Unlocking Restaurant Delivery Profits with Loop AI CEO Anan

In this episode of the Restaurant Technology Guys Podcast, host Jeremy welcomes Anan, a long-time listener and an AI expert with significant experience in restaurant tech and operations. The discussion dives deep into the challenges and solutions associated with delivery in the restaurant industry, focusing on Loop AI—a platform designed to help restaurants understand and improve their delivery profitability. Anan shares his journey from AI research to working at Uber and starting his own restaurants, and eventually creating Loop AI to address the financial and operational struggles of delivery services. The conversation covers the intricacies of delivery, taxation, profitability, and marketing spend, emphasizing the importance of data and technology in making informed business decisions for delivery channels.

00:00 Introduction and Welcome
00:13 Guest Introduction: Anan's Journey
01:34 The Rise of Delivery in Restaurants
02:26 Challenges in Delivery Profitability
03:16 Loop AI: Revolutionizing Restaurant Delivery
06:02 Understanding Financial Complexities
11:34 Marketing and Consumer Behavior
17:02 Taxation and Reconciliation
38:10 Engaging with Loop AI
41:00 Conclusion and Call to Action

Transcript

0:02

This is the Restaurant Technology Guys podcast. Helping you run your restaurant better.

Jeremy: 0:10

back to the restaurant technology guys podcast. I thank everyone out there for joining us. As I say, each and every time you guys listen, it is an honor to come on the air and talk to you guys today. We are talking about delivery and all it entails. And so I'm going to introduce our guest here for just a second and let him share a little bit about how he got into restaurant tech. And so I'm sure I'm going to screw this up, even though I just asked him how to say his name. it is add non. No, I screwed it up. Why don't you introduce yourself real quick to our listeners? And then we can talk a little bit about what you get to do and how you got into restaurant tech.

Anand Tumuluru: 0:43

No worries, Jeremy. It's a hard name. It's Anan. yeah, it's Anan. it's a pleasure to be on the show, Jeremy. I'm a long time listener. and, a quick background about myself. I started my career, as an AI researcher. Worked on a previous generation of, machine translation or think of it as a previous generation of chat. and, later worked, build at Flipkart building accounting receivables, over there and later, transport management capabilities and also on flipkart's Cloud. and most recently I was at Uber, through the pandemic. Saw the growth of delivery from inside the marketplace. concurrently, I'm also a restauranteur, have a, have a couple of restaurant locations. it's a passion project, but, just a lot of us, from the world of restaurants. It's a world, where once you are in, you're locked in and you want to keep going. So it's a small side project that we, that I take seriously and draw a lot of, a lot of, my personal, Pleasure and, indulgence from

Jeremy: 1:43

I love that. and, I know that today really the topic of conversation is all wrapped around delivery and some of its intricacies and how, both operationally and financially and all of those kind of things. And so your most recent project and why you're here is to talk about loop AI. So why don't you give everybody an intro to what is loop AI and where did it come from? and, I'm excited actually to talk about it because I think there's a lot of people that are struggling with these problems and likely they don't know that there's solutions out there like what you and your team have been able to put together.

