transcript

Speaker 1:
[00:01] Tony Xu is the co-founder and CEO of on-demand delivery giant DoorDash. He's grown the business from a Stanford-side project into America's dominant food delivery platform, and is now pushing into everything from grocery to retail, to autonomous vehicles and financial products for gig workers. Great.

Speaker 2:
[00:15] Great.

Speaker 1:
[00:16] Cheers.

Speaker 2:
[00:16] Cheers.

Speaker 1:
[00:17] Good to see you.

Speaker 2:
[00:17] Good to see you too, John.

Speaker 1:
[00:19] As I think back to that era where you guys got started, what year was DoorDash founded?

Speaker 2:
[00:23] 2013.

Speaker 1:
[00:24] Okay.

Speaker 2:
[00:25] Yeah.

Speaker 1:
[00:25] As I think back to 2013 and those early days, the iPhone and the apps that were made possible by the iPhone was the defining tech trend of the era. Uber and Lyft and ride sharing, Instacart, you guys, all of the magic wand apps that made your iPhone useful for bringing things to you and manipulating the wider world. And loads of people were going after food delivery, and way more than are around now. As you look back on that journey from, again, it was really kicked off by the iPhone, in my opinion. Not that there wasn't food delivery before the iPhone, but that really massively increased the market size. As you think about from then to today, why did you guys win?

Speaker 2:
[01:13] Well, the short answer is we have more customers than other people.

Speaker 1:
[01:17] Sure, but let's not think five ways here.

Speaker 2:
[01:19] Yeah, I mean, I think these are very tough things to study because many things are happening in the same moment. But I'll just talk about it from the perspective of things that I think we got right. When you think about something like restaurant delivery, you actually get judged on multiple dimensions as a service. We get judged on what restaurants we bring you, certainly whether it showed up on time, and the quality and condition you expect, how much did it cost, if we screwed up, what did we do about it. It's not one thing that you have to be good at actually. It's all of the above. Unfortunately or fortunately, this is literally the game that we're playing where customers are judging us on all of these dimensions. I think getting that right better than anyone else, as measured by whether or not people are coming back to the app and using us, using us even when we had no money to market to them or discount offers to them, things like that, I think, was the towel.

Speaker 1:
[02:16] Are you saying it was a very complex, multivariate challenge even from early on, and you guys just embraced that complexity and said, okay, this is going to be super complex to get right, whereas maybe others took a bit more simplistic view?

Speaker 2:
[02:30] I think if I were to become overly reductionist and purely looked at it-

Speaker 1:
[02:34] That's what I like to do.

Speaker 2:
[02:38] From the product perspective, yes, because at the end of the day, any consumer product is judged very simply by its retention and its usage. That's how you know whether you have a differentiated product. I think it's very easy to have differences in opinion about whose app do you like more or whether or not certain apps look similar or different. At the end of the day, though, if our app is performing at a higher retention, much higher retention and frequency of use than others, that's how we know whether or not the things that we say actually are making a difference to customers. And so, getting, I think, all of that right very, very early. And then building the systems to actually instrument that, as well as to repeat that over and again, I think was very, very important in the development of the company.

Speaker 1:
[03:24] Do you think you guys were more focused on retention than others?

Speaker 2:
[03:28] I don't know if we're more focused. I could tell you, though, one of the things that was happening, especially when you see a competitive fight, is you see everybody race towards it. Everybody is going to try to make offers to customers, try to give discounts, try to give coupons, free this, free that. One of the things that we had looking backwards is we actually did not have a large budget. In fact, between 2016, 17, 18, we barely were able to raise a dollar relative to our peers. As a result of that, that made it a constraint. One of the constraints is, okay, you can grow but you cannot spend in order to do it. So in order to do that, you effectively have to actually come up with ideas in a product to actually stand out and make a difference, and have organic growth carry you. And then once we were able to demonstrate to ourselves first that we had a product with higher retention than other people and higher frequency, and then we were able to raise capital, then we actually made the decision to pedal to the metal and actually go and acquire customers because we had an unfair advantage.

Speaker 1:
[04:33] Were you more customer obsessed than others?

Speaker 2:
[04:36] I think it's very difficult to measure us against other people because I didn't really work at those companies. But again, I really just look at the early DoorDash crew and what were the things that we did that were very useful. We all did deliveries, we all did customer support, we all made menus, we all sold restaurants, we all customer service restaurants, we all worked inside restaurants. And I think at the end of the day, I think the term customer obsession can be fairly generic and vague and applied. And it really just goes to show like, well, what actions actually demonstrate that? For us, some of the ones that came to mind, and frankly, the story that actually inspired the value in the first place was, when our backs were against the wall and we had, I think, less than two weeks of cash runway. And we had a terrible night where every single order was late. This was a Stanford football game in 2013 and I had trouble raising the seed round. We made the decision to refund everyone. That cost us over 40% of the bank accounts. So when you have two weeks of runway, 40% of the bank accounts.

