Loyalty Isn’t Dead — It’s Just Getting Smarter (CEO of Convenience and Energy Advisors, Peter Rasmussen)
Most loyalty programs are broken.
Retailers spend millions on discounts, apps, and activations—yet customers drift away. As Peter Rasmussen said during our conversation:
“I spent money to get you into the program, and now how do I keep you?”
Peter knows what works...
He helped lead Wawa’s massive Florida expansion and today, as CEO of Convenience and Energy Advisors, he’s showing retailers how to transform loyalty with AI. His team isn’t tied to one platform—they’re “super users” across them all—giving him a unique view into what actually drives results.
Here’s what we dug into:
-Why loyalty members spend 18–30% more.
-How Casey’s has over 40% of transactions tied to loyalty
-The key to Oxxo reaching 45.8%.
We also explored what U.S. brands can learn from Luckin Coffee in China—21,000 stores built on ultra-personalization that left Starbucks scrambling to catch up.
The message is clear: personalization isn’t a “nice to have,” it’s the future. And AI is the unlock. In fact, Peter’s seen loyalty analysis that used to take a week compressed into 24 hours with AI—allowing retailers to respond faster, target smarter, and drive more profitable growth.
If you want to move from “having a loyalty program” to running what Peter calls a “mega commerce engine,” this episode is for you.
Transcript
A loyalty program. It's a mega commerce engine.
Speaker B:What do you see is happening in loyalty right now?
Speaker A:Loyalty members spend 18 to 30% more. What percentage of my transactions are part of loyalty? Casey's has over 40% of their transactions part of loyalty.
Oxo, 45.8% if you want to get to that and beyond then.
Speaker B:He was one of the key leaders behind wawa's massive Florida expansion. Now Peter Rasmussen is bringing that same playbook to retailers everywhere.
As CEO of Convenience and Energy Advisors, using AI and loyalty to turn fuel into serious customer stickiness.
Speaker A:Sometimes you hear brands talk about, I have 2 million loyalty members. How many are active in the last 30 days or the last 90 days? I spent money to get you into the program and now how do I keep you?
And I'll give you an example.
Speaker B:With AI, we've been able to see, you know, tremendous gains in productivity.
Speaker A:When Luckin came into New York, they had guts. Luckin leveraged ultra personalization. They created value. They have an operating model less expensive than Starbucks.
It's like nothing you've ever seen before.
Speaker B:Do you see an opportunity in that?
Speaker A:I think in the grand scheme of things where, where the biggest opportunities lie is that.
Speaker C:AI is the next big boom for fuel and C stores. You know you need it because you're drowning in data, yet sometimes lack insights.
You're stretched thin and the AI learning curve can feel impossible. Your competitors are starting to move. Are you getting left behind?
Well, welcome back to Fueling AI, the podcast that cuts through the noise and delivers the real story on AI for Fuel and C stores. Hosted by industry veteran and CEO Doug Hawke, this is your no nonsense guide to safely leveraging AI to drive profitability and growth.
We'll expose the risk, explore the possibilities and give you actionable strategies you need. Now subscribe and ignite your AI advantage.
Speaker B:Hello, I'm your host Doug Hawk. Welcome to Fueling AI. And today I'm thrilled to welcome Peter. Peter Rasmussen, CEO and founder of Convenience and Energy Advisors.
es before of launching CEA in:And CEA doesn't just advise retailers, it implements next generation strategies which we'll talk about today, particularly around loyalty, but works with store design, new service models and multi channel execution. So Peter, thanks for being with us today. Excited to chat with you and looking forward to the conversation.
Speaker A:Thanks for having me Doug. Looking forward to it.
Speaker B:With Your background, we could range all over when it comes to retail, but I wanted to kind of zero in on loyalty for a couple of reasons. One, we're starting to see some interesting progress with AI which we'll kind of wander around today as we talk through it.
But we've seen AI be applied to quite successfully so far to a lot of back office processes. So just what I call automating the boring but useful stuff where it's like, frankly, we don't want to really.
We don't love paying people to do it and the people that we're paying to do it don't love doing it.
So it's like those kinds of, that kind of work where I think we've been able to see tremendous gains in productivity and the ability to kind of elevate those jobs. And I say that deliberately because I think there's a lot of fear around, oh, this is going to take my job.
