A Product Market Fit Show | Startup Podcast for Founders
00:16:10 · Dane Atkinson
[00:16:10] S0: Actually, I took back. We sold SumAll, and then we took part of the tech stack team. We had this great partnership with Square and Toast, and those folks, and we started out as geeks. Could we use that data that had usually been invisible inside the industry of brick and mortar because they have less technology, surprisingly, than a lot of other sellers or categories and do something productive with it? We built this, and here’s a great idea. Failed product market fit. We built a predictive model. It used to be called machine learning loops. Now, it’s called AI because it’s sexier. But it was very effective at understanding the future sales that we go to a coffee shop, [unclear] being the early customers of ours, and say like, we know what you’ll sell in a week. We can reshape your ordering behavior, and your staffing, and everything else to utilize that forecast. They loved the idea. They used it. It saved them waste. It made their business better, but it was a fraction of the problem. As we sat there with our customers, the vendors wouldn’t deliver after we put the order in for them to deliver. Or they would come in the middle of business, or they would have reconciliation problems and tons of invoices, or they would steal money. We were shocked because we were tracking the data, how systematic a lot of the industry had to be like, oh, these property bags are $18, and then two months, they’re $23. Who’s checking the invoice? It went to $23 and it was obviously intentional because it happened to all of our customers. It seemed that would be useful in of itself, but the real problem was that they needed infrastructure. Having had the experience of getting excited about software was able to break the VC pressure loop. It wasn’t easy. It was super duper hard, because again as a founder, you come to this thing often with either an idea that you’re fascinated by and you think the idea is it, or you’ve made a promise to your investors that you’re going to deliver on the solution. We had sold some of our most amazing investors on the idea that we were going to bring AI to an ancient industry and make them more efficient. Those would be a pure SaaS, gross margins in the 80 percentile. Everyone loves it.
00:18:19 · Pablo Srugo
[00:18:19] S1: Just for background here, you raised a $6 million pre-seed, I assume, at idea stage, just giving your background, and that was kind of the pitch you delivered.
00:18:26 · Dane Atkinson
[00:18:26] S0: Totally. We were very lucky. The quality of folks, and then they bet on my gray hair, the eighth kind and a lot of machine that I am. That was the vision, and we’d gotten some really good test data that that was having an impact. But it was having an impact that the customers didn’t care about. An evolution I’ve had along this journey was it is much easier to think of a customer, at least for me. Obviously, there’s lots of different ways you go about product. I have a friend who only can do things on spreadsheets and that’s how they figure out the product market fit. For me, if you pick the customer you care about, it makes it easier to look at the problem that you’re solving is successful or not successful without that ownership. When you come into the startup and you’re like, my idea is I’m going to make hats red, you’re screwed. My idea is like, people are getting wet. I need to solve it. You’ll find a way to expand to what actually works. I love the idea and I’ve owned coffee shops. Those people are such amazing humans try to make their neighborhoods better. They’re basically the founders that you guys deal with on a much smaller scale there. They’re trying to make a better world and no one’s helping them. When we were sitting in a coffee shop in a birch down in Spruce Street, and a vendor walked in with a giant new boat and disrupted everything, or we’re sitting at a coffee shop of Joe’s and the barista is like, I got to go. I love talking about the AI, but we’re out of milk. The milk guy didn’t show up and I’m going to run to the deli. I’ll be back in 20. We keep on talking. It’s like, okay, this clearly is a bigger problem than the hat we’re trying to invent for you. You need a raincoat and an umbrella. You need the whole thing.
00:19:57 · Pablo Srugo, Dane Atkinson
[00:19:57] S1: Was that by design that you’re in these coffee shops, by the way? Were you just there watching or you happened to be there on something else and you saw these things happen? [00:20:04] S0: Again, there’s a lot of different methodologies out there. For me, and this is something that I’ve done through all the companies, Squarespace included. We had customers that we were friends with and we answered tickets. I answered thousands of tickets. There are tens of thousands tickets from his time there. You want to stay very close? I have a rule that I have to have coffee and a coffee shop every day and I’m going to talk to a customer every day. Even now, [unclear]. [00:20:31] S1: Every day, wow. [00:20:31] S0: Every day. This industry’s super easy. It’s not as hard. [00:20:31] S1: It’s true, but it’s still I would have thought every week, you know what I mean, like you sell, but no, every day, okay.
00:20:31 · Pablo Srugo, Dane Atkinson
[00:20:31] S1: It’s true, but it’s still I would have thought every week, you know what I mean, like you sell, but no, every day, okay. [00:20:36] S0: No, because a lot of the best companies out there you can see they drift. They get fascinated. We raised $100 plus million. You get it. There’s a whole different world that you get sucked into. If you drift too far away, it’s really hard to steer the North Star, which is at the scale, my primary job is to hold the vision for the company and try to make sure it still sees that future. But going back to sitting in a coffee shop, and I suggest our customer, everyone out there who’s starting to figure the product makes best friends of a number of their customers and gets a way to be really inside that experience in whatever visibility you have. Whether it’s watching the customers sparkle in the eye and sitting with them, or seeing how their metrics are playing out or something that’s being attached to that very important part of the process. We saw that our system wasn’t the solve, it was just part of a bigger picture, and then had to convince everybody that we’d gone down the wrong road. [00:21:32] S1: What was that like?
00:21:32 · Pablo Srugo, Dane Atkinson
[00:21:32] S1: What was that like? [00:21:33] S0: Horrible. It was rough, and I’m old. It’s not my first time. Actually, all the advice our investors gave at the time was totally true. Like they said, you’re going to screw your multiple, and yeah, sure as hell, screw their multiple. No doubt about it. We have trucks and drivers in 14 cities and <laugh> it’s bananas and it’s tough. They’re like, it’s going to be gnarly and all these things that I think were right. But from my perspective, and the company’s perspective, and even people in the company were like, I didn’t sign up to build software for a driver. I want to build AI predictive models. Even your internal culture was like, why are we swinging so far from this that it made sense? [00:22:18] S1: How many people were on the team more or less back then, like 10, 15?