Speaker 1:
[05:44] You issued a refund that was 40% of your funds were made?

Speaker 2:
[05:46] Yeah, maybe a little over that. And we baked everyone cookies and deliver them at 5 a.m. before everybody woke up. Look, this is like maybe 100-ish customers or something like this. But I think it's demonstrates that this was a real value. And it's actually my test really, which is like, what are the actions that are naturally occurring? What are the behaviors that are actually occurring inside of an organization? And then how do you actually articulate it versus the inverse, which is you start with maybe some articulation and maybe some of the times it matches and other times it doesn't. And so I've always believed that these cultural norms or behaviors are really 80 percent of what you've done. And I think that's the best way to actually find what they are for your company. And we're the only platform today to take care of dashers when there is these increasing gas prices and making sure that we have their back and that we're actually trying to help them save $1.40 to $1.90 per gallon for dashers. Or in COVID, we were the only company to cut commissions by 50 percent. When we were not yet profitable as a company, that was an expense over $100 million. We then on top of that, spent millions of dollars buying national TV campaigns to tell people to order, whether it's on us or our competitors. Because restaurants have on average 17 days of cash on hand. So, you need to order. This is do or die for them. And so, I can give you many of those examples where, I think at the end of the day, whether the actions first speak, and then you can articulate the actual words and norms and cultural behaviors that the company is trying to speak. That's ultimately, I think, how I think about customer obsession.

Speaker 1:
[07:30] And if I try to draw what these values are, it seems to be a very clear-eyed focus on the best product experience and taking care of dashers. I didn't realize you guys had a time when you had only two weeks of cash in the bank account.

Speaker 2:
[07:47] We had several moments where we ran out of money. So we had that moment, obviously, in the fall of 2013. We had three very difficult years, 2016, 17, and 18, where we had two rounds of financing that were incredibly difficult for us, the Series C and Series D. And COVID was interesting because COVID started actually, again, I think it's easy to forget these things because I think humans, we adjust very quickly. COVID, the first week actually, the business tanked 80 percent. It tanked massively because everything was shut down. And then the next week, everything, all of the dining rooms were closed, but the kitchens were open. And so, boom, we see this massive doubling of the business in a week. So it was a, there are a lot of these, I mean, you've seen this at Strave, obviously, a lot where you have these moments as an entrepreneur where you have very, very low lows. The highs don't feel as high as maybe they get, but that's what you get.

Speaker 1:
[08:55] Yeah. As I think about the funding rounds, you mentioned being hard. One of the investors I know who has consistently had the most steadfast belief about DoorDash is Michael Abramson, who was at Sequoia back in the day. Why was he so convicted? What was it?

Speaker 2:
[09:14] I think you're going to have to have him on the show. To have him, but I think Michael always had a fairly simplistic view of the company, where if three things worked, the business kind of works. It's actually reminded, when I met Michael, actually reminded me a lot of our journey in Y Combinator, because I think in Y Combinator, I think we were just happy to be there, but a lot of people were really racing towards demo day, where the objective function was to raise as much money at the highest possible valuation. For us, actually, the objective function was answering three questions. It was, would consumers pay for this product, pay a premium for delivery? Would merchants actually work with us and pay us commission? And would dashers partner with us for a wage that we could afford? And I think Michael had a very similar set of very simple questions about the company, and I think so long as those dimensions looked right to him, he kept on investing.

Speaker 1:
[10:15] I think he said you have to do the math and work out that the economics of this business do work, and they do, therefore, a more compelling product experience will win.

Speaker 2:
[10:23] Yeah, that he believed that if the unit economics were there, that we could secure enough dashers. And I think his third comment was really that we can continue executing into the market opportunity, that things will work out. Yes. He turned out to be right.

Speaker 1:
[10:42] Thinking more about this ecosystem, food delivery is very popular in the United States. It is even more popular in China. I feel like the experience of just being in a major Chinese city is one of seeing food delivery. You go to a restaurant and there's like moped. You're on the roads and there's just like wild flocks of moped everywhere delivering food. The apartment buildings and the office buildings have dedicated zones to streamline it. Why is food delivery so much bigger in China than it is in the US?

Speaker 2:
[11:14] Yeah, there are a few things. This is one where I'm always on the one hand, so impressed by how far ahead sometimes behavior is in markets like China. And then on the other hand, I have to remind myself that there are differences and why you can't just clone some of these markets. Well, one of the first big differences is the eating out culture in China is very, very high and very, very affordable. Eating out in China is about as affordable as cooking at home.

Speaker 1:
[11:47] And as a result, nobody cooks.