We're not seeing any of that yet, but we're seeing a lot of, a lot of really productive enhancements to jobs where people can focus a lot more on making decisions and adding value rather than punching keys or manually wrestling data to the ground.
We're just starting to see it pop up with loyalty and with customers we see once they can connect their data and build an agent to interrogate it and look for patterns and, and sort of detect what's going on. And we're just, again, it's early days but we're seeing that start to creep into loyalty.
So I wanted to sort of base load the conversation with what do you see as like happening in loyalty right now? Where do you see the best progress?
I've wrestled with it as an operator for years and like I mentioned in our warm up here, I always felt like I was spending more and getting less in some cases and, and I know you spend a lot of time helping people fix that and get more out of it. So maybe just give us the latest on what you're seeing.
Speaker A:Absolutely. So my team and I have a unique position in that we're not a loyalty company, but we work across all the major platforms. Right.
We're impartial to them all and we like to call ourselves super users of each.
And in our relationship with convenience retailers in some cases where their entire loyalty department in other cases we work closely hand in hand with it and we're seeing a lot of now in where you can use AI applications is getting to the data faster so you can create a logical segment and I'll give you an example so say as a retailer you were used to giving fuel discounts and maybe you gave them on a certain day of the week, or maybe you gave them based on a certain amount of time that a customer has lapsed. Those strategies still work.
But what we're also finding is if we can get a discount to a customer closer to the day that they need it, then in many cases we can give them less of a discount and have a higher take rate. Which is pretty magical, right?
Speaker B:Absolutely.
Speaker A:That's an example of we're meaningfully drawing a customer to a store, an investment less than what we would have done in the past. That's one example of it. And another, I would say is really just promotion analysis, being able to get to an answer faster.
So say as an example, you have loyalty promotions and they're around package beverage. Right. And maybe it's a discount in one phase and maybe it's tied to fuel in another phase.
Well, very quickly we can sort through thousands and thousands of transactions and say, well, if my offer tied to cents off per gallon, does that mean more than if it's just straight discount in the store? And then if it does, then that dictates what I want to do in the future.
Especially for customers who purchased that and then how big was their basket, et cetera. These are all things that you could always have figured out in the past by exporting the data and building some pivot tables. Right.
You can still do that today, but we're able to get to that a lot faster, which then gives us the ability to be nimble in forward promotions.
Speaker B:Awesome. Awesome. Yeah, we're.
And I think that that was part of what spurred, you know, my interest in talking to you was we're seeing, we're seeing that area accelerate and I was wondering if, are you seeing like we've always done. What I've always tried to do in the past when I was the operator was we ended up hiring data scientists.
I mean we were, we were a large chain, so we, we threw pretty good horsepower at this. And even with that help, and obviously you have a team of experts that knows how to do this very, very well.
It's, it's still pretty time consuming, right? Like it seems to be.
It, it does take some processing time and some kind of analytics effort to apply just standard data analytics, but also deep mining and data science and really getting when the data set gets larger and larger, which we all hope it does if we're being successful with deployment. Right. And we've, we've just now started to See some customers be able to take AI and apply it to that problem.
And we ran an A B test recently with not a massive data set, but it was a medium sized marketer with, with pretty good data set. And we, we ran it with our data scientists using traditional analytical approaches.
It took us about a week, which I was reasonably impressed with, given was from a standing start. So not bad. But the AI beat them pretty well like it was. They turned it around in 24 hours. And we initially said okay, well that.
And it looked really, really good.
Like the, the insights it gathered, it picked out some customer profiles and types and market basket correlations that I didn't, I wouldn't have traditionally seen. But we weren't confident in it because it's the first time we'd kind of seen it applied in that way with an agent that was built with that objective.
And then we tested that against our data scientists and they came to the same answers largely.
So do you think, I mean is this, is this still all hype or are you seeing the opportunity to kind of connect that process to greater intelligence where we can sort of really. I think, I think the best practice is still very applicable. Right.
Like if you don't get these insights out of your data, you're kind of wasting the investment you made in loyalty is what the way I've always felt about it. But perhaps we can lower the barrier to kind of getting those insights back is my hope.
Speaker A:Yeah, I don't think it's hype at all. And I think if anything it's, it challenges the teams more to have fact based decisions. Right.
Like you watch Mad Men and you think how great would it have been to be a marketer in the 50s, right. Like you're doing everything off your gut. Well, I think. Right. And you can't do that anymore. Right.