Anand Tumuluru: 2:13

absolutely showed me. So quick context is that as a restaurant or the total amount of software spend, that we made a zero. I know what it means to, as a restaurant or to basically look for every single penny, and make sure that the operation is profitable. But at the same time, it's really hard to understand. where the cash flow is and how do you plug the holes? And how do you maximize your revenue? coming from that world and going through the pandemic and sign the seeing the growth of, delivery over, over such a short span. one of the big, one of the big questions that sort of all restaurants, were struggling with was how do we make delivery profitable? And, right around the time of pandemic, when we would start, when we're starting to get out there, it was okay, socially okay to be out there, a lot of us were helping our favorite restauranteurs, our favorite community shops, and mom and pops out and, just like all of us, we were out there talking to some of our favorite restaurants and. And literally all of them just said, Hey, delivery is our primary source of revenue. And we were struggling to, and they were struggling to understand how to, how to make it work. So that's sort of, where loop, started. We basically worked with very small mom and pops restaurants, trying to understand what the big problems they had with delivery work. And surprisingly. with a ton of our partners and friends today, order aggregation was not really a problem, right? So they were able to get orders from Dodo. I should be scrub hub. They were able to inject it into their, into the T. O. S. Or, maybe they had one tablet, to rule them all. And that world was working fine. The problem was. They weren't really sure, how profitable delivery was and, whether they were making money. 30 percent sounded like a lot of commissions and they were struggling to understand what they can do to get it right. And, as data scientists and engineers, one of the first things that we did was, Hey, this is the time for. an extremely sophisticated menu, right? So let's use data to figure out what the optimal menu is, what the layout is, let's optimize images. And maybe there is 20 cents of pricing that we can change and did a whole ton of, whole lot of minor and major changes to their menus and to their, to the delivery applications. And at the end of, at the end of the month, we would see these, Graphs go up in the DoorDash, Ubers like, the revenue would raise. but when we go back to the operators and we tell them, Hey, have you seen all of this additional money come into your bank account? their response was, what money? What are you talking about? What did you do? And. We were shocked. We were surprised and shocked because in the world of Uber, which is a company that's driven by extremely large data sets and large scale experimentation, if you made a change that caused a 1% increase in any metric, it's a companywide celebration. Like it's a massive event. in these restaurants, we were making like five, 10, 20 percent difference to their revenue and to their orders. And based on what they were telling us, they couldn't see any difference to their cash flows, to their sort of profit and loss. And that was so stunning to us because, we just couldn't even reason with them in terms of how much they're making. And, and that sounded like a much bigger problem. Like, how are you operating a whole line of business? Without even knowing how much money you were walking away at the end of the month with and the restaurant Owners basically said hey, why don't you go talk to our accountants? you know we go talk to the accountants and they're like You know feel free to look at the quickbooks and we followed that rabbit hole and at the end of the day What we realized was that restaurant accounting is a mess it's very hard to understand your revenue by channel your profitability most of them just operate accounting just so that they can file taxes

Jeremy: 6:12

Mhm.

Anand Tumuluru: 6:12

sales tax liability thing. It's payroll taxes, stuff like that. there isn't like serious attribution to a specific channel and amidst this extremely broken world of restaurant finances, you have a completely new business line, which is DeliBee.

Jeremy: 6:26

Mhm.

Anand Tumuluru: 6:27

it's a whole new financial and operating model. You have a 30 percent cut in terms of commissions. But you also have a significant, addition in revenue, right? and is it incremental? Is it not? How much cost do you amortize between food versus operations? how would you think of, increasing prices on these apps? If you increase too much, nobody's going to come to your store. If you don't increase too much, you're probably just giving away free food. marketing is really effective. how much do you want to market? There's just so many questions there and you cannot answer those questions without a clear Understanding of your finances. You cannot make these decisions without data and if you especially fast forward this entire evolution of delivery assuming delivery continues to grow

Jeremy: 7:15

Mhm.

Anand Tumuluru: 7:16

And this revenue channel the operations and finance the complexity with operations and finances continues to grow It's an obvious idea in retrospect You 10 years down the line, you cannot imagine, you cannot visualize a world where these decisions are being made without

Jeremy: 7:32

Without understanding them.

Anand Tumuluru: 7:34

without understanding the data. so for us, what we are building is fundamentally a financial foundation, and a bunch of operational levers on top of them so that restaurants can not only understand the finances by this delivery channel, but execute the operational levers so that they can make it profitable. And especially over the next decade. as delivery grows, as it cements itself as a more, stronger channel with, with all kinds of restaurants, certainly with fast casual and the more, take away specific formats, like off premise formats, but definitely with all restaurants, we think, it's a no brainer that, a software like loop AI, and, a data, first, orientation towards delivery. it's just going to be an obvious thing that all, every brand must have to do.