Speaker 2:
[11:48] And as a result, nobody cooks. Exactly. And there are a lot of reasons for this, but we can go super deep on retail history and grocery history in China. But anyways, but that's a huge phenomenon. I think second, because of labor market dynamics, both the availability as well as the cost of labor in the Chinese market, that's allowed a lot of these businesses to make this activity almost as affordable, as if you were to pick up the orders yourself. I think third, is that especially, it's not every city in China, but more and more the Chinese, started really with the Eastern Seaboard cities, where the density just allowed a very easy delivery, kind of set up almost like every city was like New York City. I think in America, we think New York City is very special. It has millions of people. In China, there are many dozens of cities over a million in population, and the population density is even perhaps higher than that of Manhattan. And now, that's actually more to the Western cities too. It's not just the Eastern Seaboard cities. If you actually study this over a time series, whether it's the 80s to the 90s and certainly to today, because of how fast China is able to manufacture things, city plant things, deploy things. I mean, literally, they can build a train station in an entire day. Because they can do things like this, the market potential has really expanded. Even as people moved now from Eastern Seaboard cities to other cities.

Speaker 1:
[13:27] So you're saying a big part of it is lower labor costs mean food delivery is quite inexpensive. Does that affect them?

Speaker 2:
[13:35] The cost of the food, I would start with that, it is a lot lower. Then you have lower labor cost and you also have massive availability of labor.

Speaker 1:
[13:43] Yes.

Speaker 2:
[13:43] And then now you also have rising incomes because of how fast cities are getting developed. It used to be that most of the income for consumer discretionary spend if you studied as a percent of China's GDP was along the eastern seaboard, say take circa the early 2000s even, or even up to the 2010s. But if you looked over the last 15, 20 years, that has now become a lot more uniformly distributed, kind of like the US whereas this is not true in other parts of the world.

Speaker 1:
[14:17] Well, where I was going with this is, does that then predict the behavior of other markets? Where is there also a lot of food delivery in other markets where food is cheap and labor is cheap?

Speaker 2:
[14:26] And whether or not there are a lot of restaurants and people who can afford delivery, sure, but also the production of food. Yes, right, I think one of the things that I've always thought about is restaurants have two very special properties about them, and I do think that more and more they are almost going towards the ends of these two spectrums. Same thing with retail, we can talk about that too. But restaurants on one hand, I think are centers of hospitality, and it's incredible, like the level of attention to service they have. And I think that will never get replaced by AI, that human to human connection. On the other hand, where technology and autonomous technology can make a difference is, actually, restaurants are almost like manufacturing production sites.

Speaker 1:
[15:15] They're a third space and a factory.

Speaker 2:
[15:17] Yes, yes. And so it's no different in retail. You have showrooms and warehouses, right? And so I think in the case of, back to your point around China, China has a lot of restaurants. Over 7 million restaurants versus what we have here in the US, at about a million restaurants in comparison, for example. And so in China, you also have a very deeply capitalistic society in the sense that, wherever there is opportunity, you're going to see lots of people go and fill that. It doesn't have to be a restaurant. It could be a kitchen. It could be coming up with different merchandising. If you're a restaurant, you can sell not just food, you can sell t-shirts, and you can sell hats, and you can sell cookbooks. And I think there's a lot of commercialism also in that industry in a way that is much more advanced than other countries.

Speaker 1:
[16:14] Yeah. Restaurants are very hard businesses, and they're one of the most common businesses that people start, and yet they're incredibly sophisticated even at a small scale.

Speaker 2:
[16:25] Yes, and they are also incredibly sought after. In fact, if you looked at the census data in America now, and this is also true in China, but if you looked in America in the last 60 years, I think there's only a couple of years where the number of restaurants in the current year didn't exceed that in the previous year. And even though they're such difficult businesses, because of our love for food, for socializing, being with each other, and what a meal represents, and how it can connect different people, it continues to grow. In fact, it's the number one type of establishment that malls and a lot of shopping centers want the most of.

Speaker 1:
[17:04] Talk to me about the trends in the restaurant industries these days. If I think about what people talk about, there's dark kitchens, so that was more a few years ago, people were talking about dark kitchens. There's the fact that high-end restaurants can't make any money these days because no one drinks. There's maybe the emergence of new fast casual trends, but also some criticism of the sloppels and everything. But I know that's just what people are, you're in it. So tell me what's actually going on in the restaurant industry.

Speaker 2:
[17:30] One of the most difficult things is how do you actually staff your restaurant? This is the number one challenge, this has always been the number one challenge. And I think there's no easy ways around this really. And I think because the cost of labor only goes in one direction, only goes up, restaurants are increasingly making this choice of on the continuum of service to manufacturing, where do I want to sit on that spectrum? I think that is one very big trend, that more and more restaurants feel like they have to go towards the ends of the spectrum. Whereas before-

Speaker 1:
[18:06] You have a local restaurant, but people are sitting and eating their dinner, and also is fulfilling a few takeout orders. You're saying that's becoming less common.