There's still some experience, intuition, but everything has to be fact based. And I think where we're at right now is the AI helps us get the data faster, more fact based, which is magical.
Where we're not yet across the major loyalty platforms is okay, well I still need to program that algorithm. Right. And we'll get to a point where AI can start to program the algorithm. But a loyalty program, it's a mega commerce engine.
In many cases you have millions of users, even if you have hundreds of thousands in it, like the checks and balances in it to make sure that we don't duplicate a segment or get anything wrong on it before we push that offer out. AI isn't there yet, but Just based on advancements, it's, it's only a matter of time.
So it's getting us smarter data to send stuff out and be able to move quicker. But there's still a lot of manual work in the programming of the segments.
Now if it's a repeated segment, you set it up once and that's great, but still a ways to go there.
Speaker B:Yeah, yeah.
And I think one of the things that we've, as we've been working with lots of agents kind of across the enterprise, one of the things we have learned certainly is kind of like, and we use the analogy a lot around kind of digital employees, right?
So as you, as you sort of bring up these, these capabilities, thinking of them as onboarding new employees has typically been more helpful to our customers than thinking of that as a program because it sort of shares a lot of the attributes, right?
Like you gotta, you gotta onboard them, you gotta teach them sort of about the company in terms of, well, where am I working and what do we do and how do I get things done? Some cultural sort of awareness like how do we, how do we, what's our brand about?
How do we, how do we communicate with folks, with each other, let alone our customers.
But one of the fundamentals is also, and I think that extends to kind of the employee analogy, which is focused work yields more accurate, better results, right?
And like, so like any of us, but certainly with new employees or younger employees, if you give them 10 jobs, they're probably not going to succeed very well at any of them.
If you can narrow their focus into saying, hey, master this area and focus on it and execute in that space, then they got a good shot or at least a workable shot, right?
So the same thing we're seeing with AI where, and I think when it comes to loyalty, we certainly see sort of the data ingestion and analytics and sort of data sciencey aspects of it. Like okay, I think we can get real expertise in the AI in that area, right.
That as you said, can speed up that cycle time of just how do I get the data in faster, get to the insights faster, turn it around to where my, then my promotion or offer is more timely.
I think it's going to take breaking that out into multiple, a multiple agent environment where, okay, I got to get the insights I'm constantly processing as the data is coming in.
Again as you said, like the different types and sort of correlations that I've already seen because then I can sort of act on those reliably because I've got Some experience with them. I guess my question is then, how would you break down the rest of loyalty work?
If you think about like how your team divides up the work, how should, you know, how should companies think about applying this kind of technology versus again the traditional loyalty platforms?
Or you know, I've always thought about, you've got kind of the, you got the mobile experiences, one part of it all the way out on the end and, and then you've got all the integration that we have to do through the spaghetti bowl that is our retail environments these days in terms of technology. And then connecting that back to my execution platform where I really want to drive the activity.
I think it's going to take a multi agent approach to figure all that out and kind of replicate with speed, you know, what, what the best experts get out of it today.
Speaker A: They carry share there until:And that's when Luckin came about, Right. And you fast forward to today and In China there's 7,000 Starbucks, there's 21,000 Luckin locations. And so they kind of blew their lead.
Yeah, it's nuts, right. But their cost of operations is so much lower because you have to order mobile so there's absolutely no cashier. So then they speed up production.
The app is phenomenal.
And in China's case, they basically just cut Starbucks at the knees and said, I'm going to give you the same or better quality product and it's going to be more fun, it's going to be more digitally personalized and it's going to cost half the price. Right. And it worked. And I think fundamentally we think customer experience has to be warm.
I'm friendly, like that's what I've always learned in all my years in retail. But there's a customer base who would trade value for. It's digitally personalized, right.
So I got very curious about this and a couple weeks ago I went to New York City because there's now two Luckins, soon to be five, and they continue on expanding in the United States. And when Luckin came into New York, they had guts. They're on a block with a 711 and a Starbucks, right?
Like they're taking class A real estate, but they're building it cheap. And when I went in there, it's almost like a silent Disco. It's like nothing you've ever seen before.
There were 14 people working at 4 o' clock on a Thursday. They're slammed, but the employees aren't talking to the customers.
