Chris Baggott, Brian Howenstein | ClusterTruck: The Tech Behind a $1 Trillion Industry

Media Thumbnail
  • 0.5
  • 1
  • 1.25
  • 1.5
  • 1.75
  • 2
This is a podcast episode titled, Chris Baggott, Brian Howenstein | ClusterTruck: The Tech Behind a $1 Trillion Industry. The summary for this episode is: <p>We talk to Chris Baggott, CEO and co-founder of ClusterTruck along with COO, Brian Howenstein. ClusterTruck is disrupting the growing food delivery industry by putting the wellbeing of their drivers first. An early pioneer in ghost kitchens, ClusterTruck is positioned as a leader in the projected $1 trillion industry. In this episode, we discussed the motivation behind founding ClusterTruck, how their kitchen operation differs from other delivery services, and what&apos;s on the horizon. </p>

Roger Shuman (01:13):
Well, I am with Chris Baggott, the CEO and co-founder of ClusterTruck. Chris, thank you so much for allowing us into your building and we got to go into the one of the restaurants. So if you follow TechPoint and the work that we do, and I know you're very aware of TechPoint, um, this is a little different, right? This kind of, this kind of technology company is a little different than what we're, what we're used to looking at. So tell me how ClusterTruck is a technology company?
Chris Baggott (01:44):
You know, we started off to solve a technology problem, which is aligning, preparing food and the timing of preparing food with the delivery. Where is the driver? When will they arrive to the kitchen? When should I cook the food? Uh, where is the customer and how can we maximize this process using machine learning and algorithms, um, to do that because a model didn't exist, we literally had to build the prototype kitchens to kind of make the software work. It only worked if we controlled the entire stack, if you will. Okay.
Roger Shuman (02:21):
So ClusterTruck is a ghost kitchen, right? I mean, you're comfortable with that term.
Chris Baggott (02:27):
Yes and -ish.
Roger Shuman (02:28):
Yeah. Okay. well, that, that might be interesting to talk about as well, but ghost kitchens, the growth has been phenomenal, right? The past few years, you might say you got lucky in terms of when, when you started your company, pandemic hits and ghost kitchen growth is going through the roof. I've read one thing that says that one report that says that growth kitchen revenue could reach a trillion dollars a year by 2030. Right?
Chris Baggott (02:55):
Roger Shuman (02:55):
So, um, you kind of got ahead of the curve on that. What is, what are your plans to grow ClusterTruck for the next few years?
Chris Baggott (03:06):
Sure. Well, we kind of have two paths we're taking, um, but one is the technology itself. So when we started and we started working on software in 2015, we didn't open a kitchen until oh 2016. Literally this week will be our sixth anniversary of our first kitchen, but now there's an entire ghost kitchen industry. So now there is a lot more opportunity for us to, to promote and license our software to other ghost kitchens without us having to physically own and operate restaurants. Right. And then the second area that we're looking hard at and we're actually going down the path of is franchising. So the entire ClusterTruck system, which includes not only the software, but also the food, but independently, there could be ghost kitchens that don't serve our orange chicken... Josh, you know?
Roger Shuman (03:59):
Yeah, yeah.
Chris Baggott (04:00):
Sorry, inside joke. But yeah, so, you know, there'll be a complete ClusterTruck model that can be a franchise and then freeing our software to go out and target all kinds of people who may be interested in managing their own delivery for ghost kitchens.
Roger Shuman (04:17):
So in essence, the system that you built 2015, because of the expansive growth that's taken place in ghost kitchens, you're now able to pick that up and drop that into other, other systems as well for other people to use.
Chris Baggott (04:29):
Exactly. Yeah. It just didn't exist. We were the first ghost kitchen on earth, I think. Yeah. So it, um, you know, now the market is finally and it's not there yet. Like nobody is doing anything close, you know, to the kind of volumes we're doing most ghost kitchens that you read about do 10 or 15 orders a day. You know, we're gonna do 800 orders a day in Indy.
Roger Shuman (04:49):
Chris Baggott (04:50):
And even our suburban kitchens will do well over a hundred.
Roger Shuman (04:53):
Chris Baggott (04:53):
Which, you know, I mean our worst performing kitchen is still the busiest ghost kitchen on earth or the fifth or sixth, cause they're all ours. But, um, but that's the whole idea of the vertical integration. And, and it all comes down to the actual software of managing the drivers. The other systems are all completely dependent on third parties and that's proven it doesn't work. Yeah. But that's the only game in town. So yep. That, that gets very exciting to entrepreneurs.