Speaker 2:
[18:13] Yes, because there's a lot more pressure in order to make sure that everyone deservedly gets paid, what is required to actually work there, especially inside some of these city centers. So, I think that's a perennial trend. I think a second perennial trend, and this is why I think people love restaurants, is the innovation in restaurants is a little bit different than innovation in, say, software, where innovation in restaurants is just like different types of cuisines and food. And so, you're always going to see the next type of restaurant. And I think this is best shown in what I was saying earlier around the number of restaurants. The number of restaurants always grows. That's a perennial trend. That's something that is not changing, even though the types of maybe food is changing, or what's hot, what's not, that's changing. What's not changing is the consumer's appetite for actually these restaurants. I would say number three is restaurants are thinking about increasingly how to scale. And this takes on different forms. So, in the case of some of these large brands, the big QSRs that you've heard of, which represents almost 50 cents on the dollar of restaurant spend in a place like the US, they're thinking about how do I take my economies and scale and just keep going, right? Because I have that as a big advantage. But you also see smaller restaurants who are trying to figure out how do I open up location number two? And it's really difficult. It's actually really, really difficult in a lot of cities, even for the most popular restaurants, the hottest chefs in town, who you'd be shocked at how hard it is for them to raise the capital for location number two, or even get the permits to start construction on location number two. And so, I think that's another perennial trend that you see happening in the restaurant ecosystem. So, those are the ones that I think a lot about, which are what are the things that are not changing, that are incredibly difficult, that if you can solve these big rocks, you can unlock even more value. Now, I kind of like presented a lot of obstacles, but if you actually look at the totality of the data, you would see that the amount spent on restaurants for eating out has increased over the last 75 years every single year. It used to be that in the, you know, these are rough numbers, but in the 1950s when the government was measuring this, we would spend in this country in America maybe 75 to 80 cents on the dollar on groceries versus restaurants. In present day, you know, those numbers are almost reversed where it's, you know, almost 60 cents on the dollar on takeout and 40 cents on grocery. And that number has only kind of gone in these proportions or this direction. So even though it is so difficult to make it as a single restaurant tour, especially when I think about like the days of washing dishes in my mom's restaurant, the totality of the industry continues to remain very strong and they're moving in one direction.

Speaker 1:
[21:28] When you talk about permits, famously a lot of cities do a bad job of, make it hard to open a restaurant. San Francisco people have a lot of complaints. And one of the innovations that you see these days in restaurant culture is the food truck gardens and food truck collections. And I always find those kind of bittersweet, where often you have like really cool new concepts and stuff, but we have societally lost the ability to allow people to open restaurants and therefore we're reduced to a collection of food trucks in a parking lot somewhere. Are permits getting better or worse?

Speaker 2:
[22:01] I think in general, similar to building things, they've gotten largely worse on average. That doesn't mean there aren't cities who are green lighting and making it a lot easier. In fact, if you look at some of the fastest growing cities in the country, they tend to also be the fastest growing cities for restaurants. Not a shock. It's probably not San Francisco.

Speaker 1:
[22:22] Are like Phoenix and Austin, these places doing a good job of permits? Yeah.

Speaker 2:
[22:25] If you look at places in Arizona, like the Tri-City area, Phoenix being one of them, Scottsdale and the Tempe area there, you look at the Tri-City area in Texas near Austin, or you look at what's happening in Dallas and the Dallas-Plano area. There's these pockets in the, actually, in fact, if you look at the country, a lot of this growth is happening in the south of the country. And that's been true for a couple of decades now. And they tend to be correlated, meaning if it's easy for me to build apartment units and to build just construction in general, it tends to be a bit easier to also get the licenses to open up a restaurant.

Speaker 1:
[23:07] That's good. There's some bright spots and it's a nationwide maybe negative trend when it comes to permitting.

Speaker 2:
[23:13] Yeah, look, I think when you're in any business, certainly the restaurant industry or even our line of work, I would argue you kind of have to be an optimist. You kind of have to see the silver lining on the way out of how to get there. But it's a slog. And I do think that one of the responsibilities we now have as a company, as we're a little bit bigger now, is to help on behalf, particularly of these small businesses, to represent them almost as a class. And actually try to even the playing field a bit and make it a bit easier to actually be a small business.

Speaker 1:
[23:48] What do you argue for on behalf of small businesses? Like when you talk to someone in Washington, what are you saying?

Speaker 2:
[23:55] Well, one of the first ones is actually making it easier to actually open up location number two.

Speaker 1:
[24:01] So permitting reform.