Jeremy: 8:17

Yeah. And so there's so many different trains of thought that I have, after the description. So first and foremost, you're 100 percent right. I have an eight year old. I remember, my wife got a DoorDash gift card, a digital gift card eight, nine years ago when, right after she was born. And quite frankly, I was in the space and I had no idea. And so the rapid adoption of DoorDash, UberEats, GrubHub, just all of the different TSPs that have been out there has been One of the most rapid changes to restaurants prior to any of these DSPs being out there, it was, you could only get pizza for delivery. And if you were in certain geos, maybe Chinese food, maybe Indian food, but you had to be in a major city, you couldn't likely get it in the suburbs unless you wanted pizza hut or dominoes. Now, I would say close to 90 percent of restaurants have some form of delivery. You talked a little bit about kind of aggregation. We've got multiple aggregators that have been on the show. So from that perspective, I think everybody's figured out how to get it from those companies into the point of sale. what they haven't necessarily done, and I would love to talk a little bit about this and how you guys see this as is taxation and pricing. And out of stocks and all of that, those are problems. Those are problems that a lot of people are dealing with. And so understanding did the consumer pay to uber and what did uber pay the restaurant? Have you guys figured that piece out? Because I, I feel like your description of the problem from the last five years, you could have been sitting in 50 of my customer meetings because so many customers are like, Yes, I have to turn on delivery, but I don't know how profitable it is. And I know if I don't have it, I'm going to lose this customer. But I know if I do have it, I don't know how profitable it is. And is it incremental? Is it not incremental? So I want to tease out each of these, but I'd love to talk a little bit about even identifying the order and how did it come through and what does it look like, I got, a pizza on this, order and I paid 18 for it to Uber Eats. How much of it's coming through? Have you guys figured that piece out? I guess let's start there. How much of it was taxed? How much it was the product.

Anand Tumuluru: 10:09

Absolutely. Jeremy. So one of the core pieces that you get with loop AI, is you basically look at an income statement for your third party delivery with your gross profit, assume that a hundred percent of that revenue is incremental. What's your gross profit, right? against that. So breaking down the different fee components, understanding your marketing spend. Maybe there is the problem of chargebacks. Maybe there is a significant amount of unfulfilled sales and in the name of canceled and missed orders. you touched on a very important topic in terms of taxes. how much taxes does the restaurant? Oh, versus what was the marketplace facilitator? component to that, we basically understand that at an order level

Jeremy: 10:54

Okay.

Anand Tumuluru: 10:55

at a payout level and basically make sure that the restaurant is very clear about what their gross profit is, not just at an aggregate, but by channel, by Doordash, by Uber Eats, by, even within channels by dash bars, customers versus non dash bars. and even within that, how much of that was driven by marketing? What's the true incremental ROAS on marketing? and so on and so forth. So by different spent years of commissions or the money that they're investing into these channels. How much are they making? And you can also go down all the way down to an order level and understand what you actually made from that order net, all of these sort of deductions.

Jeremy: 11:40

I love that. just for our listeners that might not understand what row as is. I do, but, I think it's, I think it's one of those things that helping them understand you've mentioned marketing a few times, and this is one of the things that the Uber Eats, and DoorDash drivers talk about is we're going to get you in front of so many more eyeballs And you're going to spend money to get us there. So if you can help our listeners to understand what that looks like or what that even means, because, again, at times I get people going, you have this guest on and I had no idea what they were talking about. Can you define that for me? So would you mind doing that for our listeners?

Anand Tumuluru: 12:11

Absolutely. So from, from a very, from a very first principled sort of investment and written on investment, terminology, if you basically spend, let's say 30 percent off your revenue, you're expected to get, let's say, a hundred orders from them, according to the market basis. If you actually spend 40 percent by, upping your spend on marketing, let's say you invest 10 percent more, you potentially get 200 orders or 150 orders. So if you actually spend a little more than your commission. Then your base rate, you can actually make a lot more money, in terms of a lot more incremental orders just because you're capturing customers eyeballs or helping them convert once they're at your store because they look at a promotion they would otherwise have not checked out. But now they want to get that promotion and they check out. So the million dollar question that, truly a million dollar question in the sense of brand spending millions of dollars and in marketing is. Hey, my commission base rate is 25 percent. Could I spend three percent more five percent more or ten percent more? In order for me to maximize that revenue. so can I get more, a lot more orders and at what percentage of incremental spend at what more, let's say maybe at 5 percent you can actually get 50 more orders, but at 10 percent you just get like 60.

Jeremy: 13:38

It's not. It's really that measurement of your ad spend. What is the return on ad spend? I think is what a row as stands for. And so it's if I spend this, what do I expect to get back? If I spend X, I get, I get this. If I spend Y, I get. this next amount. And so understanding what that looks like and what did it drive. So I love that you guys are doing that. Cause so few people even understand that they spray and pray, throw a bunch of money at it and go, I don't know, was it good? Was it not good? So talk me through that.