Even people coming in for the first time ordering are literally downloading the app, sitting down to order their orders ready very quickly. And then they go up, they scan their phone to pick it up and they're off. Nobody talks to each other.
So I share that example because Luckin leveraged ultra personalization. Their coupons galore, they created value. They have an operating model less expensive than Starbucks.
And you'd say, well, could Starbucks just do the same thing? No, because right now, let's say 40% of their business is mobile order. That's Great.
Luckin has 100% mobile order and then they have this big machine of extra cost tied to every store that Luckin doesn't have to deal with. It's just wild.
Like if a competitor came at you and charged half as much to do the same thing, like, wow, who would have ever saw that coming for the chain that controlled coffee share in China?
Speaker B:Well, and I, I think when it comes to, as, I just think if, I mean, it feels to me that loyalty's kind of stuck. Like it's sort of, I think we spent so much time and money and capital and effort just getting the infrastructure deployed. Right.
Like, I mean, I remember just pushing, activating at our stores.
I mean it was, it was so much work on getting the app out there and getting it connected and then, and then I feel like everybody sort of to some degree said, okay, great. And then we've kind of stayed there and, and I, to me, my personal experience outside of our channel is like, is Starbucks and Domino's, right?
Like, I mean I, I was a big fan of Domino's early just because I'm kind of a logistics guy at heart in certain parts of my life. And like, I love Delivery tracker, right? And like our industry is still horrible at this. Like, we can't ever tell you when stuff's coming.
Vendors can't tell me when they're dsd, when it's going to come to my store. Like, I don't know when my fuel is going to drop.
I don't, it's, we still are not very good at this, but somebody figured how to do it for a nine dollar pizza. So that was impressive to me. Right?
But when it comes to, and they have, you can earn great points, but the coupons and the promotions and the offers are depersonalized. It's like the opposite end of the spectrum to me to what you're talking about.
And Starbucks, even when I mobile order, like sure, I can reorder my previous order, but that's about as personalized as it gets. Like I, I was thinking about this the other day. After years and years and years of using it still doesn't seem to know who I am.
And so I guess my question is, do you, are we getting to the point where getting to that ultra personalization as you put it, and what I've always termed kind of one to one marketing, like can we actually execute at that level with the infrastructure that our industry has standard? Not, not the best we've ever seen. Right.
But the bulk of the stores out there that we've all built or worked for or worked with, do you think that's within reach?
Now if, if people lean in with real discipline to get to that opportunity to really market to the customer one to one and, and get offers in front of them that as I always say, I want it to be engaging and meaningful to them. So it has to connect and it also has to be more profitable for me because otherwise what am I doing?
And it could be profitable on obviously unit item or visits or frequency or volume, et cetera. I mean there's lots of ways to calculate that. But are we there yet?
Or you see technical barriers in kind of the infrastructure in stores that you're, that you work with. Are we ready?
Speaker A:I guess I think the capabilities there with the large loyalty providers that serve our industry. But I think our industry has a lot of distractions to loyalty which also distracts focus on it. Some examples of that, right?
Tobacco is a very important part of the program. Tobacco has a lot of digital requirements to it, which can be complicated.
And then at the end, if I'm a dealer site that doesn't have a loyalty program and my major oil can't provide that to me, I can be at a $2 pack disadvantage to my competitors.
There's a lot of confusion between if an operator has their own loyalty program and then there's a major oil program and then does it or does it not stack? And then should it stack? Because is there any money left if you do that? And then I think we get distracted too much from the app side of things too.
When you look at transactions in our stores, from my experience, 80% of them are usually phone number driven.
So then from a resource perspective, we look at how much money do we want to put into our program, how much do I want to spend on my App versus what I would invest in messaging, whether that be sms, push email, or with new tech technologies like Braze, you can even message out on social, which I think is phenomenal. Right. So I think there's just so many distractions to the complexity of it. It distracts the core mission, which is.
had the pizza Tracker in like: Speaker B:I mean, they were so early and have done not much with, you know, it still works.
Speaker A:You're like, my pizza left the store. This is great.
Speaker B:Yeah, Yeah. I think it's akin to your Starbucks lucking thing. Right? Like, huge lead, huge engagement that others really just still haven't duplicated, frankly.
But it's just.