Speaker 2:
[24:02] Permitting reform is one of those things that we certainly stand for. Making sure that labor laws are changed, or when they are changed, that they take into account the restaurants. We're talking about one of the largest sectors of job creation here, that is always growing by the way, every single year, which is a rarity. But a truism in every economy to take into account what the restaurateurs have to say. Those are some of the big topics. Again, I look at the things that aren't changing in terms of the difficult challenges of being a restaurateur, and we try to fight on their behalf.

Speaker 1:
[24:46] Where has technology meaningfully changed how restaurants work? Like, a very visible example to people might be in fast casual restaurants, they have managed to change the labor equation, it seems. You might know the actual number is because it's self-serve ordering and pick up at the counter and stuff like that. That's much more common than it was, and so you need fewer people for the same volume of orders, or you can run much more scale, the same number of people. I'm guessing there's supply chain stuff, but it's less visible to us as people who visit restaurants, but you'd know. Just as you think about where tech has made the biggest impact versus 10 or 20 years ago with restaurants, what would be your top three list?

Speaker 2:
[25:27] Yeah. Well, I mean, not to speak our book, but one of the first things that comes to mind is actually something like food delivery. When you look at the economics for a restaurant, rough math for every dollar of food that if you and I bought inside of a restaurant, from the cost structure, you're going to have 30 percent of that in the food and the packaging. You're going to have 30 percent of it in the rent. You're going to have 30 percent of it in the labor, something like that, rough math. And on that dollar, a restaurant can net 10 cents. On a takeaway order, you're still paying for the food and the packaging, but you're largely speaking using the same labor, and you're paying the same rent. And there are some exceptions where some restaurants have become delivery only and things like that. But by and large, on average, you're going to make three to five acts the margin, the incremental margin. I think number two, I think restaurants recognize that they need to build relationships with customers that are not just over the telephone or over in-person visits, where they're relying on their memory. And so I think, but that area is still, I would say, somewhat incomplete, where there are products where you can manage your social media pages and maybe have a database of relationships that you recall. The challenge, however, though, is you don't get to see everything. You don't get to see the full visibility of your online orders, your in-store orders. Another challenge is your staff turns over. The average staff may turn over every other day, not every other week, every other day. And so, I do think that there's still a long road ahead there, in both making that product a lot more robust for restaurateurs to be able to have those relationships. Because back to one of the things we talked about in this conversation about, the importance of retention in a consumer business is so important for a restaurant to build the concept of a regular. Which is a retained customer, right? You and I, I know we travel a lot for work, and so we wouldn't always be great customers for a restaurant. What's more important actually is if they knew that there was a regular that is actually coming, that it should be prioritized. And so, those are the kinds of things that I think, hopefully, we DoorDash can help and actually solve.

Speaker 1:
[27:54] Most restaurants do a bad job of recognizing regulars, where you think about the airlines as an industry. They've made it where it's highly irrational as a frequent traveler to travel not your preferred airline, like they've really created a lot of lock in there. Whereas, as I think about restaurants, there is like the supermass market, punch cards, 10th coffee free stuff. And then there is the like really old school restaurant where the owner might greet you and might comp your dessert or something, but it's very sporadic and very dependent on the owner being there because as you say, when the new waiter or waitress is there, they don't know you. But there's kind of nothing in between systematic and it feels like some kind of way of rewarding regulars is missing.

Speaker 2:
[28:38] Yeah. Well, it's a hard problem. I mean, let me ask you, I mean, what is your favorite food to eat?

Speaker 1:
[28:44] Depends, but at the weekend, we went and we got good Taiwanese food.

Speaker 2:
[28:48] All right. But how often do you eat that?

Speaker 1:
[28:51] Once a month, once every two months.

Speaker 2:
[28:52] Once a month, once every two months. That's the challenge, right? Even your favorite food is probably not something you're going to do every single day. When you're talking about an activity like eating, which is 20 to 25 times a week.

Speaker 1:
[29:03] It's not like coffee.

Speaker 2:
[29:03] Yeah, it's not like coffee. It's even different from travel where a product may be the same every single time. I think it is tough to create what you're describing, which is this program in which you'll be known as regular. But that, I think, is the opportunity that at least we're thinking about at DoorDash. Because if you think about it, our product with now over 100 million plus annual customers, tens of millions of monthly customers, they shop at various frequencies. And they're building relationships with all of these businesses, sometimes many times a day, sometimes once every other month, sometimes once a year. And I think because there's 20 to 25 moments per week, I think that there is an opportunity in which we can create that. And now, we recently acquired last year a company called Seven Rooms that manages a lot of the in-store bookings of restaurants, particularly of higher end restaurants. If we can democratize that and give that to everybody, and then also layer on the DoorDash data set, and actually kind of tell you that John is a regular and he tends to like the following things, and here's other things that he tends to do, perhaps we can crack open that question.