Roger Shuman (05:19):
You know, one of the things, as we look around it looks like a kitchen, so a little familiar, but it's a ghost kitchen.
Brian Howenstein (05:26):
Roger Shuman (05:26):
I've been in kitchens before. It's not quite as noisy as other kitchens that I've been in. So I mean, ghost kitchen doesn't mean it's quiet. Right? So tell me a little bit about what's going on here and what's different than maybe somewhere else?
Brian Howenstein (05:38):
Yeah, absolutely. So the biggest thing you're gonna see different is that our software is gonna control a lot of the processing here. So traditionally when you're in a restaurant, you'll have expeditors, it'll be controlling the whole process. It'll be telling, um, you know, different stages on the line when to fire different items when to, when to cook it, when things should be done. Here we control that all with software and we have to do that in order to make that sync with what's going on with the kitchen, what's happening with the drivers, what's happening with the orders that are coming in. We need all that to tie together. We need all that to integrate. We need to do some planning, some swapping around some managing in order to do that. It all has to happen to the software. So it all happens with these screens and we're able to take over a lot of those processes here with technology.
Roger Shuman (06:16):
So how much does that software really dictate everything that's going on here today, where people are, what's being prepared?
Brian Howenstein (06:23):
A lot of it. A lot of it. So software pretty much is basically the quarterback of the kitchen. So it's gonna tell things when to fire, when not to fire, when to hold off. So, um, right in the middle of it.
Roger Shuman (06:38):
So like I'm a user of ClusterTruck, so I can kind of see when, when my meal's being, being prepared and like you're even indicating to drivers. Right. So they know when they're supposed to show up to pick up an order?
Brian Howenstein (06:48):
Yep. Yeah. So as a customer ClusterTruck and looking at our, looking at our wait-times, looking at the website, you have a view right into our kitchen. So that's, that's all day know that's being pumped out in real-time. Same thing with our couriers, we're managing our relationship with our couriers and our drivers all the same way. So we know what's happening in our kitchen. We know what's happening with orders coming in. We know what happens, order being delivered and all that works together in order to make ClusterTruck possible.
Roger Shuman (07:12):
So, you know, I've seen UberEats, I've seen GrubHub, everybody else. What what's different about your drivers compared to other drivers? I've heard, I've read that your drivers make a pretty good living.
Brian Howenstein (07:25):
Roger Shuman (07:25):
Can you tell me a little bit more about that, that process and how that works? How compares to GrubHub and everyone else?
Brian Howenstein (07:31):
Yeah. So when we designed the ClusterTruck system, we decided to put drivers right in the center of it. We try to make them a...they are our core constituents, so if our drivers did not make a sustainable profitable living, then this whole system wouldn't work. So one thing we discovered is that if you look at a third-party delivery driver, they're gonna get maybe one or two jobs an hour, but that's not enough for them to actually compensate for their time. So we've turned out, we need to just solve that problem and get them more jobs per hours. So at ClusterTruck, we get them four to six jobs an hour versus one to two. And that's really the key to make this whole system work is we keep their utilization very high, keep them working, and that helps them. And that helps us make, make all the economics work.
Roger Shuman (08:12):
How do they engage? So, I mean, you don't just have 20 drivers that are working for ClusterTruck, right. They have, they have the opportunity to engage with your, with your software and figure out if there's work for them that day. Right?
Brian Howenstein (08:23):
Yeah. So that's, what's great about our system is that there's no scheduling, it's purely on demand. So we also make sure we don't oversaturate our courier pool. Cause we wanna make sure that the couriers who are in our loop, that they're making enough money. So if one of the things that, you know, we will... If DoorDash has a thousand orders coming on, you know, downtown here during lunchtime, it's gonna take them 800 drivers to deliver those orders. But here at ClusterTruck, we do all our deliveries with a max of about 30 drivers here at our downtown kitchen. So we wanna make sure that we don't oversaturate that pool. We keep them highly engaged and uh, and highly utilized so that the economics end up working out best for everyone. So a courier comes on in the morning, they just say, hey, I wanna work in the app. And as we have demand, we'll bring them on one at a time. Um, you know, as demand presents itself,
Roger Shuman (09:11):
You know, other than like meeting you and Chris really don't see anyone else that I know that that works for ClusterTruck. Right? So the people that I see that I know are drivers.
Brian Howenstein (09:21):
Yeah, absolutely.
