Unlocking CPG Sales with AI Insights

Full transcript

All right, welcome back to the podcast guys. Today we're joined by Chris Sterbenc who's the Chief Revenue Officer at Aisle AI. uh Chris, welcome to the podcast. Thank you, it's great to be here. Let's start this by you telling us a little bit about what you guys do. at Aisle. So Aisle is a CPG analytics firm. What that means is we can take sales data and basically let the CPG brands use that information to visualize where they're selling, to identify where they're not selling. It's a great tool to track launches of new products and that sort of thing, as well as to identify white space and where they should focus. Across retail, there's a lot of different segments. We specialize in the convenience store channel, but we can actually handle data from any other channel as well. So big box, grocery, drug, and others. But in the C store, we've actually got some unique insights that we can share to the brands. Okay, and when you look at the trends that you're seeing right now, what are they?

Trends broadly in CPG or specific to our channel or what things would you like to learn about? Probably CPG. CPG, well, I would say that they're all trying to figure out how they could leverage AI somehow to sell more stuff. That's probably the biggest one. We go to a lot of the various industry shows, Bivnet, Expo West, and uh that is probably the hottest topic du jour across the industry. I could say also from personal experience, it's the hottest topic in every industry right now. All these companies are trying to figure out how they can leverage AI somehow and they're... They're all dabbling and just about everybody's at least playing with Claude or chat GPT, but they're trying to figure out how to actually build it into their business motion to get value and accelerate their growth. That's probably the biggest trend. uh Other ones that we're seeing tend to be kind of focused in various niches. So right now in, uh in alcoholic beverages, ready to drink cocktails and non-alcoholic beer are probably the two hottest spaces. Although you're starting to see also other strange things like hop water and things like that. uh The other thing that we're seeing quite a bit of is organic versions of things that have been around for a long time in the snack space. But these are healthier for you purportedly, and they don't have, you know, no preservatives and things like that. So organic chocolate, organic pretzels, organic this, organic that. It's probably one of the other biggest trends that we're seeing across the snack universe. And so in the C-Store world, the three big areas are beverages, snacks, and tobacco. And in tobacco, the big trends are all the strange new variants of uh non-tobacco nicotine or non-nicotine tobacco. It's kind of funny. So folks who want to get the same feeling but not get the nicotine can do tobacco or nicotine-less uh snuff or pouches. And then you've got all kinds of nicotine delivery mechanisms of pouches, pillows, uh and other alternatives like uh tea leaves that are turned into tobacco. And then you've got the whole universe of the vaping product. So very diverse and they're doing a lot of crazy things in terms of flavors, packaging and everything else away from traditional tobacco. So those are the kind of the big trends driving those three pillars of the C-Store space.

You mentioned AI as it's a very hot topic in uh basically every industry, right? How does it specifically play into your guys strategy and how you guys actually use it? Great question. So we use it a couple different ways in the platform and then we also use it as individuals. So we'll start with the platform. So the data set that we get is updated daily. It's the actual back office point of sale data from 23,000 convenience stores. And that stuff gets uploaded every day. And so we have literally a database with 27 billion transactions in them. And as you can imagine, it takes a long time for anything to process that. So we use AI to process each batch as it comes in each day. And then we, that's one layer. So we're processing just a vast amount of data and putting it into a single data lake and making it useful. The second way we use AI is it allows people to drill for insights in that data and refresh dashboards. So you could build out a dashboard and then it gets refreshed daily with the new sales data. And so AI is doing all the big data management. as well as the visualization. And then the third way it's used in the platform is we have a product called Kaya, which is a lot like chat GPT, where you can just freeform ask it questions. You could say things like, what are the top 10 stores selling my product in Texas this month? And they pop up. Oh, that's interesting. Three of them are part of the, of the break time corner store chain. I don't know the whole break time chain nationally, how many stores are selling my product in, you know, this month? They pop up, okay. Looking at the top store, what are the demographics around that store to get a sense of where my product is selling the best? And that top break time location might be in a largely Hispanic neighborhood that is of median age and median income level. And they go, that's interesting. But you don't have to be a programmer that can do SQL coding to go get these answers. You can just literally ask Kaya questions, just like chat GPT where it's like a conversation. And then when you get to somewhere interesting, I'd like to see that in a pie chart. It'll pop that up and visualize it. And so those are the three different ways that I all that we're using AI in the platform. And then uh in the sales organization, sales and marketing org that I run for the company, we're using it to do a lot of our creating of content. So blog posts, things that are on the website, case studies, and the personalized emails that we're sending out to, uh to prospects and customers every day.

You mentioned that you actually run the sales organization, right? And the marketing, like what's been the biggest challenge for you in terms of scaling the team? Uh, it's always hard to find, you know, a players. have three salespeople today, uh, and, uh, they were each hand picked and they're, they're all, all three very excellent producers. And, uh, you know, it's, it's, it's always tricky to recruit, hire, ramp up good salespeople. Uh, salespeople in general, all interview really, really well, even if they are not very good fit and can't sell. But the one thing they can do is interview well. So you find that, uh, if you've got about a 60 to 70 % hit rate. with your hiring and a sales team, you're doing a very good job. So that's probably the number one challenge, which is true to sales teams everywhere, anytime. I think the second biggest challenge for us really as a company, as we're scaling the business is we have this platform that can do so many things that it's hard to describe how you could use it. And so what we've been doing, and really it's been an evolution over the last year or so, is we're identifying specific business use cases and we're productizing. So you get a subscription to the platform and go crazy, but okay, where should I get started? I'm a category manager or I'm the head of the West region sales team. We can actually go through and structure specific dashboards for your role. And we can spend some time if you wanna talk through those products. But an example of one is called Atlas. And what that does is it allows you to identify white space in the channel where you're not selling your product today, but it also prioritizes all those stores that are not selling your product using criteria to say which ones have the highest odds of being successful selling your product by looking at the ones that are selling your product, right? And applying those same kind of parameters to all the stores that are not selling your product. So if you subscribe to Atlas, we go do all that work and deliver that back to you. And then that net of that, the business use cases, this is a prioritized list of target stores that you should be trying to get into for your sales team.

