Senior Fool analyst Tim Beyers, caught up with Leach, for a closer look at this newly public company. They also discuss how watching a stranger upload a reimbursement receipt, kicked off a decades-plus-long journey, growing from WTF to RFP, and why Ibotta's growth strategy looks like that of a library. 

Leach and Tim Beyers discuss:

  • Ibotta's strategy as a digital promotions network, connecting major retailers and consumer packaged goods companies.
  • Utilising AI to analyse consumer purchasing data.
  • Humble beginnings and the challenges of building a two-sided marketplace.

To catch full episodes of all The Motley Fool's free podcasts, check out our podcast center. To get started investing, check out our beginner's guide to investing in stocks. A full transcript follows the video.

This video was recorded on Oct. 27, 2024.

Bryan Leach: You think about the wealth of nations, Adam Smith, one market clearing price for everything. Well, not really. If you knew everybody's elasticity of demand and prior brand loyalty, you could strike the right price for that person or a group of people. It's just that Adam Smith couldn't envision having access to that information in 1776. 

Mary Long: I'm Mary Long, and that's Bryan Leach. He's the founder and CEO of Ibotta, a promotions and performance marketing company that likens itself to the trade desk of digital rewards. You might have used Ibotta yourself. The company has a namesake app that allows consumers to clip digital coupons and earn rewards, including cashback on a number of purchases, but Ibotta doesn't just exist to make you money. It gives retailers like Walmart and PNG to name only two basket-level data about your purchases so that companies can get even better at selling products. Leach founded Ibotta in 2012, but the company IPO earlier this year. Senior Fool analyst Tim Beyers, caught up with Leach, for a closer look at this newly public company. They also discuss how watching a stranger upload a reimbursement receipt, kicked off a decades-plus-long journey, growing from WTF to RFP, and why Ibotta's growth strategy looks like that of a library. 

Tim Beyers: With me is the CEO and founder of Ibotta, Bryan Leach. Bryan, welcome to the show. Thanks so much for being here. I'm not sure how many people are familiar with Ibotta. You've only been public for a little bit now. You came public fairly recently but we've been in business for quite some time. Let's talk about what Ibotta is. Just a quick introduction to yourself and what Ibotta is.

Bryan Leach: Sure. Thanks for having me, Tim. Ibotta is the largest digital promotions network in the world. We work with consumer packaged goods companies like Coca-Cola, Kellogg's, Anheuser-Busch to help them intelligently promote their products to 200 million consumers through our network. We started out with an app that you can download for free, called the Ibotta App. Fifty million people downloaded that app. You can use that almost anywhere to earn cashback rebates on PayPal, for example, or gift card credit, when you take a picture of a receipt or check out with your loyalty card. That was our original business. We now are powering a whole system of what we call publishers, so these are channel distribution partners, white label partners. The biggest of which is Walmart. We are the exclusive provider of all item-level digital manufacturer offers on all Walmart digital properties. If you're on Walmart.com, whether you're buying in-store or online, you can find 1,200 different offers that you can use to earn Walmart cash. We sit behind that and source all of that offer content and power that. Not just Walmart, Dollar General, Family Dollar, Schnooks, we recently announced Instacart as a major partner. You can think of us as somewhat like The Trade Desk, a single interface, but instead of a single interface to distribute display ads on the Open Web through a network of publishers. We're a single interface to distribute digital promotions through a network of publishers.

Tim Beyers: Dose this always result in their cashback offers? I use Ibotta. I'm not yet at my next $20 cliff but I'm getting close, so these are all cashback offers?

Bryan Leach: On the Ibotta app, they're all cashback offers, but these days, for example, Walmart has a cashback structure. Dollar General has something called DG cash, but with Instacart and with Family Dollar, they're actually digital coupons. They're digital discounts. With Shell, the power of Shell fuel rewards, their points. We're agnostic as to the form that the reward takes. What we're really passionate about is using AI to decide what is the right offer to put in front of the right consumer at the right time. If I can figure out using machine learning and studying your history of purchases over time down to a very granular skew level, what you're likely to purchase, I can then figure out what would look like a stretch, an incremental sale from the standpoint of a brand manager at Pepsi, for example, if you're buying two Pepsis a month, I want you to buy three or four. Then I can figure out what's the smallest amount of financial incentive necessary to get you to change your behavior? It all comes into one equation, which is how do I get the lowest possible cost for incremental sale? We're solving that equation using smart, targeted promotions, and our AI determines the parameters of these promotions to solve for the lowest possible cost per incremental sales. That's never happened in the history, over a century-long history of promotions, and it's bringing this incredible ability to measure real-time the incremental sales that we drive, and then use AI to get smarter and smarter so it's more and more efficient.