Roger Shuman (09:22):
So to some degree, they're your interface, they're your public, right?
Brian Howenstein (09:25):
It's funny, it's, you know, we're a restaurant where you'll never meet, you know, an employee of ClusterTruck, um, you know the courier is the person who you're... they're our front of house. They're the person you're gonna see and you're gonna interact with most. And that's why it's, it's, it's really awesome. The way our courier system has ended up that, um, you know, with them being very happy and very engaged and keeping them at the forefront of our business, it is really valuable for us, obviously as a business that the person that we want to keep the person happy. Who's the person who our customers interacting with, you know, on a day in and day business.
Roger Shuman (09:58):
Alright. So, Chris, for those who aren't familiar with your career, I'd love to kind of maybe back up a little bit and talk about where you've been. I think most people know that you were one of the founders of ExactTarget. That was a pretty successful outcome. And then from there you went and you did Compendium, had another successful outcome there. So, you know, of course, if you look at all the, all the success you've had with marketing software, it makes perfect sense for you to jump into the food business. Right?
Chris Baggott (10:26):
Well, yeah. Yeah, totally. I think one of the things with, um, you know, with me and like my trick is, is a frustration with the problem. You know, I got involved in the food delivery space because I happened to see GrubHub go public, um, you know, watching Jim Kramer in the morning and interviewing the CEO. And he starts talking about small businesses and we bring them this incremental volume. You know, I just started thinking about the problem, as well, you know. Wait, I never give away my customer data and that's these small businesses are sometimes sucker for these kind of things. Incremental volume, you know, for a small business usually means it's like extra business, it's gonna be lower friction. And having been in small business prior to ExactTarget, I was a dry cleaner. Right, you know, and, and so I understood like people coming in and trying me sell these marketing plans and, you know, I knew how valuable customer data was, um, from my background.
Chris Baggott (11:25):
So that was the first thing. Secondly, you know, I have the Mug in Greenfield, we were starting to take online orders and I could see the friction, it caused a lot of stress. So when I saw him talking about this incremental volume, you know, I kind of said, that's, that's a lie and it's not gonna work. And the other idea that there are just so many moving parts, and, you know, and there are even more moving parts now, right? And you need software to make delivery work with your other software, you know, so you've got delivery software, integrated software, restaurant software, a separate marketing software. And just the whole thing is a mess. Um, you know, and I, you know, I thought of it like FedEx, you know, those of us old enough to remember before FedEx, if you were mailing something, shipping something it's five to seven days.
Chris Baggott (12:16):
It's in the ether somewhere. You can't track it. You don't know what's happening. It's really expensive. And it goes through a bunch of middlemen. Most packages before FedEx were delivered in incremental volume, in the belly of a TWA plane going to Kansas city. And he said, look, I'll get it to you tomorrow. And I'll get it to you at 10 o'clock in the morning tomorrow. But his audacity was, I've gotta own the airplane. And in our case, we had to own the kitchen. We had to own the production facility. To actually make that work. You have to control everything.
Roger Shuman (12:47):
Yeah. To some degree. I think if you look at what a lot of companies are doing today, they're doing the opposite, right? I mean, they want to own as little as possible. But with ClusterTruck, you want to own the entire process from the time that you're creating the food until you're actually delivering it curbside to a customer.
Chris Baggott (13:04):
Right. I mean, the big change that's happening right now is this word incremental, right. Versus disruptive, incremental was Sears. Right. Sears had everything thing, right? They sold everything. They had warehouses and catalogs and, you know, they were shipping houses and plows in the 1800s out west. Along comes the internet and it was like this incremental add-on right. It didn't become a core piece of their business. It was an add-on and everything at food delivery is still considered an add-on. They don't consider it as its own space. Meanwhile, as you said, this is a trillion dollar business, right. It's like, this is almost as big as the entire restaurant business, and everyone's still treating it like it's this incremental stepchild to the real restaurant. What's interesting about the industry today is that restaurants are full. Everyone says the pandemic and that's actually not exactly true, but when restaurants were empty delivery coincidentally grew. But restaurants are full and delivery's still growing, right? So who are we taking share from? We're not taking share from Mike Cunningham restaurants. You can't get in them. But delivery's still growing. So, you know, you're really taking share from people cooking their own food. So I think smart people are starting to recognize that delivery is its own category. It's not an incremental category that I have a few extra hours on a stove. I can cook a couple more grilled cheese sandwiches. This is an actual real business.
