Welcome And What We Cover

SPEAKER_01 0:00

Welcome to another edition of Give and Ovation, the Restaurant Guest Experience Podcast. I'm your host, Zach Oates, and each week I chat with industry experts to uncover their strategies and tactics to help you create a five-star guest experience. This podcast is powered by Ovation, the feedback and operations platform built for multi-ner restaurants. Learn what's actually happening in your restaurants and exactly how to improve while driving revenue. Learn more at ovationup.com. And today we have got an icon of the industry, Sterling Douglas, the co-founder and CEO of Chowley. Sterling, you have been a pillar for a full decade now. How does that feel to have done something in your life for 10 years?

SPEAKER_00 0:44

Yeah, I don't I don't know if that's a good thing. I don't know. I would say it's something that I brag about. Sometimes I think about 10 years and I go, holy, holy cow, man, I've been in here a while. And also I was a baby when we started. But yeah, man, it's honestly the most fun part is getting to see all the different waves the restaurant industry has kind of faced. Right? I got to see the third parties, the cloud POS, the online ordering, and all the AI wave.

SPEAKER_01 1:07

So the ghost kitchens, remember those?

Why AI Adoption Feels Different

SPEAKER_00 1:09

Those were we still to this day have over a thousand virtual concepts on our platform today. That's amazing.

SPEAKER_01 1:17

Well, and what's interesting is that as you see these different changes, there is such a wide variety of adapting and fearing tech. And one of the things that's really interesting about this wave that we see with AI is I'm seeing restaurants lean into this more than ever.

SPEAKER_00 1:37

Yes.

SPEAKER_01 1:38

And it's incredible to see how quickly they're adapting this. And I know that you talk a lot about AI, and you are a huge proponent of AI. And so, you know, talk to us about your podcast and your theory on AI.

The Drivers Behind Faster Adoption

SPEAKER_00 1:54

To your point on the like embracing tech, right? The restaurant restaurant industry always gets a terrible, a table to rep. Like they don't embrace tech, they're always the slowest to adopt and all these things. And to an extent that's true, I think back to when we first started Chowley. I was literally walking around Wrigleyville in Chicago, uh, just walking into restaurants and trying to get them on the platform. And one of the biggest issues that we had, one of the biggest objections we had is they just didn't believe we could do it. Like I just literally were just like, you can't do that. Like, you know, some guy tried to do this or something. And that to me was like a perfect example of how they weren't adopting technology and how they weren't embracing it, how skeptical they were and how they didn't believe any of it. And on the AI side, I see almost none of that. Like restaurants are running toward this for a lot of different reasons. But for me, it's exciting because after watching a space get hit by wave after wave after wave, now I'm actually seeing them like just embrace this and all in, wanting to learn more, going to boot camps, doing certifications, like pushing the envelope, all the things that they should have been doing for all these different waves. And now I think that we're not going to see such a slow adoption on the restaurant side. Why is that?

SPEAKER_01 3:02

What's different about this than prior waves?

Building An AI First Team

SPEAKER_00 3:05

Yeah, I think there's a few drivers here. I mean, one is you just said COVID really changed the mindset of the restaurant tour. During COVID, technology was the savior, it was the only way you could keep your doors open, whether it was online ordering or all these different things. And so every restaurant kind of had to learn this whole digital experience. And so that really got them much more comfortable with tech and more tech enabled. They kind of exploded. We did a workshop a couple of years ago with uh like 200 different independent operators, and we asked them how many tech solutions they had, and the average was 28. The average restaurant had 28 pieces of software to run the restaurant. Now I think that's come down a lot as we've seen more consolidation. But I think that you kind of saw that big push. And so now on the AI side, I think that's a big driver. The other big driver is that AI brings efficiency. AI helps like make people more efficient, people can get more done. It's great for learning. Half of the sessions that I do, AI is teaching me something and doing research for me. These are things that entrepreneurs love, right? And they're drawn to. And so I think there's just kind of like this learning nature, this efficiency. And then you've also got this wave of I know tech, I know it can on my restaurant, I've seen it before. And I think those three things really combine into a lot faster adoption. Are these the things that you discuss on your podcast? Yeah, we talk a lot about adoption. So, real quick, we do a podcast, AI for restaurants, easily found on LinkedIn, it's on YouTube. It's literally just AI for restaurants.ai. So we say AI twice, you know, just for the SEO.