Anand Tumuluru: 14:07

yeah. So the, again, the real world application of this is very straightforward. the mathematics of it and the science of it. can, can get abstracted away, but fundamentally, let's say you're a brand, I'm just going to use starboard as an example, just because we were on the call with them before. And my, it's my favorite brand in the Bay area. and it's, phenomenal, garden bird salad. I'd recommend everybody try. They have a 4. 8, 4. 9 rating on delivery. They were one of the earliest delivery, first brands. They adopted delivery. They do really well. All of the finances and operations as it relates to how the food flows out off premise. super low error rates, phenomenal brand visibility. Everybody knows about starboard there, their brand. it doesn't need to spend more on, let's say, ads, right? Because everybody knows about Starboard. there isn't, or even if you don't know about Starboard, if you come to Doordash and Starboard is within your serviceable area, you already know that it's present. it's around the area. Contrast that with, maybe even a McDonald's, right? That's completely new to the area, right? So the customers in that delivery radius didn't even know about this specific brand being around. So it makes a lot of sense for McDonald's to spend on ads just to know, just for the customers to know that McDonald's just showed up. in that area. at the end of the day, I think the nuances around the way that you run these ads or the way that you measure these, they're obviously different. They're different between Google and Facebook, as they're different with marketplaces, too. But I think the principles remain the same, which is Hey, if you already have a lot of visibility ads is not the way to go And in fact you want to know where there is headroom for you to get A lot more consumers to be aware of your presence in the first place and maybe you want to run ads there similarly with promotions Maybe you want, a set of customers to try out your brand and you have that, the good news is that with the third party platforms, you have so much demand in terms of consumers. You have that ability to pick and choose these levers, at a store level, at an, by audience type, you can basically deploy these ads. For the right store for the right audience type to basically make up for whatever the store needs to be doing in your vision for that brand and that's basically where loop. ai comes through, we are helping we are helping these brands get that nuanced understanding of hey, where am I lacking? How do I spend this money? How do I make sure i'm not giving away free food while I deploy the spend? and at the end of the day, make sure that You Their third party delivery presence is ideal and is according to their brand's vision of how they need to be viewed by customers.

Jeremy: 17:00

I love those, those thoughts. And again, I think they're all very needed. And I think they're because so many people got shotgunned into doing delivery because of the pandemic, or, they never really thought through these things. one of the other things that you talked about is kind of taxation. Taxation is a pain in the butt because my understanding, and I guess, correct me if I'm wrong, is that, even if your restaurant is in one zip code and one tax zone, they're Uber eats because they're such a big company or whomever it might be that's delivering actually has to charge the tax rate of where you're delivering it to not necessarily where the restaurant is. If I'm brick and mortar and I walk into the restaurant, I go order food. It's whatever the tax rate is at that physical geography, my understanding, and I guess, correct me if I'm wrong, is the taxation for that order is actually where it's getting delivered to based on the current tax laws, which may be different than the tax from where I ordered the food from, which creates a discrepancy. With your data. Is that a fair assessment and figuring out the data between those two is often a challenge. And now a word from one of our sponsors. Every restaurant operator understands the chaos of a Restaurant kitchen during the meal rush restaurant technologies, oil, total oil management solutions, and end to end automated oil management system that delivers filters, monitors, and recycles your cooking oil, taking the dirtiest jobs out of your kitchen and letting your employees focus on more important tasks. Control the kitchen chaos with restaurant technologies and make your kitchen safer. No upfront costs to learn more, check out rti- inc. com or call 888 796 4997.

Anand Tumuluru: 18:34

No, that's a totally fair assessment, Jeremy. And the good news is that, again, just like with marketing, third party marketplaces have a lot of tools, have a lot of data around this. So what they do for the restaurant, barring a few exceptions, there is always exceptions where Michigan passes a new law and, they're a couple of months behind, barring sort of those exceptions. They do a phenomenal job of putting estimating the tax liability, both the taxes that they've withheld versus what you need to be paying, to your state authorities very well at an order level, at a transaction level or at a payout level. The problem is that it's very hard to actually integrate all of that data in, in the context of your point of sale. Which has its own taxes configured and your accounting software, which again has its own rules and logic that's applied to it. The second thing is that there's a whole set of decisions that a brand needs to make, in terms of, pricing, right? So if they're increasing prices, so what is it getting taxed on? Or let's say they spend on marketing. they need to make sure that they're paying the taxes for the right amount. And that basically. Listening to the marketplaces and taking that help in terms of sizing their liability correctly. a lot of them actually end up paying double taxes, right? They basically end up, just to be considerate, just to be safe, what they do is, Hey, I made 100 on third party delivery. I just need to pay 8%. I'm just going to pay that entire 8%. Turns out 5 percent of that was already paid by the marketplace. You're just supposed to pay three percent. so what loop. ai is helping do is not just understanding the tax liabilities well and building the order and audit trail for you to understand what, what led to a certain calculation of tax liability. We are actually automating reconciliation and filing those sort of tax entries in your QuickBooks or in your Restaurant 365 directly. So we help actually create those journal entries and we don't give you another Excel sheet or another dashboard for you to figure out and navigate. We actually go and close your books for you, so that you don't have to deal with the complexity of trying to break these nuances down.