It doesn't seem like a lot of those situations have evolved to really leverage what they have, which is, as you said, if you can get to that ulta personalization, I think it gives us the opportunity to both parties can win. Right. Which if you get to that win win transaction, like, I, I think sky's the limit for a retailer. But it's.
And I do agree with you, I think, I mean, I've, I've lived it where we had our ability to execute in a.
What I call our brand store, where we didn't have the fuel brand in the middle, was quite different than what we had to deal with when we had a major fuel brand engaged. And yeah, when we got to.
And that was with our sites, I mean, we could do certain things as the operator that our deal we couldn't necessarily do for our dealers. My last experience, we ran a couple hundred stores ourselves, and then we had 650 dealers nationwide, most of which were aligned with some brand.
So I think they are, they're big distractions. So I guess what's your recommendation? If, if.
What should we look past as retailers to focus on versus getting tied up in that morass of fuel brands and stacking it is. And they're not just distractions. They're like, they're significant barriers in some cases to execution.
What would you recommend that a retailer focus on to get past that in the most effective and hopefully at the end of the day, profitable way for them?
Speaker A:I think in, in many ways it depends on the model that you have and then how you want to use that. Right. So let's say I have some smaller sites and a major oil branded. Right. How do I counteract big competition? Right. Well, Costco as an example.
Right. Pumps more fuel than anyone else in America. Right. And their brand, Kirkland. Right. Has more annual Sales than all of Nike.
But if I'm a BP station and I link to Amazon prime, my discount might actually be better than the Costco street price. There's some advantage in there. But how do you get people to know that? Right, right, right.
Or you take some brands like QT as an example, they've done such a great job. They don't have a loyalty program. Right. They have an ACH program, but they don't have one much like Trader Joe's doesn't have one.
So there's brands that can do the polar opposite of what the trend is. But that's very much, very much a one off and very much a company cultural phenomenon that have built over time.
But I think in the grand scheme of things, where the biggest opportunities lie is that people expect personalization and the major platforms that serve our industry today, they have the capabilities to do that. It's just a matter of taking the data, which you can use AI for today and leveraging it that way. So I'm a bit strange in that given, given what I do.
I subscribe to over 40 convenience store and oil loyalty programs. Right. So when I see these offers come across that say, like, hey Peter, it's National Hot Dog Day, like I've never gotten a hot dog at your store.
Speaker B:Store.
Speaker A:But like, that's cool. It's National Hot Dog Day.
In a world where I mentioned that my Roomba broke and I pick up my phone and Amazon has a Roomba on there, like it's creepy, but it's also extremely convenient. I'm like, great, and now I can get my vacuum. So people expect that same thing.
So just through the act of things like receipt tagging as to what do people buy. So then what offer should I send them?
I don't want to send you coffee if you buy energy drinks, you know, or maybe if that coffee is a funded offer, I'm offering you energy drink or coffee.
Like give people what they buy or what you think they would buy versus pushing down mass offers for everybody because that, that doesn't work anymore. That's almost like having the tolerance to say, go through a catalog that you get in the mail. Right.
Versus the capability of a personalized Amazon that comes to what you're looking for.
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Speaker B:In some ways for me and I'm like you, my and my kids think I'm nuts when we're on a road trip because like everywhere we stop, I'm like another loyalty app I could download. And I tested them all out.
I think every retailer in the Eastern Seaboard has my banking information for ach like just because I want to see, I typically want to see how hard it is to get the darn thing set up and what the fuck friction points are right? So. But it almost does become off putting to a degree.
Like if I've been with you a while and I'm giving you a lot of my business and I'm being loyal and you haven't taken the time to understand who I am, like just sort of, well, do you care about me as a customer? You know it. I think there's a higher threshold right to demonstrate that versus customer comes in and doesn't have any of that history with me.
Demonstrating you care might just be greeting me with a smile and having a clean, fresh, bright store like okay, great.
But when you've said you want me to be loyal and you've asked me for data and information and maybe even my bank account, it seems like you should do a little bit more right to dig in and get personal, I guess. What do you think now are the biggest barriers to that happening?
I feel like I said we've spent a pile on infrastructure and connectivity and I think your point on the mobile app is really important because we're seeing I do think there's some opportunities with just geofencing and kind of real timing the location services to say hey, it's 100 degrees out and I see you right nearby.
I don't know if you're getting fuel today or coming in or not, but if you do, like here's an offer for you because I know you get my extra large soda fountain drink, come get one for a really good deal. But make I think for that to be relevant, like we have to get to where it's right now.