SPEAKER_01 4:32

But or the GEO.

SPEAKER_00 4:34

Uh yes, right. We do talk a lot about GEO. Me and Aaron Newton from Thanks. He's the co-founder, chief data officer. Him and I have been trading notes on AI for about a year and a half. And we talk about a lot of things. We talk about restaurants adoption, we talk about why they're adopting it, we talk about how they can adopt it. We talk about use case from big restaurants using AI, little restaurants using AI. And one of the more interesting topics we talk about is how we get our companies to adopt AI. Because at the end of the day, like that's still a struggle. Thanks has done a really good job getting their team in it. We've had like a very different approach on the chali side. And so we go over a lot of those different things on the episodes.

SPEAKER_01 5:08

And it really is interesting because everyone thinks, like, oh, you're a tech company, which means everyone at your company knows how to use AI and they're all using Claude Code to code stuff up. But there's still a lot of training because as we look at ovation, for example, we have a really long tenure of people. People like staying at ovation. As a result, and by the way, everyone's really, really busy at ovation, right? And so there's not like we don't just have two days a week that people can dedicate to learning about AI. And so we have the same struggles that a lot of restaurants have, which is you're so busy working on stuff that it's hard to really like think about stuff. And so, what do you do to help your team really set aside and dedicate time to learn about AI?

SPEAKER_00 5:55

Every interaction is an opportunity to use a, you know, Aaron, you know, I or him and I talk about like, what does it mean for your company to be like AR first? Or like, how do you know like you're either far enough along, you've reached a whatever milestone? So his theory is that if until every single person starts every single task with clawed code, you're not, you know, an AI first company. And so every interaction that you have can help get you there. Whether you're looking at a marketing website, whether you're looking at a customer situation, whether you're trying to build like your knowledge base, it's really trying to make sure that you are constantly reinforcing the examples on when you can use it and then actually doing it with them. Tons of pairing. I pair with everybody at our company to get them in there. We do screen shares where you literally just watch if someone's new to it, I'll screen share it just so they can watch me prompt, just so they can see how I'm phrasing them. And then they can ask questions when they see tool calls, and then they'll be like, well, how'd you get it to talk to Salesforce? Like, how'd you do that? Like, I want to do that. And then you you go over kind of you get them authorized and get the MCP set up. And so it's more just like taking every single opportunity you can to push the ball forward. Some people do hackathons, some people do training days, some people do dedicated days for it. I think there's a lot of different ways to get to that place. And every company, whether it's a restaurant, a tech company, an HVAC company, or whatever, are all trying to figure out how their businesses kind of go on that journey. And we talk a lot about that on the show.

SPEAKER_01 7:18

I think that's so powerful, that code pairing, because one of the things that as I was learning AI, and I'm I mean, we're all constantly learning AI, but literally sitting down with people and just having them, hey, open up your laptop and like share your screen and just show me what you're doing. That's how I was able to learn because at some point you need to take AI from this, oh, this is like a really cool Google that's wrong 30% of the time, to like what would you do if you had 10 people working for you? So, how would your mind look at a task differently if you had 10 people that were there behind you? And and I the reason I say 10 as opposed to like a hundred or a thousand, which is what it really is, is because it at least gets you thinking, what things do I not need to do? What things is it possible to have AI do? Now, where have you run into some issues with AI? Where have you found like, hey, this is hard to here's a task that AI just might not make sense for.

Turning Ovation Surveys Into Auto Fixes

SPEAKER_00 8:22

So it's funny. I used to have those thoughts, and then I realized that someone every single time has figured it out. So I kind of compare this like, you know, like the bigger boat analogy, like there's always a bigger boat. Yeah, no matter how big, uh like I don't have a boat, but no matter how big your boat is, there's always someone with a bigger boat in this harbor or the next harbor. Like there's always, there's only one person with the biggest boat. And in AI, it's like the same. There's there's someone is using it differently and better than you, no matter how well you're using it. Aaron and I literally just talked about we have like 15 autonomous go-to-market agents at Chali. And he was like, that is so cool. But then he has this amazing reporting application that gathers all the different reports, everybody's have their run, makes data models more efficient, then surfaces it to people, and then also services it to customers. This amazing thing called Sherlock, and I'm sitting there like, that is so cool. I tried, I couldn't do that. Like I ran into this issue and that issue, and he was able to figure out. But at the same time, he was like, Well, I don't know how you get these automizations to actually do the work, right, and do it well and consistently in how you do the checks. And so you could talk to anybody and you'll find them doing a use case where they're doing it better than you, they figured out something. So I've really yet to come into it. I mean, obviously, like AI isn't washing dishes, it's not plating, it's not, it's not doing those things. But from a technical perspective, I think it's just a matter of imagination, bandwidth, and just an infinite amount of curiosity for it to accomplish, you know, the amazing things that it can do.

