to remain in control, but I have a strategy. I know what I want to do, and that tool is helping me to do what I want to do, not doing some dark magic that I don’t really understand. And I think that’s very important for AI solution provider to understand this. You can have the most advanced AI if it’s not designed to answer business questions business problems that marketers are facing on a daily basis, it will be very difficult to make them adopt your solution.
Greg Kihlstrom: Yeah, yeah. So I’m wondering if you could, in line with that, do you have maybe an example or where, you know, you’ve seen some of this AI driven, these AI driven marketing strategies lead to some significant ROI?
Cedric Chereau: Well, the best example I have is this personalized challenges solution that we developed for our client, grocery retailers around the globe. The idea is to find the right products, which brands am I the most interested in as a customer? And what are the right spending thresholds that will be defined for each customer individually to nudge the customers to do a little bit more, for them to reinforce their loyalty. And if I reach a certain threshold of spend, then I will get a specific reward. It can be points or it can be cash back or whatever. And it’s also completely personalized based on the promotional sensitivity of each customer. I think that’s an interesting example of… how you want to play this, because if you want to recruit more customers in that kind of program, then you make the challenge easy for customers. So you stretch my shopping behavior because you’re looking for incremental sales, but not too much because you want to maximize the recruitment of new customers in the program. Once you have hooked them in the program, then you might want to action a little bit the the profitability lever and increase a little bit not too much but the level of difficulty of the challenge meaning that the stretch required to earn a reward will be a little higher. And that’s how you, as once again, as a marketer, you make sure that you define the right level of difficulty to maximize either recruitment or profitability or a good balance between the two. Because on the long run, you want to make sure that the customers will participate, will remain in the program, and will continue to spend a little bit more with you, meaning a little bit less with your competitors. And that’s precisely, I think, one of the best examples of how you can enable retailers to remain completely in control of their promotional initiative. You give them the levers to activate.
Greg Kihlstrom: Yeah. So one more question for you here on this topic. As someone who AI is in your realm, again, lots of people talking about it, but this is your focus. What are you paying attention to? What do you predict as far as trends in this space? What should we look forward to in 2025?
Cedric Chereau: Everything, because I think we’re just at the beginning. It’s impressive how small we are for the moment, I think. It will become massive. You’re absolutely right. I just came back from the NRF in New York. Everybody’s talking about AI, but I can bet that in five years it will be even more than this. It will be everywhere and in everything. I think what we’re doing in terms of Personalizing the offers to the promotions the loyalty programs. We’re just at the beginning so we’re able to complete the personal parameters of an offer but you just mentioned it with jenny i will be able to. go one, two, three step further because we will personalize the picture. We will personalize the message. We will personalize the recipe. We will personalize plenty of things, and that’s just for personalization of promotion. But AI, I think, will be also here in the voice commerce and all the conversational bots and everything. We’re just at the beginning. We can see that it’s very cool and we’re getting there, but it will be much, much better. Another example, which I think will be a huge revolution also, is everything that is linked to supply chain. Being able to predict how many products, how many units you need in the backstall, all these things will increase profitability and revenues for retailers. And I think we’re just at the beginning.
Greg Kihlstrom: Yeah, yeah, agreed. Love it. Well, one last question for you. I like to ask everybody here. What do you do to stay agile in your role? And how do you find a way to do it consistently?
Cedric Chereau: It’s a very good question. I love this question. I think what I’m trying to do is to continue to prioritize the different tasks that we have. We need to remain flexible. When I say this, I think staying organized is very important, but if you schedule everything and you overschedule everything, then you lose flexibility and you need to remain agile. And I think the other thing is I rely on my incredible team also. So empowering them help me and help us to remain agile because the right ideas will come from everyone. And that’s how you really remain agile is making sure that you hear all the good ideas from everyone. And there’s not like the big boss and everybody else execute what he’s saying. I think it’s very important to empower an amazing team. And we have an amazing team. So that makes our life easier.