Speaker 1:
[30:19] So you want to help restaurants take care of regulars?

Speaker 2:
[30:21] Yeah, because that is how you build a great consumer business.

Speaker 1:
[30:25] Yes.

Speaker 2:
[30:25] Right? You need the retention. That is true for every restaurant, every consumer business.

Speaker 1:
[30:31] That's interesting. A core challenge for marketplaces like DoorDash is streamlining courier operations like letting their network of couriers and shoppers make specific purchases for customers. Think about it, you can't use a traditional corporate card here. You don't have the right permissions, you don't actually get to interface programmatically with the card in real time. So Stripe issuing is our answer to this problem. With Stripe issuing, you can use Stripe to create virtual or physical credit cards. They can be single use, single vendor, programmatically controlled, whatever your use case needs. People are even these days giving their open claw a credit card, so it can spend money on the Internet. So if you need to create credit cards to manage spending in the real world, see what you can build with Stripe issuing. We were talking a lot about ghost kitchens, I don't know, five or seven years ago. You don't really hear about them that much. How big have ghost kitchens become?

Speaker 2:
[31:27] They're relatively small.

Speaker 1:
[31:30] People thought the model was going to take over, right?

Speaker 2:
[31:32] Yeah, look, the model sounds really reasonable and anything logical on face value, where if you can, on that spectrum of restaurants where you have high-end service on one end and hospitality only to perhaps delivery only or more of a manufacturing concept on the other end, it seems reasonable that you can actually just borrow a small square footage of space, not incur a lot of not just the fixed cost, but also the labor cost of actually running your restaurant in quotes and then selling through a delivery platform or acquiring your own customers or doing something like both. It just turns out it's extraordinarily difficult, however, unless you're a large brand or a house of brands, someone like DoorDash, to be able to attract enough customers to make that math work.

Speaker 1:
[32:24] So, is another way of putting it this, it's hard for a ghost kitchen to be as efficient as a restaurant that is also churning out orders across both in restaurant and delivery, like it's just hard for them to compete on the economics?

Speaker 2:
[32:43] Yeah, it's slightly different. So, perhaps we can look at two types of examples. So you can have one type of example, which is perhaps, you know, my mom's Chinese restaurant, you know, it's an SMB, where the name value outside of perhaps, it's literally, it's locale, isn't that well known. It's very difficult for that restaurant to acquire enough customers to make that math work, because they still have to, remember, I mentioned that staffing was the number one challenge that restaurants face. They still have to staff these kitchens. You know, that's one of the challenges. Now, you go all the way to the other side. To pretend you are a large QSR with a big brand presence, you certainly can attract lots of customers. But you're going to have to think for yourself, well, what's my opportunity cost? My opportunity cost might be to open up another restaurant. Why not do that and take my economies of scale and actually apply it to more orders, in-store orders as well as to-go orders, because I can do that with a restaurant. Hard to do that with a delivery-only kitchen. And so I think because of that, it's a tricky model to scale to every type of restaurant brand.

Speaker 1:
[33:51] Yeah. I think people maybe thought that big chains were going to do it more, where you're right, the billboard effect for an actual retail presence is hard to compete with, where you get this very cheap customer acquisition from the fact that people know your name from the high street or maybe have been to you. As it goes kitchen, you need to make up for that awareness gap. But if you're Chipotle, maybe people thought that the orders get fulfilled out of a dedicated Chipotle central factory, and then the retail space are separate. But also, that hasn't really happened that much.

Speaker 2:
[34:26] That happens occasionally, and it's because I think these are not decisions where we're accounting for all of the variables. One variable we're not accounting for is, well, what else could I do with the space? You have to remember, for businesses like Chipotle, who tend to identify real estate in fairly expensive areas, there's high opportunity costs of what you do with that space. Yes, you're right. One choice is to turn it into a delivery-only kitchen, and sometimes that happens. But there's also a massive opportunity to recoup the expense, and if you start introducing, for example, franchises for, Chipotle is not really a franchise, but if you look at other types of brands where it is franchise, I think that the economics become even trickier.

Speaker 1:
[35:17] So, the next best use kind of math. Which restaurants have actually invented something that's hard to copy?