Tim Beyers: It's really interesting. This is very sophisticated where you are today but I heard you at Denver startup week convincing folks, because the way this sounds like, Bryan, is, this is a bit of a two-sided marketplace. You got to get supply and get demand, if you have lots of demand and no supply, that two sided marketplace doesn't work. You told a story about actually building this up from the beginning. I would love for you to talk about this from the beginnings of Ibotta because I think it illustrates where you've been to frame where you are today. It's interesting.

Bryan Leach: Absolutely. Look, I can't stand it when people come onto these shows and pretend that they're fully formed and that they have this idea from day one. We all know that's total rubbish. No, we started out in the basement of a fire station with no windows in Downtown Denver paying $8 a square foot and just trying to hang on for dear life, buying whiteboards out of consignment and Commerce City for 10 bucks apiece. I started this business in the front of my house with nothing but a PowerPoint and no prototype or team or anything. Along the way, we had to figure out this two-sided market. One of the problems we had is that a free app that pays you cash. Sure, I'll download that app but then if you don't have enough critical mass of offers in your app, people will try it once or twice and then they'll say, well, there's nothing here that I want to buy. If you have eight offers, you just see a huge rate of churn and you can never get off the ground. You have to stimulate that two sided market somehow. For us, one way we did that was we started self-funding the offers. Now, we did this totally legally. We went and licensed copyrighted images of these products from a database that gave us the right to do so and then we would decide, let's do this box of cereal or this bag of M&Ms, whatever we thought was popular because it was Easter or whatever, and we would put it on the app. Well, what would happen would be these companies would figure out that nobody in the building knew anything about this promotion.

Why was the product on this app and who did this deal and whose budget is it coming out of and how does it interact with their trade calendar and so forth? We would get phone calls, and very often, they would be angry. You can't do this, and we would say, Well, no, it's actually entirely legal to do this, but would you like to see the results because the results are very compelling and you should be funding this. We're going to move to somebody else's product here, but we'll happily share the data. I'd say 50% of the time that led to them then becoming clients of Ibotta. We call that the WTF to RFP strategy, which was quite effective. It even netted us our current Chief Marketing Officer, Rich, who was then the Brand Manager for Classico at Heinz, he called up and said, "You are promoting my product. Who are you? Tell me more about your business? It sounds interesting." Next thing, he's interviewing on a Google hangout and driving his family all the way from Pittsburgh to Denver to become part of this crazy adventure. By putting it out in the universe, the way we wanted it to ultimately look, it willed itself into existence.

Tim Beyers: Those are amazing beginnings and for those, I would encourage anybody who hasn't seen this to try the Ibotta app, because it is a pretty slick app. You do have a lot of relationships with a lot of different stores. Obviously, I shop it at King Soopers, so I get all the offers that are available to me in King Soopers, and you literally put it in a basket, you go to the store, and if the deal is right, and it's there, you just buy it, I scan the receipt, and there you go. There's cash back within a period of time. You said something though during Denver Startup week that I want to park on as part of the founding story, Bryan, because I think it speaks to why you're messing with AI right now. I thought I heard you say something about receipts having a lot of data that is just not used either properly or just not captured, talk a little bit more about this.

Bryan Leach: The way I came up with the idea for this company was I was riding on a plane back from Brazil. I was a lawyer practicing in international arbitration, and I watched this woman taking pictures of her receipts to submit for expense reimbursement. It got me thinking about all the information that's sitting trapped on this receipt. It's the price that you're willing to pay for products. It's how many of them you bought, how frequently you buy them, exactly which skew or flavor or variety are you buying at what store location, at what time of day? If you understood that over time for every consumer, think how you could shape the way that we advertise and promote. You think about the wealth of nations, Adam Smith, one market clearing price for everything. Well, not really. If you knew everybody's elasticity of demand and prior brand loyalty, you could strike the right price for that person or a group of people. It's just that Adam Smith couldn't envision having access to that information in 1776. The idea of this new technology of a phone of optical character recognition, being able to create in effect an e-receipt that the consumer could use was compelling to me, and that's why I called the company, Ibotta, as in, I bought a bag of groceries. It was the power of our own purchase information to make our lives better, to make the process of saving money better, learning about new products better, and we went from there.