Jeremy: 20:50

I, I appreciate that. And again, I, I've got a lead for you. After we get done with the call, I got a customer that I was just on the phone with the other day and he's can you help me fix my tax thing? So we can talk about that offline. But, another line of thought I had that you talked about, I think it's, Yeah. Until you get into the data and you start to look at it is each of these delivery service providers do things differently. They give you data differently. They give you your reporting differently. They charge you differently. They may have different rates, different times of day, different rates. Talk to me a little bit about, for those that just think, oh, all delivery service providers are created equal, or they're at a brand right now that only is supporting DoorDash, but they're considering Uber Eats and Grubhub. They all do it differently. And because they all do it differently, reconciling them, you have to build systems or, engage with something like loop AI to understand what those reconciliations are. So can you walk me through that, that each one of them are their own tech that's been created differently with its own set of rules, its own set of outputs, its own set of dashboards, its own set of those kinds of things. But I think all too often, if I haven't dug into it, or they say, that's my accountant's problem, it's not my problem. I just need to offer Uber Eats, but those levels of complexity that exist because every one of them is different.

Anand Tumuluru: 22:03

great question, Chadmi. And I think. first things first, I think the answer to these questions, I'm always afraid to indirectly imply that my old employer, Uber or Doordash, I'm not doing a good enough job, off of doing these reports. And I just want to preface this entire conversation by saying, I think we, we should, we should have the understanding that this entire industry was created like three years ago. Everybody's figuring everything out, including the market cases, right? So they're figuring out their own sort of profitability. They're figuring out what the right team structures are, what the right reporting standards are. And by and far. The way that the big two, Doordash and Uber Eats, do all of these transactions, payout reporting, and helping restaurants understand sort of the breakdowns, is, miles ahead of, everybody else. So they have, to their credit, invested quite a bit in simplifying finances and operations for restaurants. there is no doubt about that. Except, it's, It has a long way to go, right? there is still a lot of work to do. The key problem here, Fundamentally Jeremy, is that from Dotash's standpoint, they are building their own ideal standard and, it's perfect and it's beautiful, except a restaurant is looking at 15 such statements. They're looking at their POS. They're looking at EasyGator. They're looking at Grubhub. And then they're also looking at Lunchbox. And then they're looking at, Olo, Olo and Thanks. And at the end of the day, they, the amount of just spread that they have with respect to understanding what was the actual payment that they got from any of these sort of providers is a complex maze. And we went from a world of Not even having cloud based point of sale to having 15 different sort of, digital ordering channels on steroids, just pumping, all of these orders into the restaurant. So we just live in a world where it is complex and overwhelming for the restaurant. Now, in terms of the, in terms of the complexity that exists with understanding payouts, everybody's doing their own thing. First of all, there isn't like a standard or there isn't like a rule set that says, This is how you are, how marketplaces are supposed to report, or these are the fees that you need to expect. Atoms have been made at different cities and, different, different states and cities where they try to say, Hey, here's how you can charge it. But. That only led to an explosion of more than items. at the end of the, at the end of the payout. So I think everybody's trying to figure out what's the right way to, what's the right way to present it, present these transactions and payouts. Now, one of the things that I would like to point out, Jeremy, is that in the world of third party delivery. The complexity is actually a lot more than what you would have in store. for your regular POS transaction. So for POS transaction, all you have is you just go buy the food and you basically have, let's say a 2 percent deduction on your credit card, right? But in the world of third party delivery, you have marketing, right? Which is super important. you want the visibility, you want promotions. You potentially have, refunds, which are also bundled in, for what it's worth. It's significantly larger than what you would have in store, fundamentally because there's a lot more operational complexity for taking food out. But at the same time, it's actually simpler than, handling chargebacks is simpler than what you would have with your POS, because with POS It's a lot more complex with POS, right? And then you have the taxes, marketplace, withholding taxes. And on top of all of this, you basically have your first party, delivery orders, which are fixed fee based, ordering channels. So the complexity with respect to the payouts and transactions, it's warranted, it's necessary. It represents, The complexity of the channel and the way the consumers are actually changing their behavior, right? So it represents the wide array of things that you would do with a regular e commerce store, right? It's no different from what you would do if you were selling let's say an iPhone With your e commerce on an e commerce store or a bag like or Apple so I think there is a lot of parallels to the world of e commerce and There's a lot of complexity that necessitates running your digital delivery channels well, except it's completely new. Each of them is doing it in their own way. And at the end of the day, the fundamental question of, hey, This is all great. Like at the end of the day, what is a gross profit? Like how much am I actually like paying? that question becomes harder and harder to, answer for restaurants without using technology. If you're basically, deploying another person to sit down and pull these reports, or if you are asking your, outsourced accountant to do it, good luck with that. It's just going to take so much time, so much effort, and it's going to be a one time thing. just trying to figure out what these calculations are.