SPEAKER_01 9:57

And one of the things I find to be really interesting is you're one of the only partners I know of that's really using ovation data to help your business. So it's not even, and that comes down to like the curiosity and the creativity that you're talking about.

SPEAKER_00 10:15

Yeah. So for those who don't know, we we we have a good partnership with ovation where they are basically like embedded into our product and into our online ordering product so that even like we predominantly work with independent operators, one to 10 locations. And so we can actually directly integrate all those surveys, have them go out, have all the responses show up in in our platform so that you kind of have this one place to work with everybody, which has been an awesome partnership. Thank you, Zach. Thank you, and the team. It's been really cool to see that come together. But one of the things that we realized we could do a few months ago is that the survey data that these diners are filling out, it's not always about the food or about the staff or about the cleanliness. Sometimes it's about the application, sometimes it's about the website. Sometimes it's about the restaurant was actually closed, but an order went through, which would cite this could be a technology issue. And so what we ended up having to do is every day we look at all of our review responses across, you know, we've got a few over a thousand restaurants with this now, and we comb through and filter them and look for ones that could be either a configuration issue or maybe there's a bug. And then it goes through, creates us, then it creates a support case for them automatically. And then it even tries to then help the support case and say, hey, I looked into this configuration and saw this as an issue. Either we fix it or we can tell the restaurant to fix it, uh, or this might be a bug. And now the product team can kind of take it over and then go refine it. And so it's one of the use cases where we've actually been able to use the ovation data that we have to make our product better, which has been a really cool use case and something I imagine your customers, if they're not already doing, will be asking you to do so.

SPEAKER_01 11:52

Yeah, because I mean we analyze and we show them, hey, if there's ever a tech issue or an ordering issue, we surface those to them. And that's been awesome because we've seen people where they have uh not with Chowley, but there was an issue with one of our partners where they were not putting modifiers onto the online orders. And so, and and this was a sandwich company.

SPEAKER_00 12:16

So they're just getting two pieces of bread.

SPEAKER_01 12:17

Yeah, well, well, they were like ordering the sandwich and then saying, like, oh, but I don't want sauce on it. Right. Well, they don't want sauce, wasn't showing up. And so they were getting a lot of complaints about their food for online orders, but they realized that it was a tech issue, and so they were able to go in there, talk to their vendor, get that fixed. But it's amazing that now flip that script, and if you're using Chowley, now Chowley is just automatically going in there, seeing, oh, there might be a tech issue, we're looking into it, and we patched a fix before it even becomes a serious issue.

SPEAKER_00 12:52

In the month of March, we remediated 32 issues for our customers without the customer ever knowing that the issue existed. Because their diners basically told us.

SPEAKER_01 13:04

And that's at the end of the day, there's two things that every restaurant is trying to do increase profits and improve the guest experience. Right. And when you're able to fix these issues before you see a trend with them, before it becomes like, hey, 30 people have had this issue, but uh now with Charlie, it's like one person had the issue and it got fixed. It's like that is the power of AI because you can't hire 50 people to go and read every single piece of review, pull out that feedback, create those tickets, and like historically that was the cost of that kind of service.

SPEAKER_00 13:41

And what it ends up being almost like of the 32 issues that we fixed, 30 of them were someone went into basically like toast point of sale, another point of sale, and then changed the hours and didn't reflect those in other places. So we can go fix that for you, which is what we ended up doing, more getting making sure that we had the right hours. And so it's really cool because you can't, especially like some of these point of sale systems, there's four different places you can put in hours, you have menu hours, you have locations hours, so you end up with all these permutations. So trying to do this programmatically is really difficult, right? Because we have 60 different point of sale integrations, so you multiply this out and all of a sudden you have it's like a Coke freestyle machine. There's 1.2 million different combinations that you can check and that you can do. And so by AB, you know, this is a nice, one of those very boring use cases where AI helps make the product better, the experience better, and ultimately benefits the customer, which in my mind is always the end goal with these types of things.