Tim Beyers: Is it fair to say then, by the way, I think that's the first time that we have had Adam Smith and the Wealth of Nations on Motley Fool Money. Congratulations, you're a pioneer, but it does sound like part of the advantage of Ibotta then is that you have all of this history of data that is allowing you to maybe price offers a bit more effectively today. Can you talk me through this a little bit? What are you doing and how has this changed over time, the way you look at and capture and use data for what is effectively this marketplace?

Bryan Leach: This is a really exciting and unprecedented moment in 140 year history of promotions, which itself is a $20 billion industry just in America, just in CPG. Why is that? Two reasons. The data is that you're talking about, having full basket, item level data. Not the data credit card companies get, which is what's called Level 2 data or transaction level data, but actually seeing inside the basket, what do people buy? That's important because now you can be much smarter about targeting offers. As you say, Tim, the idea is, I don't want to subsidize people for offers and products they were already going to buy. I want them to buy something that's incremental. The whole point of a promotion is to change behavior, not to reward someone needlessly for what they were already going to do. Having all that data allows us to be much smarter about putting that right offer. How many should I ask them to buy? How much money should I give them? You can titrate those with that data. The second thing that's even more powerful is measurement. It has never been possible in the history of the $200 billion spent in CPG marketing every year, to be able to measure in real time the effect of a given tactic, whether it's television, radio, out of home, billboard, on terms of incremental sales. What happens is, you run an ad, you do a billboard, you do the jersey patch, and then you have a mixed media model 12 months later that's econometric model that tries to figure out what the different causal variables and assign this percent of causality to this and this to that in this window. It's an imperfect science driven by assumption. What we do is create a scientific method, where we can look at millions of consumers and create a test versus control and say, these are the people exposed to these promotions, and these are the people who are not.

Let's look at the Delta, those are incremental sales, and then let's calculate the cost per incremental sale and put it in a dashboard. Now the brand manager for the first time ever can say, well, at $1.18 per incremental sale, I will take as much as you can give me, but I don't want to spend more than $1.25 per incremental sale. That whole idea allows for an agility that is not an annual planning process that every CPG has had since the dawn of time, where your annual plan, wait for your measurement 12 months later, adjust the annual plan. Now you can be much more nimble, much more agile. The data is really unlocking a much more sophisticated use of performance marketing, as we call it, because you have a tool that you only pay when there's a sale, you're not paying for impressions, you're not paying for clicks, and you can know in real time how well it's going totally deterministically down to a measured skew that's tied out to that human with minimal modeling, that's something that's extremely compelling. It is a really new time, and people are taking another look at promotions and saying, this should be a major pillar of my marketing plan, no matter what brand we're talking about.

Tim Beyers: I want to park on something you just said about the way that you get paid or at least it sounded like the way you get paid. I'm pretty sure I've read this properly. You get paid when an offer is concluded, when there's a sale. Now, you just said, this is not paper click. This is the typical stuff that we see. Is that a strategic advantage for Ibotta? Does that make your attractiveness to a partner? That, look, we have all of this data, and this is a win-win. We're only going to get paid if you're winning and getting incremental sales. Is that the way that you pitch this business?

Bryan Leach: Yes, absolutely. If you get 10 billion impressions and you sell 10 products, well, we'll charge you 10 times our fee per unit sold. Let's say our fee is $0.80. You pay eight bucks. If you get 10 impressions and you get the same 10 sales, you pay eight bucks. At the end of the quarter, General Mills doesn't report impressions. They don't report clips. They don't report prints or clicks. They report sales. They're especially interested in incremental sales. If you can prove that there is a causal relationship between this strategy or tactic, this promotional approach, and incremental sales, and you can move millions of incremental sales because you're at a scale where your network can do that, there's really no other solution that is de-risk because even if you buy on Facebook or on Google or television, you still have to bear the risk of whether the creative is going to result in conversion.