Because if I send you that at 10 o' clock at night when it's all over, like I'm just going to look foolish, right? Or if I send it to you and you're nowhere near one of my stores because this happens because I'm, I'm, I'm logged into so many of these things.
Like, like you said, I'll get an office, says, hey, stop in today. I'm like, I'm not even in your state right now.
Like, so is there, is that getting easier to execute now with, with I guess the apps and messaging and sort of awareness that we can build with the customer?
Speaker A:It needs to be because there's too many apps and I think the world's moving away from that. I think we're a little bit slower in the U.S. like in the U.S. and I think New York and San Francisco, there's now Blackbird, right?
Which Blackbird brings together a lot of restaurants into one loyalty program, trade points amongst programs and then even trades personalization so a waiter can come up to you and they might know your drink because you ordered it at a different restaurant.
Speaker B:Right.
Speaker A:But on a bigger scale. Like China's had WeChat for years, right. So go back to my luck. In example, you can use the Luckin app or you can order it through WeChat.
I think we have massive opportunities like that. Like BP created a relationship with Amazon which is like magic. So I thought it was very cool.
I get my earnify app, like my Amazon Prime, I can activate it from the pump, it goes to Apple pay, I don't have to put in my payment. My wife's like, that's really complicated. Which is actually. Right, right. Why isn't it like the ant? Why wouldn't you just go into the Amazon app then?
Because when I go to Whole Foods, I no longer have a Whole Foods app. Right. I scan my prime account. I would say ExxonMobil could do that same with their Walmart relationship.
So the world's over apt and you don't want to keep having apps. And then if you do have apps, the new standard I think is that it has to be really easy.
Like passwords are becoming a thing of the past, two factor authentication. And I think some programs are even a bit more forward too, where maybe they do have to, they do have an app, but you don't have to do it.
It can show up through the browser, et cetera. Because like nobody wants all that on their phone. It's, it's frankly too much yeah, it's.
Speaker B:It'S certainly overwhelming if you're a junkie vitamin like me, but it's, I think even for the everyday customer, right? It's like every retailer you walk into has one now and it's like I have to be, you know, and that's where I think the folks that.
I think it's twofold. If, if, if I do go to that, if I am a customer, that goes to the extent of downloading your app, setting up my profile, configuring all that.
Like, then I think the, the burden is bigger on the other end. Like, hey, I did that amongst hundreds of opportunities to do it with lots of other retailers that I didn't give the time of day. I did it with you.
Show that you care. Right? So.
And I think I, I do think back from an AI perspective, like where I'm living these days, like, I just get excited because it's, I think we can speed things up.
I mean, we're definitely seeing that where just the just consuming and processing this amount of data in real time with not with just blind algorithms like we've done in the past once we kind of set up the analysis profiles and so forth, but with live intelligence, in this case, synthetically alive. But it processes with. It's different, right? It's thinking about intent.
We, We've seen the opportunity to really teach the principle, kind of first principles of loyalty to an agent, where it's like, hey, here's why we're doing it.
Because I think what gets missed in kind of some of the algorithmic approaches, even if you can get them installed and integrated to your data, is they're more about the how and the what. You understood the why of when you put it in place, but it didn't really know why you did it. Right. Or why it exists. It's just a program.
And I think the ability to sort of instruct these agents and say, here's by the way, here's what and how we need to do things, but here's why I'm doing it to begin with.
Like, don't miss the point of what we're executing, which when it comes to loyalty in some cases, I think that's, that's sort of been my big pushback is did we miss the point of all this?
Which is like we spent so much time getting distracted with integration and infrastructure and apps and deployment and activation at the site and all things are necessary. But I do feel like we can sometimes disappoint if we're not careful.
Speaker A:Agree.
Speaker B:Yeah.
Speaker A:I Completely agree with you on that.
Speaker B:Where do you know, I guess going forward, what do you recommend retailers do to really even think about taking the next step with either their existing loyalty platform or how do they evaluate what good looks like? Am I getting what they're going to have? Like you said, a lot of this in the early days has started with gut, right. My customers like it.
Am I getting adoption? Do I have transactions? I mean, I got KPI, sure.
But like, how do we get them to think and help folks think a little bit more strategically about what's next and can they integrate? And it doesn't have to be just sort of all AI all the time, like, like I'm sitting here talking about.