Roger Shuman (14:32):
Now you've described yourself as a "one trick pony with a really good a trick." Right, it's all about applying technology to hard problems, or is there more to it? I mean, when you, when you, you admitted that you were watching a newscast, learning about GrubHub. And you realize that there's, I mean, you, based on the experience that you've had with a couple of pretty successful companies, that there was something that you could apply to that, was it that simple or was it a lot more to that more than that?
Chris Baggott (15:02):
I'm sitting in a room full of engineers, so I don't wanna say it was that simple , but, you know, I always threatening to get a tattoo saying "how hard would it be?" Uh, but that is the thing for me is just, I get frustrated. You know, I break UIs. I, you know, and things like that, that, that just don't seem right. Are probably not right. And, and so how would you solve that? And, uh, you know, I'm fortunate to have super, super talented folks around me that can help me solve that.
Roger Shuman (15:32):
You you've noted too. You mentioned the Mug, one of your restaurants. You've also got Tyner Pond farm?
Chris Baggott (15:41):
Roger Shuman (15:41):
So you've definitely, you had ventured into food already, before you decided to go with ClusterTruck, no,
Chris Baggott (15:48):
That modicum of experience, you know, wasn't much, but it was enough to say, you know, coupled with, again, my small business experience with dry cleaners, you know, and seeing these people, you could just see the future. You could say, you're gonna take my data and you're gonna sell it to McDonald's. Right? And when I go online to search for hamburger, you're gonna offer my customer a competing hamburger, because they're gonna pay more. And that's of course, exactly what's happened. Right? Absolutely. These companies are all completely built about big brands and all the small companies that started them are left by the wayside.
Roger Shuman (16:23):
But to a degree you've also created a brand too, right? With ClusterTruck?
Chris Baggott (16:26):
Again, that's, you know, we are, we're at least transparent that we compete with restaurants yeah. To a point for delivery. But like I said, Mike Cunningham is a partner and just collaborator and ClusterTruck, because we do not compete with them. If you want to go out with your friends after work, or you wanna take your significant other and go have dinner, you know, you're gonna do that. Right? But you know, when you're sitting on your couch, streaming Killing Eve, it's seven o'clock at night, you know, and you want something brought to you. That's our space.
Roger Shuman (16:58):
So Brian we'll talk a little bit about menu, right? So you've been at this for what, six or seven years now. And so you've had the ability to kind of track what sells, what doesn't sell. Um, but well, first off, how much does that affect what you've put on the menu, what you take off of the menu?
Brian Howenstein (17:15):
Yeah. So data is a huge part of ClusterTruck, and that's one of the really awesome parts about being this vertically integrated restaurant is that we have data from top to bottom from, you know, a traditional restaurant, you know, well, they know that they have a customer come in, they don't know who that customer is. Well at ClusterTruck, we know who everybody is, you know you are a customer of ours. You know, you interact with the app, we know, the things you like, and we can make recommendations based on the ordering history. And we can see, you know, which items are popular. Which ones don't sell. And then we can see, you know, really cool things like return-rates. So we know if certain, if somebody has a certain item for their very first visit, you know, there may be a 50% chance that they come back, but we know if they have this item for their first visit, maybe there's an 80% chance that they come back. So we can do really advanced analytics to know, you know, what are the items that we should push towards you? What are the items that may need to cycle on and off the menu? You know, what items do we need to tweak, but data is what makes all that possible. And it's a really key advantage to ClusterTruck.
Roger Shuman (18:09):
So you've benefited from that six years or so. Right? But you had to start somewhere. So six years ago you're sitting in a room and you're trying to figure out what are we gonna put on a menu. So how did that decision, how did those decisions get made? And like let's even narrow in, on like something you're popular for, that I think you're way ahead of the curve on and that's tots, right? How did tater tots get on to the menu and why are they so popular now? What did you know about tater tots that we didn't know six years ago?
Brian Howenstein (18:40):
You know, it's funny, I'm not sure what we knew or not. It's, beyond the data we have, we also have an really incredible culinary team. So, you know, our executive chef, Tim Macintosh, you know, him in combination with, you know, we have some awesome advisors in the Cunningham Restaurant Group who have helped us, you know, with that initial menu. And Tim built out some awesome recipes. That, that all this came from, you know, you get an email, you see from chef Tim or chef James, or, you know, all of our, of our awesome chefs here at here in Indianapolis, you know, they built out that initial one. And, you know, at that point, there are years of industry experience to say, you know, these things are awesome. These things that people are gonna love. And so, you know, let's start there and then we'll see what the data says.