Speaker 2:
[35:23] Well, I actually think any restaurant that's been around for, let's say, two plus decades, probably has very interesting IP. And obviously, some of this information is not public, but you could imagine when you go into McDonald's around the world, that French fry, perhaps they don't sell the same exact items in every single store in every country, every city, but the French fry almost always tastes the same. That is an extraordinarily difficult feat to accomplish. There's a lot that goes behind the scenes, just like there's a lot that goes behind the scenes at DoorDash in terms of getting you one order on time to make that sentence true. And the same can be said about a lot of other businesses that have been around for very long periods of time. That's on the big brand QSR side, where a lot of the innovation, if you will, is in the process innovation. And then also, how do you run large groups of people and have very high and consistent standards of service? Extremely difficult, extremely difficult. And that's the IP, I would argue, for a lot of these large brands. Now, on the other side, there are small restaurants, some of whom have been around for almost a century, actually. There aren't that many of them. But when you look at what makes them special, it tends to be the same things that actually make startups special. Tends to be a small group of people that really believe in a certain idea, some commitment towards some standard of excellence. It could be excellence towards the food, the service, or takeout. There are some takeout-only businesses that have been around for many decades, and as a result they have high retention, high usage, and they're very efficient.

Speaker 1:
[37:12] Can you speak about any specific examples of just the impressive IP that these chains have conducted over the years? Like it could be the McDonald's French Fry, how they actually make it taste consistent. I don't know the answer to that or any other of your favorite restaurants.

Speaker 2:
[37:26] Yeah. Well, one of the things that I'll never forget was, I went through a hospitality training at Chick-fil-A in, I want to say it was 2017, maybe it was 2018. And I don't remember everything on the checklist, but one of them that stands out is that the floors must be so clean that babies would lick them or could lick them.

Speaker 1:
[37:55] The babies will lick them regardless of how clean they are. Is Chick-fil-A still the highest grossing fast casual restaurant per square foot?

Speaker 2:
[38:02] I don't know actually, but it's definitely up there.

Speaker 1:
[38:04] People talk about it.

Speaker 2:
[38:06] Yeah, but it's definitely up there.

Speaker 1:
[38:07] Why is it so successful?

Speaker 2:
[38:09] Well, it actually goes back to, I think, the standard ingredients of a great consumer business. It has a highly retentative following, which it spends very little money acquiring, and they come back often. And they're extremely efficient with all of the scale economies behind the scenes around equipment, which is quite custom to that company, to the service training, to how they treat their staff. I mean, one of the most impressive facts about that business is that, many people actually that I met with have spent over two, three decades of their careers at Cheeky-fil-A. And, you know, I think we find that to be a novelty, actually, here in Silicon Valley or in technology.

Speaker 1:
[38:57] I'm in the restaurant industry.

Speaker 2:
[38:59] And in the restaurant industry, one where we described all of the churn and the difficulty of staffing, Cheeky-fil-A has extremely high retention of staff. And it has, you know, so many repeatable stories of where, you know, it gives somebody who comes from not a lot of means, frankly, to become the general manager of one of these stores, and earns a really healthy living, pays, you know, their entire family through college and beyond. And I think it's, you know, many ways a lot of these restaurant stories, Cheeky-fil-A being one of them, have a lot of the essence still of the American dream.

Speaker 1:
[39:39] We're talking a lot about QSR chains here. And people often like to ask the question of, why is there not a Chipotle of, you know, my preferred cuisine, where it's, you know, slightly elevated versus like regular fast food, very good consistent quality, good execution. There is no chain that serves you really good Neapolitan, you know, thin crust pizza in whatever city you're in, or Indian food, or again, pick your favorite cuisine. Why don't we have more chains delivering just a really good standards version of the cuisine?

Speaker 2:
[40:16] Have you ever cooked for a large group of people? Do you cook often?

Speaker 1:
[40:20] Yeah, we cook, but not for huge groups.

Speaker 2:
[40:22] Yeah. And one of the things I found is that as the number of people you have to cook for grows, the difficulty to keep the standard of service, whether it's the taste, the temperature, the speed in which you receive the food, goes up exponentially. And that is what's so hard about exactly what you just said around keeping that quality control really high. It's maybe easy to build you the Chipotle for one type of cuisine for one restaurant. And that's just on the skill perspective. Although, you know, I do have some ideas on how perhaps you can do that. But the second reason also is, think about who you're competing against, right? So you have to now, okay, let's say that you want to make a Neapolitan pizza. You mentioned that, or any kind of pizza. Okay, great. Great. I can't wait to taste it. I can't wait to taste it, John.

Speaker 1:
[41:14] Okay.

Speaker 2:
[41:15] Well, did you know that there are over a thousand different pizza choices in the Bay Area on DoorDash? Just on DoorDash, right? And we don't have all the restaurants. And, okay, that is just one of the many things that you're going to have to do to be able to create this concept and actually scale it. And then don't forget all the other challenges we talked about, the staffing, the permitting.

Speaker 1:
[41:42] But what determines whether chains succeed versus whether they don't? Because a lot of pizza restaurants in the Bay Area, but at the same time, there's a lot of Mexican restaurants in LA that are really good, and yet Chipotle still has plenty of locations there. And so it doesn't just seem to be, you know, do there exist local options? Sometimes a chain can break through. I also don't think it's a skill issue, because it's very process-isable to make a good Neapolitan pizza. It's about, you know, the ingredients and the temperature and humidity control in the proofing the dough, and then the, you know, cooking it at very high temperature. But it's not rocket science. You could make a process around this.