But like, and we see on the news, but what are the, what are the first principles they should really think through as they're evaluating their situation and where they sit today to take the next steps and get, get more return out of all the money they've already spent?
Speaker A:Sure. Well, I think a good place to start would be where do you stand today versus industry benchmarks? Right.
To say, well, am I doing pretty good or do I have a ways to go? Right. So we know based on data that loyalty members spend 18 to 30% more and visit at least one more time a week. Right.
So then what percentage of my transactions and gallons are a part of loyalty? Benchmark that to some of the best publicly traded companies, which are facts. Right. So Casey's has over 40% of their transactions, part of loyalty.
That's phenomenal.
Speaker B:Right.
Speaker A:Oxo down in Mexico has 45.8% as of their last. As of the last shareholders report. That's like, that's the Mecca, right, of how good it gets. So what percentage are your transactions today?
And if you want to get to that and beyond, what do you need to do to get there? And a big part of his personalization, which we talked about today.
And I think there's also just a lot of other emerging technologies which could be powerful, but also depends on your model and your workforce. Right.
So there's a couple point of sale providers today where loyalty integrates down to not only having a suggestive cell on a screen that might face the customer, but also to the employee. That sounds really cool, but depending on where your workforce is, are they going to upsell?
Have you built enough of that across your organization that that investment would matter? So I think it's mostly a matter of how can I get something to be meaningful.
But generally what I see where you can make the most headway is Start with fuel. Because no matter what, what I always see is fuel drives the most affinity in our industry, whether it's tied to other products or not.
So if you have an investment to get folks into your loyalty program, there might be a welcome offer, there's a retargeting. But then what do you do after that? Because sometimes you hear brands talk about, Well, I have 2 million loyalty members, that's great.
But how many are active in the last 30 days or the last 90 days? Because from our experience what we find is keeping people active within 30 days. That works. That's my cycle of commerce. Right?
And when I get to that 21 to 24 day mark, I have to start to work really hard because I don't want them to fall out. 31, 90 have a chance of getting you back and after 90 it's completely hopeless.
So I spent money to get you into the program and now how do I keep you.
And leveraging a lot of AI in the data to find personalization so I can get the right offer to the right person at the right time is really what's moving the magic in programs today.
Speaker B:Do you see an opportunity in that? Like one of the things that we were kicking around is.
And this gets back to obviously it's been in place with the tobacco part products a long time necessarily so for lots of reasons.
But like if I can get to the insights faster and I can create the potential offers proactively again using again, execution is a little different as we push it down.
But like if I can bucket that at that point, one of the things we've been kicking around is like can I also use that speed and sort of depth of the data? Because it. And basically can I be convincing enough to go back to the supplier base and say, hey, like I want.
Is there an opportunity for retailers to be more proactive in that Right. Versus responding to hey, I have this funded offer this month from the.
Because they're launching a new product and a new flavor and they want me to do it.
I think there is an opportunity potentially to say, well that's fine and good but like look at what we've really learned about our customer base and how they react to your products in this at these sites this day part this season and here's what we'd like to do and kind of flip that script a bit and push back and go proactively against the supply base and say, look, I want to work with you. I think we can both do better. And here's.
I just feel like Doing that from the gut in the past was, in my experience, wasn't effective with my merchandisers and otherwise. Right.
I see an opportunity, maybe be better on the retail side at really sort of driving that conversation in the supply base and helping both parties execute better.
Speaker A:I think you nailed a huge opportunity there because a manufacturer is going to come to you with their initiatives, what they want to push out. Right.
And when you can come back to them with sophisticated data that you have access to that used to only come from the largest CPGs, it's magical and it gives you a lot of power. And as you're doing it too, you're also building this massive digital messaging footprint. Right, right.
And that gives you the idea, the capability to directly sell retail media versus aggregating it through a third party and you can deliver it hyper targeted versus generic in some cases. So yeah, I mean, I think that's an absolutely massive opportunity.
Speaker B:Yeah. To me it feels like that's just been completely untapped by our, our channel largely.
Like I'm, you know, I mean 20 years ago I was, I was even in, I was working with Walmart, but I was in the UK at their ASDA stores and like they were on the same point of sale back then and I was just, I was in the back office and just watching just the granular data and how they used it with the manufacturing and supplier base was, I mean that was two decades ago. Right. So I just, it's always. But I, I can. The reason that's so crystal in my mind is like at that moment in time I'm like, how come we don't do this?