Roger Shuman (19:19):
So how much has it changed from the early days to now?
Brian Howenstein (19:23):
It's gone through phases. So, you know, there, we we've got some phases where we, we had the initial menu, you know, some of that stuff, it was really great. And then we, you know, we tried some things, we learned what was good, what was not. We brought some old favorites back, you know, there's some things that's even sold really great in the old days that we're still trying to bring back. So there's a lot of the balance between, you know, knowing the data and knowing the reorder rates, um, you know, how does that work in our kitchen? What's really interesting here in this kitchen is we have all these content to come off of a single make-line. So it's not like we have little individual restaurants stacked up in our kitchen. So we're able to do that with a lot of cross-utilization ingredients. So, you know, not only does the data go into that, but understanding how we can best run our kitchen, you know, knowing that we have these ingredients in the kitchen, what are the different items we can make with it? So there's a lot of management goes into that. A lot, a lot of chef's expertise. A lot of data. And it's a really cool way to kind of combine those two worlds that haven't had a lot of cross colonization in the past.
Roger Shuman (20:19):
So that data has to be pretty strong to say that you're gonna bring a new menu item on if it's gonna mean a disruption to the way your kitchen is set up right now. Right.
Brian Howenstein (20:28):
Exactly. So, yeah, we're, we're typically not gonna bring on a new menu item. If it's got a unique ingredient that's only gonna be used on one item. You know, we look at, if we're gonna bring something in, you know, what are four or five different items that we could put on a menu and be able to make sure that's really well utilized and the same thing for taking an item off. You know, we have some really interesting data that says, you well, a certain item may only sell a certain amount. But by having that item, it unlocks a-whole-nother group of people being able to order. So there, you know, the veto-vote, you know... I wanna make sure you always have vegetarian vegan things, that there's something for everyone here. And even though it may not be the top item on our product mix, it's really important. So we to see all that data, see how things interrelate and make sure we're making the right decision with our menu.
Roger Shuman (21:11):
Alright. So let's talk about beyond Indianapolis. So we've got Indianapolis, we've got Kansas City. We've got Columbus, Ohio. And you've got a great portion of Indianapolis as well. Have you found that in certain areas, like for instance, are the, are there things on the menu in Kansas city that aren't on the menu in Indianapolis? Things that are unique?
Brian Howenstein (21:31):
Yeah. So it's 95% the same. So beyond some regional specials that we may do. You know, just some, some unique things. It's almost identical. What's really fascinating to see is that our P-Mix, our product mix is almost identical between the kitchens too. So, you know, we've had a lot of theories or hypotheses that certain cities have different,, tastes or whatever, but you know what? You still see tots at the top of the menu. You still see the lazy breakfast burrito. You see the buffalo chicken wrap. Those things always come up to the top. So it's really fascinating to see just how consistent it is across markets.
Roger Shuman (22:07):
Alright. So let's talk a little bit about the future of ClusterTruck. So since establishing yourself here in 2015, you basically were hold up and probably in a room with a bunch of engineers came up with the software, opened your first kitchen in 2016,
Chris Baggott (22:22):
Right. Literally six years ago to this week. So Tomorrow, next day.
Roger Shuman (22:26):
Yeah. And so now there are how many kitchens in the Indianapolis area?
Chris Baggott (22:29):
So we have, seven total about to build our eighth. We have five here and one in Kansas city and one in Columbus, Ohio.
Roger Shuman (22:35):
Yeah. That's so that's what I wanted to talk about. So why Kansas city? Why Columbus, Ohio? How did those come about?
Chris Baggott (22:43):
Cause I'm not very smart. I didn't know a lot about the restaurant business. So, you know, when we went out, you know, Indy downtown was such a wild success that we thought we better run to other cities that look like Indy. And what we didn't recognize in part of the success with the Indy kitchen was, you know, that we're all here. Like every single one of us will tell our friends to order. And, you know, I people know me I can, you know, there's an ExactTarget alumni channel that I could go onto and say, order from ClusterTruck and a hundred people will. But nobody in Denver, Colorado really cares about Chris Baggott is or any of us. And what we didn't realize that the key to the restaurant business is really about saturation and saturating a market. So, you know, we go out to these cities and they kind of struggled, but to answer your question, we pick cities that look like Indy, Columbus, Kansas City, Minneapolis, Denver, Cleveland, to some extent, but we could not build the brand fast enough to make the restaurants make money.