Bryan Leach: Even if you could measure that, which you can't, you have to rely on these other proxies to fit because it's an offline, 90% of CPG products are sold offline. It's very hard to measure conversion unless you have 85 point of sale integrations like we do with the retailers. So even if you could measure it, which you can't, you're still bearing the risk that each campaign might not hit. What if the redemption rate is 3%, or 5%, or 10%, by cost per actual unit sold is wildly varying? If I pay $0.10 a clip and I get a 10% redemption rate, I paid $1 per unit sold. But if the redemption rate goes down to 5% and I still paid on clips, well, I just pay $2 per unit sold, and I can't predict that. We take that guesswork out. Now you're paying on the bottom of the funnel, a fee per unit sold, and that is why we've been able to get 3,000 CPG brands to do this and invest close to a billion dollar in this network because they love that performance element of what we do.

Tim Beyers: That makes a lot of sense. I have to tell you though, as you're talking about, I like, why in the world hasn't Procter & Gamble come to you and written a giant check and said, Bryan, come be part of the family.

Bryan Leach: Well, it's a great question. We are ultimately a network. The value of our network is that we have lots of different brands and lots of different distribution channels and partners. Same reason we aren't bought by one particular retailer, it would destroy value in a way because the value is that we're a platform. Much like The Trade Desk isn't bought by Condin asked or ESPN. They want to serve all the advertisers that want to use that network, and they want to reach and push their content out on all these publisher sites. Now, they can have a preferred relationship, they can have a strategic partnership, they can get more preferable access to early, better testing of our features, they can get better pricing and so forth. But fundamentally, we don't exclude brands. We don't have a strategy where we say, we only work with Coke and never with Pepsi, we only work with this mannas and not that. We're like a neutral Canvas on which everyone is invited to paint, same as a radio, same as a television, same as the newspaper.

Tim Beyers: That's a great way to segue, I think, into the growth strategy here. We know where you've been, WTF to RFP, you're way, way past that now. As you said, you are orchestrating all of these deals for some very, very big retailers. I think it's now, is it two years? No. Maybe more than two years. How many years has it been since you became exclusive with Walmart? Because I want to talk about that a little bit.

Bryan Leach: Let's talk about both topics. Let's talk about our growth strategy first. I think with regard to the growth strategy, I like to use the analogy of a library. If you were the president of your Alma mater, and let's say I was on the board of your Alma mater. I said, the main metric we're going to grade you in your new presidency is the number of books checked out of the library. You say, well, that's very strange, but okay, I'll go along with it. I said, I really am just going to judge you based on how many books you were able to get checked out this year versus last year. What would you do? Well, you would first of all say, well, that's all that matters, let me get lots more students on this campus. Let me increase the admissions rate, let's get more potential people who might walk in and check out a book. Make sure everybody is armed with a library card. Second thing you would do is you would say, well, we have about one million books in our library. Let's get the number of books up to three million, five million. Not because any one person is going to read all the books, but because the more books, the greater likelihood that you're going to hit someone's interest. The third thing you're going to do is you're going to get a better system for matching students and books. Instead of making you come in and use a complicated system to find a book, what if we predict what next book you might like and use a trolley and deliver it to your dormant? If you did all three of those things, you would have a huge increase in the number of books checked out. Well, we get paid based on the number of books checked out of the library. Only the books are offers, and those offers are redeemed by what we call redeemers, think of them as the students. If we can add more redeemers to the ecosystem by bringing in a company like a Walmart and growing the audience from 5% penetration to closer to 100% penetration over a period of years, and then bring in a bunch more publishers, that's prong one of the growth is grow the addressable audience. At the same time, you're also growing the number of offers and the duration of those offers and the quality of those offers, think of having three copies of a book. It's going to be there for more people for longer. That offer is deeper than it's going to stay on that network for longer, and there's more of them. That's another lever.

