The Exchanges

Q Okay, so you have the app, and, and it launches at, you launch it with this restaurant, and I mean, how'd it work?

A Well, I remember we had a launch party with our friends and family, and we invited them all to Firebrand Saints and convinced them to download the app and try it, and I think some people got through it, but it was, it was actually quite buggy, I remember. Um, because the infrastructure we were building on top of wasn't as reliable. It wasn't built for, for cloud, right? These systems are built for in-store interactions. And, and so beyond that first day when we had that launch party, when we got maybe, you know, 50 or so people paying, we were never able to figure out how to get users to pay with any sort of velocity after that first day. And we would, like, I remember we'd go out, Steve went out there a bunch of times and spent time Uh, to try to, like, get people to understand how this works and to download the app at the restaurant.

AI assessment note: “some people got through it, but it was, it was actually quite buggy”

Q Alright, so you're, you're talking to restaurateurs, and they're saying, you know, the thing that really is really annoying is the system that we have. It's like, it's bulky, it, it, it's complex, it's, and, and this is getting the, sort of the, the gears in your head to, to start to spin about, well, maybe that's actually the problem?

A Absolutely. In fact, I remember, I had a conversation with, um, The owner of a restaurant crawl finale desserts, Chris Kane, he was, uh, um, one of the first, I'd say, like, full service, like, busier restaurants that was open to giving us a shot. And, um, I remember sitting with them and pitching toast, and my pitch was anchored on a few things, because, you know, these systems are hard to switch, and people would describe these switches as, like, root canals, and so I, I pitched it as, like, yes, of course, we can do all the things you do today, but there are a few things that are unique and better. One, we have these handhelds, so you can take the order and payment at the table. Two, it's got integrated e-commerce, As online ordering was becoming bigger, so you can, you can, people can discover you and order online, and you get incremental demand. And then three, um, you know, we talk about how you can access and manage everything, uh, from anywhere. And so, when we sat down with Chris, he said, it's a good vision, but like, let me show you, like, what it takes to run this. I think it was like, they had a location, Harvard Square, and in the back bay, and they had a, a commissary for a lot of their catering. And it's like, well, I've got the point of sale system. I've got a company providing payments. I've got a loan with somebody. I've got the separate software for accounti…

AI assessment note: “Absolutely. In fact, I remember, I had a conversation with, um, The owner”

Q they, I'm assuming they're not going to get rid of it right away, because I don't know if this is going to work, but it's a big deal to, to shift from one system to another system entirely. I mean, You know, and then train everybody on it and to try to do that while still running a restaurant. So how did you convince the first restaurant to do this?

A The first restaurant was Dwell Time, and this was in Cambridge Port, um, and the pitch we made to him was, we can build you something that's a lot more restaurant specific than the system he was using, and he was using one of these cloud solutions that weren't purpose-built for restaurants, and, and then I remember, you know, we worked really hard for a bunch of months to try to get, get to what we felt like was something ready for production, and I still remember we were getting, installing this restaurant, and they open, and within 20 minutes of taking, like, the first few orders, it's like the system is down, and, um, now they've got a line, and they were, like, physically writing down the order, On a piece of paper and dropping it off in the kitchen and taking the credit card number down on paper and like trying to do this manually and realize as part of the experience that, uh, these systems are mission critical and like, um, can't break. So there's a lot of learning just in that first day.

AI assessment note: “the pitch we made to him was, we can build you something that's a lot more restaurant specific”

Q to adopt this, right? Because a lot of restaurants were, were not, obviously, they weren't happy with their point of sale systems, but still, like, this was going to be a huge overhaul for, for most of them, right? So, I mean, did you have restaurants who were like, I don't know if I even want to do this, like, this is good, just going to be such a pain?