Jeremy: 26:50

and at the end of the day, in most brands, it doesn't even represent 50 percent of their total volume. And so you're now at, 20 percent of your volume is through DSPs, but you've got this complexity of having to deal with this. So without tech, the juice oftentimes isn't worth the squeeze. And which is why I love, I love aggregators, order aggregators. We've had multiples on the show. I love that they allow the orders to get from the web down into their store. So operational complexity, In inside of the four walls is great. And now we've got tools like what you've got that are going to help people reconcile. Am I making money? How am I making money? and really even be able to make business decisions. And so I'd love to take that path because again, Not all deliver service providers are created equal. Not all of them are going to do the things that you might want to deliver on your brand promise to people. And depending upon what you negotiated and how long your term is on your contract, you may be paying more to one of the delivery service providers, but they deliver a higher level of service. And maybe the guests are willing to pay more, but you don't know that unless you have the data to be able to make those decisions. So talk me through what all of that looks like, because I think all too often people, I ha I had a customer as silly as this sounds. I had a customer recently that said, I can charge more on my third party delivery than I do in store. And I looked at them and said, absolutely. You should, because it's a higher value to that customer. Yes. It's the same cheeseburger. Yes. It's the same chicken sandwich, but you're delivering your costs are higher. And, all of it. And so across the board, talk me through how you guys think about that and how the data that you guys serve up gives people the capability to deliver on those promises in different ways that, that they hadn't considered before. Potentially.

Anand Tumuluru: 28:32

Absolutely. Absolutely. So if you, there are a couple of what you might think, think of as ground rules here, Jeremy. So the first one is that the customer that's coming to marketplaces, those marketplaces worked hard to get them right. They have billions of dollars of spent in terms of. Demand generation on Google, on, on social media, their own

Jeremy: 28:57

they're the ones that are at the top of the list. When you search for starboard, They show up door dash might show up before the actual customer's website because they're trying to drive that order through there just to, create a direct correlation of what you're saying. They're putting the ad in Google when you go search or when you go search somewhere, they're putting that at the top of your search results that you're going to door dash thinking that you might be ordering directly from that website. I apologize. I didn't mean to cut you off, but I think it's, I think it's important for people to understand that. Yeah.

Anand Tumuluru: 29:25

and I think Google really, is really going in the right direction there. again, we're all figuring this out. So Google sort of made this recent change where they, where they let the restaurant choose if that Doordash or, Uber Eats store is linked. but a lot of that behavior. consumer behavior, especially the strongest cohorts of consumers with these marketplaces don't even start from Google. They are subscription customers of Doordash. Of Uber Eats, they're opening that app in order to search for food in the first place. So the food search is not going to Yelp or Google. It's actually going directly to the marketplace. very similar to product search on Amazon. There was a time when people used to search on Google. It's Hey, can I buy my new top, best binoculars? Under 100, right? That's what you'd search for on Google. People don't do that anymore. People actually go to Amazon directly and search for it. So that behavioral shift is happening even with food. especially here in the Bay Area where DoDash is super, super strong. People just directly search on DoDash for, best Thai cuisine. Best Thai food nearby. Best Pad Thai nearby. and regardless of whether, whether it is through loyalty, through search, these marketplaces are investing in that consumer and they are basically keeping that consumer information close to their chest. They are keeping all of the consumer's history, all of their, predictions around the customer's behavior in the future. And then, and guess what? They're actually doing a phenomenal job at getting the customers to reorder. a couple of years ago, I