Lastly, the AI to match the offer in the consumer means the yield is higher, because you're better at predicting what's actually relevant to that person. Basically, we're doing all three of these and in that order of importance, the gross strategy is add more redeemers, add more offers as we expand beyond grocery into general merchandise, like toys, electronics, etc. Then ultimately improve the tech itself to make that more efficient. I think Walmart was the anchor tenant in that process. We're only a year or two, we launched to 100% of Walmart shoppers in September of 2023. We're barely over a year since the full roll out of Walmart. There's many, many years, we're in the first inning of that as they socialize and market the program. It's grown like a weed with relatively little marketing so far, and that's then led to Dollar General, which led to Family Dollar, which led to Instacart, which we hope will lead to other market places like that joining. That's Strategy 1. Then meanwhile, all the things we talked about in terms of targeting and measurement. That's how we're persuading the chief marketing officers of these CPG brands to say, you know what? I got to put 50 million or 100 million into this because this is the single most measurable and efficient way that I have to move incremental sales. That's Strategy 2, get more books in the library. Then lastly, our tech team, we have 450 engineers, most of whom are doing some form of AI, machine learning, data science, leveraging this data. We're trying to invest and really being the most innovative and differentiating from our competitors that way. That's how we map a cheesy analogy to a strategy.

Tim Beyers: Is it more important to get the people who are on, say, like an Instacart, or who are shopping at Walmart to take up more offers, or is it more important to grow? Because you've said, I wonder what the utilization is of your existing network, is that where the juice is right now, or do you just have to go out and get a bunch more partners? That is the number 1 thing that really adds rocket fuel to the growth. Maybe it's a combination of both.

Bryan Leach: It's a combination of both. We have juice, we have rocket fuel all over this joint. We want to add more people within the existing Walmart, as we like to say, Walmart is the next Walmart because we're less than 10% penetrated there. Then there's all the other Walmarts, and not even just retailers. Think about recipe sites, all the places where purchase intent might arise, a financial services website, for example, lots of different places that could plug into our API and ingest our content, show it to their end users. That is probably the primary driver is grow the audience because the bigger audience will itself unlock more supply of offers because when you have this level of growing audience and efficiency, brands want to advertise. We've gone from sourcing $50,000 to a billion dollars over a 12 year period and it's a two sided market that steps up, and as you grow the audience, typically the advertising dollars follow that on some, there may be short time lags, but generally speaking, that's how it goes. The second thing you want to do is get at the utilization rate, which you do in two ways. One by having more offer coverage, more books in the library, and the other by having just better technology. For example, on Instacart today, you can't see offers if there's also a strike through price on that product. Well, under our version, you'll be able to see the offer and the strike through price. If it's bread, it used to be $5, strike through $4, you have a $2 offer, it's $2. That wasn't true before. Improving the UX, making it more prominent, having a single gallery with offers, doing a better job of life-cycle marketing, retargeting. We bring all that expertise and almost op act as consultants on rewards as a service. That is because Tim, we only get paid when there are sales. Other companies have never had to develop that expertise because they're happy if you clipped an offer and never redeemed. Up clip all. Oh, okay. Well, we need you to get to the bottom of that funnel and remember, hey, you unlock this offer, don't let it expire. We partner to try to increase redemption rates over time. That is a secondary driver, nonetheless, very important and exciting one.

Tim Beyers: Can we talk a little bit about, all of this sounds amazing, and when you're using AI here, what do you have to do from an investment, like a capital allocation standpoint? You're the guy, so you are putting capital to work with your team. What do you need to do to build out all the infrastructure that makes this possible and supports this kind of growth? Because you are talking about some hyper growth here, especially, I can imagine there's a lot of stuff that supports just exponential adding of offers onto this platform.

Bryan Leach: Yeah. We're building ever more self service tools. We've just come out with our campaign optimizer product, which is a way for brands that are smaller to have more self service capabilities. We want to be able to programmatically allow people to buy their way onto our network. The vision is that you're buying an ad display upper funnel ad on The Trade Sesk, and you can add a component of direct response or reward where you click from that ad and choose a retailer where you want to get a reward when you buy that product, and then we use that to track whether or not you purchased that product. There are so many technologies that we need to build and continue to upgrade. The biggest, of course, being just the engine to decide for any individual skew, for any individual consumer at any moment in time, what is the appropriate net price that person should be paying? My wife is going to tell me to go to the store and buy Pellegrino. I don't mind whether it's $3 or $4. I'm a little bit price insensitive, more on the affluent side. I just grab the green bottle because I don't want to get in trouble with my wife. My daughter, she buys water based on what's on sale. You shouldn't be giving me the subsidy, you don't need to give me that. You needlessly gave me a dollar off. You should have charged me the four bucks and given $0.75 of that to my daughter to get her to buy your product, try it love it, and be willing to stretch and buy it in the future, and drop the $0.25 in your pocket. That mathematical equation relies on a lot of compute power, a lot of machine learning. Yes, we are a tech company. Our predecessor rivals, they're not tech companies. They're coupon companies. They are coupon companies that are struggling to get into digital, we are a digitally native company that isn't particularly interested in coupons. We're interested in the question of how do you find the efficient frontier of pricing everything you sell? If you haven't used AI to do that, and you're using AI to do consumer listening and write your ad copy, that's awesome. But the most interesting application of AI is in price, and figuring out how to clear the market more efficiently is a huge, huge unlock for every CPG brand, especially those that sell things in store, where these kinds of capabilities just haven't really existed.