A All the time. You know, we would, I mean, I think I must have pitched Hundreds of restaurant tours in the first couple of years, and very few said yes. Um, but I think there are a couple of things that mattered. One was, it's not just existing restaurants, it's also new restaurants that open. And when restaurants open, they've got to do the work anyways to set up something. And our value proposition was, instead of spending, like for a restaurant like Finale, for them to go buy a legacy on-prem system, you know, you might spend 50 to a hundred K up front. And so our pitch was very little up front and sometimes nothing up front. Uh, then we had a SAS fee. And then we had built into the platform, um, capabilities that, uh, you know, that the staff and the ownership loved. And so we had a few data points. Um, and I remember we would, we would code at the restaurants because the best thing you could do is, you know, when we got some of these early restaurant tours up and running is, Is to get Steve and John and Tim and others, like, you know, actually at location, helping install, helping train, getting feedback, and then improving the software. Uh, with restaurateurs, I always say that the restaurateurs in Boston helped us build the platform because, you know, we had a hypothesis for what we, we thought we needed to build, but until we got this up and running with, with customers,…

AI assessment note: “All the time. You know, we would, I mean, I think I must have pitched Hundreds”

Q its stride, and how COVID sends it right back to the startup stage. Stay with us. I'm Guy Raz, and you're listening to How I Built This. Hey, welcome back to How I Built This. I'm Guy Raz. So it's early, about a year and a half after launch, and Aman and his partners have been able to grow Toast to a few hundred customers. But on a day-to-day basis?

A The business was frankly struggling. On the one hand, there was some, you know, customers who were using it, and they were happy, or at least cheering us on. And, uh, But there were a lot of issues. Like, I remember at one point, all of the hardware we would ship would, like, come back, and we had lots of outages and downtime. Our customers were not happy with our support experience. I remember that was one of those times, actually, even more than when we pivoted to point of sale, that was, like, in my mind, one of the low points for us, because there was actually a good signal here that customers wanted what we were building. And in hindsight, it just seems so obvious, like, some of the things that we did wrong, but At the time, you know, part of the problem here was like, I was so focused on trying to grow the business and grow revenue that it probably didn't take enough time to step back and work with Steve to build the systems to scale, the capabilities we needed to scale.

AI assessment note: “The business was frankly struggling. On the one hand, there was some”

Q surprising that, that there weren't many people doing it. There were though some, And I wonder when you guys found out or learned about some competitors also working in this space, how did it affect how you guys operated? Did it, did it speed you, did it make you move faster? Did it make you more vigilant? Um, what did it mean for what you guys were doing at Toast?

A Well, when you talk to customers that were using Toast, that further reinforced for me That we were onto something, because we didn't have the brand, or the distribution, or the funding, really, that some of these startups had, and yet, you'd hear them say, of the cloud solutions, because some of them had tried a few, Toast was the best one. I'm a big believer, by the way, in, like, customer obsession and not being too competitor obsessed. Yeah. And, um, it, it, we were already working as hard as we could. You know, we were like all in on this, like there was no, you know, the only plan was to make this thing successful. And, uh, and so we didn't need any motivation to try to work harder or faster. And in fact, the hardest thing was once we got to a hundred customers, we actually, and we had this GFS partnership, we actually started to see a lot of interest.

AI assessment note: “we didn't need any motivation to try to work harder or faster”

Q And so you have a, an opportunity to get to 80, you know, the remaining 80%, and I'm sure there's a fierce competition with, you know, some of your, your, your rivals in the space. What is the, what's the unlock? How do you get to that, that those other, you know, the remaining 80%?

A I think it's a, first of all, like, one of the things that we focused on from day one was these busier restaurants, so even though we have 20 plus percent of the restaurants, we actually have more of the sales volume, because the average restaurant that's on toast has more sales than the average restaurant in America, and so one of the things, in fact, our marketing campaign that we just launched was called Build for Busy, Because the busiest restaurants choose toast, because again, we are purpose-built for restaurants. We have a tremendous amount of opportunity now with AI. We know, for example, that if a guest comes into a restaurant three times, they're more likely to become a regular. And so how do you create the right campaigns to bring those people back? As an example, we launched this product recently called Toast IQ Grow. Toast IQ is the branding behind our AI platform. And customers that have switched to it have seen sales go up eight percent. The analogy I like to use is, you think about as a McDonald's franchisee, for example, there's a lot they do to set them up for success. And in the restaurant business, A lot of the decisions that are made about how much food to buy, which suppliers to pick, how to price your menu, what marketing to do, how to schedule your staff is not driven by data often. In fact, it's often driven by gut and gut and some data, but I think the…

AI assessment note: “the opportunity for toast... is to leverage our data across the 20 plus percent”