Jeremy: 30:56

push market to me all the time. They're like, Hey, you haven't ordered from this brand in a certain amount of time, I don't have the brands app downloaded, but I have DoorDash downloaded because it's part of my dash pass as part of my chase card. And so I order off a door. this is a real life consumer that's in this space. I know exactly what they're doing, but almost every day I get a push notification saying you haven't ordered from X, Y, Z brand. It doesn't matter the name of the brand. What would it look like if I gave you 10 percent off an order today to drive that behavior? And it now has me thinking about that. And I might not take that offer now, but the next time I go to think about it, it's like, Hey, I haven't had Pad Thai in a while. Maybe I'll go to DoorDash this Pad Thai. So these are real life examples where they're in your customer's inbox. They're in their. apps on their phones or in their email inbox, oftentimes more often than you are to try and drive that behavior. So I apologize. I keep cutting you off, but I like, I think that it's critical for people because all too often restaurant owners, when I sit and listen to them, they don't use these apps because they want to go experience, they got another hospital industry, so they're not the consumer. But they need to understand that the consumers that are out there that are using these apps Are doing these things and it looks different So i'll let you keep going because I think it's critical for them to understand discovery And behavior and them driving that to your brand and what that means for you. Cause you likely wouldn't have gotten that customer without it.

32:22

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Anand Tumuluru: 32:45

And no, please keep adding your insights and thoughts too. I think it's, I think the important thing here is that there is a behavioral shift that's going on with consumers. in the ways that you just described, which is, which is hard to understand, which is hard to internalize or build an intuition around, especially if you're a restauranteur, if you're a restauranteur, you're built to be a person that's extremely hospitable to a person that's in person. You want to give them the best service. You want to give them the best food. You want to make them smile. You want to give them a great experience. You're not necessarily thinking in the world of sort of bits and digits, right? I think it has to be said more number of times to really internalize The consumer behavior shifts that are happening, shifts that are happening. Jeremy, just to your point, just to close that, the funnel, so to speak, with respect to consumer behavior. I think, just a couple of years ago, I think, in the upcoming Food On Demand conference, the two years ago old version of this, somebody mentioned that Dash fast consumer, consumers are ordering on DoDash seven times a month. I wouldn't be surprised if that's eight, nine, or ten now. Which means consumers are ordering on DoorDash two or three times a week. My question is, how long before it's 21 times a week, basically what if it's all the three meals every day, right? So what if they're actually going into apps? What if most of these behavior most of the behavior for customers is like fully digital And maybe it's not 21. How about right? That's 5x thing of this market And by the way, that's the default behavior in a lot of Other, other cities and countries outside and it's going to vary a lot by region It's a growing, it's a growing customer base and we are seeing that growth in marketplaces while the growth rate has slowed down It is still growing very strongly and we are seeing this across brands too that delivery revenue is growing, right? Once a customer comes into the app they can actually place an order sometimes in one click sometimes in two clicks You And they're able to actually request a refund or seek help in a couple, a couple of clicks, they can actually go ahead and. Look at that history of order. So let the app recommend the best meal that they can have in one or two clicks. So for them, for these apps, I think the reality is that consumers are sticking really hard to these apps. They are ordering again and restaurants need to go and meet them where they are a lot of brands Jeremy to your point earlier ask us the question, right? So the so when if I answer your question, hey, how you know What's the profitability is this revenue incrementally fee? If you get an answer to that question, maybe you're hinting towards how about we just run an offer towards our first party app and get all of these consumers out and, acquire them directly on the brand. We have seen that story play out a few times and the success rates have been different across different brands. But the reality is that especially not with pickup orders, but with delivery orders, The apps are so much more convenient, the marketplace apps are so much more convenient that we inevitably see customers go into the brand's app and then come back at a later point of time once we saw offered ease out. And especially the subscription customers that are extremely sticky, right? They keep going back to the third party apps. So it's this behavior. it's just consumer behavior. So the reason I'm giving you the context around the consumer behavior is that the revenue that marketplaces are generating for restaurant in the debate of whether it's incremental or not, it's really incremental. There is just a ton of anecdotal evidence for brands that have tried to take these customers away and have seen those customers go back. Plus, the subscription behavior that's Important for us all to understand and to know that investing in these channels is important. So once you have that, once you recognize that cc data and anecdotes and hear from other people's experiences, the next question is, Hey, how much should I invest here? What's the, how much of my brand should be present on these third party apps? How much of my revenue should I expect? Should it be 15%? Should it be 30%? How much should I invest in a first party channel? And how much should I drive my revenue there? Those are the things we all have to figure out in the next two, three years. Every brand has to figure out. Should I invest, let's say, 100, 000 in an app so that I get at least 10 percent of the customers into a first party ordering experience? Should it be limited to pickups? We see a lot of brands, for instance, Dave's Hot Chicken, one of our favorite brands. They don't do delivery on their app. They just do pickups, right? They don't deal with the delivery experience at all because they know that, third party apps, the way that they offer that convenience, it works, right? It works. That's where customers are going. They're happy with it, but then they have a phenomenal, app for pickups. So all of these decisions in terms of what should my channel mix be, In terms of third party versus first party, pickup versus delivery. How much marketing should I spend? These are decisions that brand brands need to make, in, in the next one, two, three years,