Chris Baggott (23:45):
And that's a big thing that's informing our future is the software has always worked, but the economics of the restaurant haven't necessarily always worked. And then we realize we are in two different businesses here. And, and it's very hard to be a master of either. We know we're a master of the software business, cause even a failing Denver was still delivering in 21 minutes and four jobs per hour for the drivers. And you know, that's the biggest key to us. Like our software treats the driver as if he's the core constituency or she is the core constituency. You know, this machine will err on the side of the driver over the customer almost every time because we know if it's good for the driver, it's going to be good for the customer. But some days you'll see, you know, up on this board, see it's coming up here in a minute, but you know, you'll see delivery times that might be in the 60, 70 minutes.
Chris Baggott (24:39):
But we can also see kind of the orders. We call it in the cloud. So a little bit into the future. And we say, oh, that like a very short bubble. If I bring on more drivers, I can make that time go down, but it's a temporary blip. And then I have too many drivers on. And if I have too many drivers on for afternoon volume, like we're in now, no everyone's gonna make less money. Like we think about diluting the driver pool. So if we're have to make a trade between diluting the driver pool or having the customer have an hour long delivery, we're gonna choose the hour long delivery. Um, the customer knows that even at an hour, because we're timing the driver and the cooking of the food that my food is never gonna be older than seven minutes. Right. If you have an hour long delivery on a third party, odds are your food is 55 minutes old. By the time it gets to you, um, but in our case, the customer knows we're not cooking the food until exactly the right time to get it to you in under seven minutes from cook-time.
Roger Shuman (25:36):
I love your transparency. You know, that you're willing to admit that yeah, we, we took this step and maybe it didn't work out cause you've been there. You're a proven serial-entrepreneur. Um, what else have you learned along along the way? So I mean, you noted that like, hey, it wasn't as easy to go into places like Denver or wherever else, but what else have you learned along the way that could be helpful?
Chris Baggott (25:56):
Well, I think that saturation thing was a big thing. I mean, we spent a lot of investors money on building facilities and trying to market into them and make them work. And, you know, again, the challenge of having this minuscule delivery zone of six or seven minutes, you know, 90% of our marketing dollars are being heard by people who can't buy the product. Right. So, and that's where I got very lucky and stumbled across. Somebody introduced me to Steve Ellis, the founder of Chipotle. And basically I, Chris, who we had 16 Chipotle's in Denver before we ever thought about leaving the Denver Boulder Metro area. You know, you need to close these things and go home and saturate your market. And a part of it also was the way we were cooking food, you know, Indy was an instant success, but the kitchen we built literally requires about 3 million a year to break even. Now we do three times that now, but, um, but that's not gonna work in the suburbs. So we had to do a lot of figuring out how to cook for in a very, very different way and that's brand new for us, right. Me then, you know, from a technology standpoint. But also, you know, a challenge.
Roger Shuman (27:11):
Yeah, you mentioned a suburb, so you've had some pretty cool partnerships come along the way as well. Right. So you've partnered with Kroger. Tell me a little bit about that.
Chris Baggott (27:19):
That's great example of kind of a mistake, right. You know, the hope was like, so we're struggling trying to build boxes, right? These units and they're expensive and time-consuming and permits. And it's like, oh man, if only there is an easy way, like who's got a lot of underutilized kitchens? Well, grocery stores have a lot of underutilized kitchens, right? There's a deli in every grocery store, there's a hood, there's plenty of electricity. There's three compartment sinks. All the things you have to learn to be in a restaurant business. And Kroger was very open to the idea, you know. Cole called them and it took a couple months, finally found somebody and they were all super receptive. And we went down this path, where, you know, we're gonna try this and opened a couple of kitchens.
Chris Baggott (28:01):
And, we built in a Max and Irma's just completely separate. And they were trying to see if a brand of Kroger delivery kitchen would work. Um, you know, he landed on that doesn't work, you know, but you know, they were great partners in the respect that we're gonna try a bunch of things and see what works and what doesn't work. And at the end of the day, you know, they're in the grocery store experience game and we're in the ghost kitchen, like we don't want a public facade. We don't want be in a busy area, you know? So, like a Fisher's for example, where it's great, very successful, but, you know, we offer pickup there cause that's what Kroger wants. And you know, nobody really wants pickup, but all the other companies that can't deliver profitably are trying to convince you to come and get it right.