SPEAKER_01 14:36

So, restaurant owner, operator listening right now, what advice do you have for them about their like, Sterling? I feel so far behind in AI. Like, where do I get started? Besides listening to your podcast, AI restaurants, not AI.

SPEAKER_00 14:50

Right. Everybody feels behind, and everybody is behind. No one is ahead. And the second you think you're ahead, I will go find someone uh who will make you feel better. A bigger boat. There's always a bigger boat. And for getting started, look, the chat interfaces are great, but the big hump to get over is to stop thinking of them as a chat bot or a better version of Googling something and start thinking of them as tools that can do tasks. And the best way to do that is to try to find the simplest task that you understand and have it do it. And that task could just be scraping something from the internet once a week and sending you a message. It could be grabbing the weather for the day and just putting that data somewhere. You don't have to vibe code humongous applications, you don't have to try to build these giant MCPs or skills. There's a lot of things out of the box. But just once you start to see it, and this has happened to every single person, including myself, once you see it perform a task, it just opens your world. You have that, like, you have that oh shit moment where you're like, oh my God, I could also do this and this and this. It's better than how we were doing it before. This is gonna make, I'm gonna save time, I'm gonna have a better experience, customers are gonna be happier, we're gonna be more profitable. Like your brain starts spinning. Every person that I've worked with has ends up having that moment. For me, it was opening a Jira ticket. Like, I know that sounds like crazy, but like I literally was able to just describe an issue in normal natural language, and I was able to perfectly format it, do research, and then open up a Jira ticket that had great acceptance criteria. You know, it was a better ticket than our humans could do in any sort amount of time. That was that moment for me. But I just think anyone can have that moment. So trying to figure out what that task is and then getting it done, that's how you get over the hump. And I think that's how you get the most use out of it. And any restaurant operator or owner can do that today.

SPEAKER_01 16:43

Love that. I think that's exactly the point. It's like you don't need to like, if you want to go run a marathon, you don't need to go buy shoes and an outfit, just like put on what you have, put on some shoes, and go jog around the block. And then you're like, oh, okay, I could jog. And then like you start to get into it, and there's a lot of levels of what that means, but just start jogging. And I think that I love that. Just start with the smallest task you could think of. And if you're not sure what that is, go on and have it scrape your Google reviews once a week and just send you an update of here's what people have said about you this last week, and have it send you a Slack message. Like that is a great first project to just get your feet wet. Anyway, but there's lots of them. And if you don't know what to do, get on to Claude and say, Hey, I'm trying to do my first project. Here's my role, here's what I do.

Who Deserves An Ovation And Closing

SPEAKER_00 17:38

What should I have an interview? You talk about the interview all the time. Ask me 10 questions and about what I do, and then you make a suggestion about what we can build together. It's a great strategy. Sterling, who deserves an ovation?

SPEAKER_01 17:50

Who is someone that we should be following?

SPEAKER_00 17:53

Oh man, there are so there are so many people in space. I mean, I think any restaurant independent operator or any restaurant IT team or marketing person that has gone to a boot camp, that has gone and gotten a certification, that spent four hours watching YouTube videos and building a little application and showing their team. Anyone who has taken the red pill, accepted that AI is going to make them better, and they don't necessarily know how, but they're just gonna go do it. Every single one of them deserves innovation because they're the ones that are gonna help push this industry forward and help get rid of that moniker that restaurants are slow to adopt tech because they're not going to be this time because of those people. Amen. Sterling, how do people find and follow you? Um, very active on LinkedIn. That's basically the only social media I'm active on. So do lots of posts, share lots of things in the pod, things that we're learning. Chally.com, if you want to learn more about Charlie, and we've got tons of things on our platform and lots of AI in there as well. But those are usually the best places to get a hold of us and to learn more. And the podcast again? AI for restaurants.ai.

SPEAKER_01 19:05

There you go. Well, sterling for helping us remember that the eye in AI does require a lot less intelligence than it used to. Today's ovation goes to you. Thank you for joining us on Givenovation. Thanks, Zach. Thanks for joining us today. If you like this episode, leave us a review on Apple Podcasts or your favorite place to listen. We're all about feedback here. Again, this episode was sponsored by Ovation, a two-question estimate-based actionable get feedback platform built for multi-unit restaurants. If you'd like to learn how we can help you measure and create a better guest experience, visit us at ovage.