Jeremy: 37:56

I think it's, I think it's ironic cause we'd never put a New York strip on our menu without understanding what my food cost was and what it was a cost to acquire that customer, but we just make these guesses on what the customers are going to be able to bear on third party delivery apps until tools like you guys have. And it's just, It baffles me. And to your point, it's only a two or three year old problem. So I think as more and more data becomes available, as these DSP solution providers end up giving more data back to the restaurants to understand these things, and then there's tools like what you guys have, we'll continue to get better. even the delivery experience now versus what it was two years ago is Phenomenally better. And it's gonna only continue to increase. and so talk me through. What does it look like to engage with loop AI? What? What's the ideal customer? How do they engage with you? How do they learn more about how you can help them to understand the profitability and truly make good science and data based decisions about their delivery service? Partners and how they're going to go into market.

Anand Tumuluru: 38:52

if you basically have a delivery revenue contribution, that's 20 percent or a hundred thousand dollars that's coming through from third party marketplaces, loop, loop AI will be a great fit, for you and fundamentally we help, on onboarding, the brand for us is very straightforward. it takes a few minutes for them to sign up, get loop AI set up. The first thing that we always recommend restaurants do is look at their income statement and look at all of the line items where the fees are getting deducted, where, where they're making money or. Where they're not, and have a strategy, have a plan towards attacking those different line items. And once we set those goals, we see returns or improvement in the profitability as early as one week. And definitely over a span of three months, for instance, with Craveworthy Brands, one of our favorite customers, we've reduced that downtime from 300 minutes a month to 100 minutes. while they were going through a POS integration again, one of those things very hard to know that your stores are not even open for customers to place an order. it's just a hidden problem, we can go solve for that. Another, another example is, Hey, we are mandated to spend. According to our marketplace contract, we should spend a million dollars in marketing. We are worried we are giving away free food. We are worried we are spending that money inefficiently. how can we understand what campaigns are working well for us? And we, deploy the cash in a way where we can actually grow our customer base. another area where, you know, Duke AI can help. And I think the, our favorite user base are the finance teams. CFOs who, who know the pain or, even outsourced, CPAs who know the pain of actually pulling all of these reports, understanding the different formats, keeping up with the reporting format changes and actually, closing their books by creating these adjustments. All of that's gone. once you're on board to loop AI, we basically take care of all of that reconciliation for you. the, we truly understand the back office complexity of. Managing third party delivery and we basically make sure that we touch all bases with respect to the burden of getting this revenue and doing delivery, right? you know for your team

Jeremy: 40:56

thank you for one, for creating the product. Cause it is a problem that everybody that has delivery has this. And so the fact that you guys are at a place that you guys are solving for this is fantastic. and again, I think, as you continue to remind me, it's only a. Four or five year old problem at the most, it's this problem that has been, we all feel like it's been forever. Cause you know, I don't know, COVID created, everything is like in dog years nowadays. at the end of the day, we're doing so much of this and it's so painful. So I'm grateful for tools like yours and others that are out there that are helping solve this problem. And so thank you for sharing. to our listeners, guys, like I said, at the onset, we love having you guys listen to the show, give us some feedback, go check out loop AI. If you haven't already subscribed to the show, whether that be on YouTube or on your favorite podcast player, please do so and make it a great day.

41:43

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