Chris Baggott (28:49):
But if you come and get it, the food is going to be old, but that's now on you. You know, I had someone that I talked to two or three months ago and he had left a review about this soggy Nashville Hot Chicken sandwich. So I looked him up and the food sat until he got it. It sat 18 minutes. Had he taken delivery? He would've had that food in six minutes from the time it was cooked. So it's sat18 minutes. So I call him, I'm like, hey, I'm just trying to figure out, you know, why you didn't take delivery and tell me about this experience. And really nice. And he's like, well, yeah. So I picked it up, but then I was gonna get something in the store. So how long did that take? Fifteen minutes. Great. Then they checked out how long it take? Five minutes then? And I had to walk to my car. Yeah. How long that take? Five minutes. Then I drove home eight minutes. Then I, you know, had to unload my car. Of course my groceries and put 'em away. Then I ate the sandwich. He's like, holy cow, this sandwich was now old. Right. And you know, that's, that's the, the breakthrough for us is, is delivery is always gonna be better than pickup, but Chipotle's out there trying to convince everybody to use the "Chipot-lane" because they can't afford to deliver and that's the breakthrough of our software is we make delivery profitable.
Roger Shuman (29:55):
So if you go back really to your start and to food with, with Mug, with Tyner Ponds, right? I mean, that's always been about quality. Right? And so with ClusterTruck, the focus really is on quality, but at the same time, profitability on top of quality?
Chris Baggott (30:13):
Exactly. I mean, there's David Chang, the famous chef. And David Chang, you know, had this article when we were first starting out a few years ago. And he was talking about this for Philly cheesesteak that, you know, painstakingly worked on this recipe to make this Philly cheesesteak taste good after 45 minutes. And we're just like, dude, solve the 45 minute problem. And you can serve any Philly cheesesteak you want. I mean, you see our packaging. Like we're not, everything is completely normal because we've solved the time problem. You know, it's Tom Hanks and Castaway. Remember that opening scene in Russia and "never commit the sin on turning your back on time." But you know, I mean, we're counting seconds all the way through the process, shaving it here, shaving it here, shaving it here. But especially... you know, I do have a tattoo that says "don't ship maybes" and a maybe is anything that sits for two minutes.
Chris Baggott (31:00):
Yeah. You know, so don't send out food that you're not a hundred percent confident in. And you see that in our reviews, if you look at third-party delivery reviews, they're all one star, you look at our reviews and every one of our kitchens, we're five stars and people are blown away because there is no expectation of quality. Like that's not the problem that you're hiring delivery to do for you. You just want the calories, you know, but when you get ClusterTruck, you're just not going back to DoorDash. Right. Because it's good. It's delivered by friendly, engaged people because we have the best job in the gig economy. We get the best gig economy people, and you probably saw them at the kitchen. Yeah. Nice, nice people. Everyone knows everyone's name because they're not a bunch of randoms that have a two-week lifespan. Brian probably told you, you know, something like 75% of our drivers started driving the week the kitchen where they work opened, like they never leave. And we have drivers that are six-years-old here at Indy, because it's the best gig. And if you want this kind of flexibility, you know, and that's, again, that's kind of our breakthrough.
Roger Shuman (32:06):
So I got a chance, as you mentioned to, to tour one of your kitchens today and, and talked to Brian, we talked a little bit about data and how important data is to what's going on in the kitchen today and how it's informed, how you've gotten to where you are today. But what about the future? So I love talking to technology companies because I know that they are collecting data and not data to infringe on someone's privacy, but they're collecting this data to inform what their next step is going to be. So you've been at this for six years now, as you've said, what have you collected? That's been able, what kind of data have you collected? That's been able to inform where you're going to go next.
Chris Baggott (32:46):
Well, you know, what I love about machine learning is it's like a child, right? And so we're sitting here with like this eight-year-old, like we've got like six years in it. You know, it can like ride a bike and it can do its homework and, you know, maybe give itself a bath. By the time any of our competitors come along to be an eight-year-old, we're gonna be going on dates and frat parties. It's gonna be at a completely different level of maturity. And so that gets us really excited. You know, the data is, is just super informative. We have this super broad menu, you know, and we have this recommendation engine that works really, really well about what you will like next based on all our customers and everything they've ever ordered and everything you've ever ordered.