Like, and I feel like two decades on we're still, mostly still not. Right. So.
Yeah, so I'm hopeful and excited that if we can just I think get the, some of the distractions out of the way, get the, get the processing and sort of the insights produced a lot faster.
My hope is that the bandwidth we can create for folks in doing that allows them to kind of pivot their attentions to more of these types of things where they can be proactive versus reactive and say, hey, yeah, I'm happy to take your offers to market and support your rollout, but here's what I want to do and here's why it can be good for both of us because I have the data to prove it, I connect it.
And as you said, I do think over time that could be even the monetization of that in some form or fashion, whether it's direct or indirect, by having that hyper Channel that's active and connected and whether it's app or SMS or you name it, but it's personalized, I think can be an asset class for retailers. Right. It certainly has been for Walmart for many, many years and I'm sure others. That's just the one I had the most personal experience with.
But I think that's how I'd like our channel to start thinking about it a little more actively. It's like it applies to what we're learning with AI is that.
And we've been getting this message for, I don't know, more than a decade now with big data and so forth. But more than ever, what I tell folks is your data is a massive asset class for your business. Protect it, be careful.
But I just end with that a little bit and I'll ask you for some parting thoughts.
But like, you know, as, as folks play with these new capabilities, pilot them, test them, just be very, very thoughtful about where your data goes, how it's used. This isn't about cybersecurity anymore. It's not about privacy anymore. All those things certainly apply.
But there's a whole, the AI topic and how it, how data now integrates and is ingested and consumed and understood and contextualized is a whole different category of data management and governance.
And I think we've all on a, we're on a learning curve there and I think you've got to be really careful but super powerful capabilities but because of the power and opportunity in front of us, we got to be careful about that. So, and, and not all of these model builders are, are benign sort of empires. Like they've got objectives too.
So I think we just have to be very thoughtful about where we build these tools and how we execute with this data. But super excited about the potential. I think hyper personalization is, is certainly attainable.
I think that monetization of our, of our channel to the manufacturing base in a different way than we've ever been able to accomplish before is, is certainly possible and, and really and probably necessary.
Thankful for, for retailers who want to take that next step and close the supply chain links all the way to their customer, back to the manufacturer and, and create value for the customer and the manufacturer. Right. If we can keep both happy and excited and engaged with us, I think everybody makes more money.
Speaker A:Yeah. And I think it's interesting time and I think we all, what I tell my team and I tell others a lot is I never like what I hear.
People say AI is taking our jobs. Right. It's not.
It's going to be a matter of who capitalizes on it by having the discipline to teach themselves to use that to create something incredible. Right. I didn't grow up in the age of AI. They didn't even have smartphones when I was in college. Right. Like I'm like the last era of textbooks.
And you even take that down to education today you'll hear teachers say, well, students are using ChatGPT to write papers. They are. And there's also teachers that are using ChatGPT to grade papers. Right. Right.
So for all of us, do we have, do you want to have the self discipline to learn it, to figure it out, that you listen to podcasts, you find your, your areas where you can educate yourself on that so that way you can make your business better. Right. Because if you don't, before you know it, you'll have a situation on your hands like Starbucks had with Luckin.
So I just think it's, it's an incredibly exciting time with just so many different things going on where we now have capabilities to work smarter, work better, more, more digital forward than ever. And it's just the beginning. So I think it's truly exciting.
Speaker B:Yeah. Well, Peter, thanks for joining us today. Exciting topic. Thank you for sharing your wisdom.
I know you've spent many years becoming a much more qualified expert on this topic than I am. So I really appreciate you sharing that with us and, and talking about some of the trends and opportunities you're seeing.
And I just leave our audience with echo your comments. Find a way to get started. I think more than anything else, what we've learned is that the learning cycle is compressed and very fast.
But because of that, the sooner you start, the faster you get there. I mean, it's like you can get there faster too. And I think don't let the distractions or fear or concern or anxieties hold you back.
Dive in and get going. Be thoughtful and careful about how you proceed. But proceed is my core message. Thanks, folks. Thanks for joining us today. Thanks, Peter.
Speaker A:Thanks everyone. Thanks for having me.
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