Who do you think benefits the most from what you guys are doing? who benefits the most? It's kind of interesting. The use cases and the value that they get varies by the size and maturity of the company that's using it. These are all CPG brands, right? So, you you take an emerging brand, this could be a brand new company. You've not really heard of them. They're like sub five million in revenue. So the whole world is white space to them, right? But what's most valuable to them is when they can do a new product launch, they could identify, say, 100 stores that they look like to be the best fit for them. They could do the actual launch and now they can track the progress of the new product sales daily across those stores. Which stores are selling? Which stores are not selling? What kind of velocity does each store have? What price point are they selling at? And then if they decide to run a promotion, you know, buy one, get one free, a BOGO or they can track the actual impact of this and they get refreshed daily. So it's very granular and it's very real time. And so from an emerging brand that's trying to launch a new product into the market, that's probably the number one value that they get is they can identify the best stores to try to launch in. And then they get that granular daily updated vision of what's actually happening. Right. Now that's the emerging brands. If you move up the chain to the challenger brands, you know, we're talking companies doing a hundred million, 200 million. For them, it's really about growing market share. And that's where that white space analysis really comes in because they're already in a lot of stores, but they're not in all the stores. And so uh as you know, you can't boil the ocean, you can't do it all at once. So where should we focus? Let's identify the highest value, most likely to be successful white space spores where you're not currently selling. And so that's probably the number one thing that we get. uh The other flavor of that is if you have multiple products or multiple SKUs, the other kind of white space we can find for you is stores that are actively selling a lot of your product, but they're only selling one skew, right? Let's see, if you've got, so we work with Spilt, for example, that's a protein milk product, and they've got four or five different flavors, know, chocolate, strawberry, whatever. And one of the things that we do with them is we find stores that are cranking out big volumes of Spilt, but they're only selling two of the four flavors. So it's an easy conversation with the store, like you're selling a lot of our stuff. Why aren't we stocking all four flavors, right? So that's an example of identifying white space so that the sales team can have really targeted specific conversations based on data, right? And so that's the kind of work that we're doing with a lot of challenger brands across multiple different CPG categories. When you get into enterprise, it's a little bit different. So enterprise would be your, you know, half billion, multi-billion dollars, your Kalanovas and your Nestle's and... They're managing a whole big portfolio of brands. These people, they've got access to lots of different data sources. They've got whole teams, know, whose job is to get this data, get it

in a place that's usable, drill for insights and present it back to sales and marketing to find actionable things. But again, what we're finding is they don't have visibility into this independent C store channel. So that's one piece of unique value we can bring to them. But the other thing we can do again is give them the opportunity to get that really granular daily update when they do product launches or promotion testing, because their syndicated data, which they get from Nielsen's or Sarkana or spins or even chains, it's a once a month data dump. So everything you get is kind of old news and it takes them a while to actually munch through the data. So it could be five, six weeks old before they actually get any insights from it. So like right now. uh April 8th when we're recording this, those companies are just starting to mow through their March results. Whereas the folks that are using our platform are looking at April 7th results. Very interesting. Okay, is there anything that you would change about the CPG industry?

Really? mean, it's an exciting, evolving space. There's constantly new brands innovating and doing crazy things in every category you can think of. I think that that forces the legacy players to stay on their toes. frequently what they do in reaction is they buy these hot little upstart companies. And so similar to the tech industry, where I've spent most of my career, you have a startup, you have a new idea. You build it, you take it to market, you prove there's demand for it. And then some bigger company, know, pays you a lot of money to snap up the concept, your customers and your products and add it to their portfolio. So um it's a kind of a cool cycle in that you've got, you know, CPG brand entrepreneurs that are launching new products all the time with the goal of growing them and then selling them off and then starting it all over again. So to me, I find it really, really fascinating because it's kind of like a parallel universe. to the tech space, is where I spent most of my career. How do you envision ILAI over the next few years?

Well, uh we're accelerating our growth uh and it's more more traction across the brands of CPG. uh There's the flip side of the coin, which is all the retailers, which interestingly, you know, the platform could do a lot of things for them, but we have not yet productized the most commonly needed use cases for the retail chains, right? uh We've got hundreds of small and mid-sized chains where we're seeing their daily data. already in our data set. And that's the stuff that we're using for the brands today. But we can flip that around and provide some really fascinating insights, especially for the category management teams at these smaller chains, because we've got 100 % of their data. uh So that's probably the next logical expansion for us. We just actually signed up our very first small retail chain uh last month. It's a four location chain. And so we will learn quite a bit from working with them and start to productize that stuff. And that will then become new messaging and then we'll proactively start to market and sell to the chains.

Okay, great Chris. So for the listeners who want to connect or learn more about your work or what you guys are doing, where should they go? Great question. our website is aisleai.com. So that's spelled A-I-S-L-E, like walk down the aisle in the store. aisleai.com is our website. And you'll find a lot of great info there about the platform, as well as some great case studies that talk through things like the white space analysis and the Atlas product. Okay, great. So thank you guys for watching and we'll see you in the next one. Next time, be on. Alright, so I hope hopefully this ends as it's still running for some reason. I will... What? It freezed for some reason. That's a very. Weird. So have this recording button, right? But it's not... Really? Okay, so it's a glitch on my side. Okay, great. So how did you find it, Chris? that was fun. Okay, great. So I will...