Chris Baggott (33:33):
And, you know, it's just, the insights are incredible. You know, if you order a chipotle shrimp taco, are you a Mexican food eater? Are you a savory food eater? Are you a seafood eater? And that's gonna inform what, you know, what we offer to you as what we think you might like next. Okay. And when you have a broad menu, like us helping the customers sort through that, you know, I mean, I'm all in favor of, of course I've been in the data business my whole life, but, you know, I will give you every scrap of data to make my life easier and better. And that's really kind of how we approach this. We don't use our data that much for marketing. We use it a lot to make the system better. What kinds of foods do we get complaints on when we launched, we launched with a um... and we made all of this in-house, but a tofu kimchi vegetarian burrito, and it was one of the top five sellers. But then we looked in the data after a few weeks and we realized that nobody ever reordered it. And if it was the first ClusterTruck item, you had, you are never coming back. So then it's like, okay, what item should we serve a first time customer, right? To make sure that we get a high reorder rate, right? Like you are gonna like this food. So what are our most highest reordered items for a first time customer is an important piece of data. Secondly, obviously kill the kimchi tofu burrito.
Roger Shuman (34:54):
Chris Baggott (34:55):
But that kind of thing, you know, just, you know, all across the system, what do we get the most complaints about? What do we, you know, pad Thai is, uh, it's very polarizing, but it's our highest reorder rated food. But also one of our most, you know... "When I was in college in 1975, I was wandering through the streets of Bangkok and you know, this is not that, you know." Okay. Yeah. It's at that. You're right. But it's pretty good.
Roger Shuman (35:25):
So as we look at the future for ClusterTruck, we've talked about some pretty significant things that are coming down the pike. One of them is the software. So ClusterTruck, as we have known it for the last six years has been the software and the restaurant. But now you're talking about being able to pick up that software and allow other people to use it? Talk to me more about that, how that decision came to be and what it's gonna look like?
Chris Baggott (35:49):
Well, yeah, thank you. It, you know, you can't go to any kind of conference in our space, which is restaurants and not hear everyone bemoaning the entire third-party delivery relationship. It's bad for the drivers and they can't make enough money. So they have to be subsidized by the third-parties. So now the third-parties can't make enough money. The fees are too high on the consumer and the quality's not good enough, you know? And the fees are too high on their restaurant, right? So there's the, like, nobody's happy with this. And yet you've got this massively growing business and people are trying to solve the problems kind of on the periphery of what we do and really believing that the third party is the only way to do that last mile delivery. And, you know, we know we have an alternative, we have a six-year-old beta test here with a ClusterTruck we've delivered literally millions of orders.
Chris Baggott (36:41):
And average is seven minute delivery time from cook to in your hands. We average four jobs an hour. We average an under 10% delivery cost; 10% is the line item you would use if you were scooping food at Chipotle, like that's what front of house cost. So we're delivering at a lower cost than you can serve in a restaurant. That's a huge breakthrough. So, you know, lots of folks are starting to reach out to us like what are you doing and how are you doing this? And as you said before, this ghost kitchen is just, it's massively growing. And we're the only ones on the planet that I know of that can deliver profitably for free. Um, and you know, we, for fun order from Five Guys the other day, and I think two cheeseburgers totaled something like $47. Well, I mean, again, $8 DoorDash service fee, right? Not counting whatever. The delivery's fees only $2.99 or whatever, but then there's this $8 service fee. And you, you dig into that and it's like, well, tax, oh. And, uh, helping us keep the software running, but DoorDash can't make money. Right? I mean, their stock has been like this. And the only lever they have to pull to make money is fees. And the market has pretty much reached tolerance on fees. So we just feel like there's a spectacular opportunity for us.
Roger Shuman (38:04):
What's the timeframe on that launch?
Chris Baggott (38:06):
You know, we have some unnamed customers lined up and a lot of 'em have to build facilities, but, you know, we will be ready to go in the fall for sure. I mean, we will be live in the fall with customers,
Roger Shuman (38:21):
Chris, thanks so much for your time today and opening up not only your office, but your kitchen to us to get a glimpse into what ClusterTruck is. And we're excited to see what's next.
Chris Baggott (38:31):
Good. Thank you. Appreciate.


We talk to Chris Baggott, CEO and co-founder of ClusterTruck along with COO, Brian Howenstein. ClusterTruck is disrupting the growing food delivery industry by putting the wellbeing of their drivers first. An early pioneer in ghost kitchens, ClusterTruck is positioned as a leader in the projected $1 trillion industry. In this episode, we discussed the motivation behind founding ClusterTruck, how their kitchen operation differs from other delivery services, and what's on the horizon.