Tim Beyers: Let's try and end around this. I want to get a sense of, imagine the future here because you are not consistently profitable, but you've shown profits. That's happened. You've shown some cash generation. Let's imagine, is it five years from now, three years from now? Whenever it is, you are consistently profitable generating a boatload of cash. What happened, and if it didn't happen, what went wrong?

Bryan Leach: First of all, we have been profitable for eight straight quarters. If you look on an adjusted EBITDA basis, we've been profitable since six quarters before our IPO, and we're cash flow positive. We generated $33 million in cash flow in the second quarter, and what we said on our earnings call was we expect to generate over $100 million in free cash flow this year. But yes, to answer your question, we're going to generate a whole lot more cash flow. Our margins are expanding. We're already a rule of 60 company, and our margins are growing, we think they can grow into the 50 plus percent range because we don't have any cost of acquisition.

Tim Beyers: On a gross basis, are you saying?

Bryan Leach: No.

Tim Beyers: On net basis, or on an EBITDA basis? Okay got it.

Bryan Leach: EBITDA basis. Yes. To answer the spirit of your question, Tim, Yes, we're going to grow our EBITDA margins. Our gross margins are 75-80%. Our EBITDA margins are going to go from the 30% range to the 50 mid 50s even into the 60s over time. If that doesn't happen, that will be because we did not continue to expand our third party publisher component of our network. Our DDC app isn't growing that rapidly. It represents a smaller and smaller percentage. That's anchoring down our EBITDA, we need to bring in more Walmart. Walmart is a great deal for us. Every redemption that occurs on Walmart, we get paid on average about $0.80, and there's no revenue share. We drop almost all of that for every new dollar of revenue, we're dropping almost $0.70 to the bottom line incrementally across the whole network. Now, most that's being anchored down by the app, where we have to pay cost to acquire Tim and get them to download and register, and refer friends, etc. If we are unable to grow the margins the way we say, it's because we somehow we couldn't get more people on Walmart to redeem offers. We couldn't get more Walmarts to join, etc, or we had to somehow alter the fundamental cost structure to bring those retailers on board. We have a lot of good precedents now with very, very good economic arrangements and great margins. I'm feeling pretty good about the recurring revenue.

We know there's a certain baseline level to which say Walmart e-commerce grows every year, like 20%. You can look it up in Walmart's earnings report. If they stop growing their business online, that would be a headwind. But as long as they're growing, we're growing because we're intercepting all of those searches and all of that traffic, and that's just one publisher. I think it's a pretty unusual business and that it is a high growth business with a high margin structure and winner take all, very high barriers to entry. It's not in a sexy market. But it's in a market with $200 billion that has to go somewhere to battle over market share for these products, and that's just in the United States. As we look out beyond the horizon you're talking about, I think there's opportunities elsewhere and in other verticals beyond CPG, whether it be some of those general merchandising examples that I mentioned.

Tim Beyers: I guess that's not going to be sexy to everybody, but I'm going to guess that there are some people that will find that sexy Bryan. Thank you so much for being here. Really appreciate it. This Bryan Leach, founder and CEO of Ibotta. Thanks, Bryan. Really appreciate it.

Bryan Leach: Thanks for having me.

Mary Long: As always, people on the program may have interests in the stocks they talk about, and the Motley Fool may have formal recommendations for or against, so don't buyer sell stocks based solely on what you hear. I'm Mary Long. Thanks for listening. We'll see you tomorrow.