Speaker 2:
[42:22] Potentially. But I think the fact that there only exists so many of these QS accountable number, of these brands who have actually scaled to the size that we're talking about, where they're ubiquitous, I think, you know, should be some evidence.

Speaker 1:
[42:39] It's harder than you think.

Speaker 2:
[42:41] You know, that it's a lot harder than you think. And because of what I just said, there's a lot of process skills that you have to be extraordinarily good at. In fact, I remember we partnered with one brand where we launched this brand to great fanfare, and sold a lot of burgers, actually, on a weekend testing this idea. Can you make a healthy tasting burger if you put a brand name around it? The answer is yes, and the answer is really hard to retain any of those customers.

Speaker 1:
[43:15] Because it's too healthy?

Speaker 2:
[43:16] No, because half of the reviews said your burgers were great, and the other half said that they were inconsistent in quality. And it's because it's extremely difficult. That exponential challenge as you try to grow scale and keep up the quality is very, very, very difficult. I mean, you have to get right the service, you have to get right the production, you have to get right the pricing, the packaging. There's lots of things you have to get right.

Speaker 1:
[43:44] So do you think reliability is the thing that people underestimate about the restaurant industry?

Speaker 2:
[43:49] Yes, or about a service like DoorDash. I think when you have high volumes of activity, I think keeping the reliability as reliable as the electricity we have or the water inside of our buildings, that is extraordinarily difficult.

Speaker 1:
[44:03] Can we talk about the future of delivery and how you see it playing out in 10 years time? There's a few different modalities being discussed. There's drone delivery, there's sidewalk robust delivery, and you guys have Dot, I'd love to talk about Dot. I don't know how much you're doing in drones, maybe you can talk about that too. Maybe there's autonomous vehicles like autonomous cars, people don't talk about that that much, but maybe in the suburbs, it would kind of work. That's what we have at the moment. Just like what's the mix in 10 years time?

Speaker 2:
[44:31] Yeah. Well, I think even before we go there, I think the first question might be what might be delivered, because I think that's actually still not that well understood. So today, yes, DoorDash is probably most known for food, potentially now increasingly groceries and household items. But that is a fraction of the tens of millions of items inside every single city. One of the biggest things that we're going to have to do before we can just fulfill the items, which is what we'll get to, is where are the items and what are the items? There's tens of millions of items literally inside these cities, whether it's in the US or different countries within Europe, other parts of the world, they're not catalogued. There's no structured data that you can scrape in order to figure that out. And I think that's going to be a long journey. Sometimes the inventory is not even close enough. And so you may have to house the inventory, so that you can actually bring those goods, and even have the right. A lot of what I believe makes for great logistics is you need a great setup. Because if you're always trying to figure it out on the fly, and you're pulling some magic trick out of thin air, and you have to be the hero, that is not a system. That is an exception. And I think great logistics or great reliability, they require building systems. And so, okay, you have the catalog, you got maybe the inventory close enough to where people live. Now, we can talk about the fulfillment. But the entirety of that is what you have to build. Before we can get into the great technologies and aviations.

Speaker 1:
[46:07] The staging of what it is that you're delivering.

Speaker 2:
[46:09] Because if you don't know where to get the items, or if you can't get the right item, what difference does it make if you have the right vehicle?

Speaker 1:
[46:19] And you're talking about the fact that you don't actually know what's on a supermarket's shelves where the fact that you have to actually be able to predict when the restaurant will have the stuff ready, like all that kind of knowing what is ready to be delivered. Yeah.

Speaker 2:
[46:33] Or, I mean, take when the Cheeky Pint becomes an established bar and maybe DoorDash can deliver from one day. What's inside the Cheeky Pint? What's on the actual menu? What's off menu and actually you can order? I mean, these are complicated issues before we even get to the fulfillment of the actual items. And so, okay, then you can get to fulfillment, right? And I think that's one where we're still exploring. And to me, the most important question we always ask on any, frankly, technology, but certainly a technology like this, where there's long cycles of development is, what problem does it actually solve? Obviously, in the case of drones, you mentioned it, it can cover a lot of ground very quickly. So, longer distance orders, that seems to be a great job for it to solve. In a busy high-rise area where you got short, dense orders, which is the majority of these orders, maybe not the best solution for such product, right? And this is actually what led us to the creation of Dot, which was when we started the Autonomy Project in 2018, 2019, we actually did not set out thinking that we needed to build anything, that we would surely there would be someone.

Speaker 1:
[47:47] We'll just pick the best one and I'm sure we can buy some tech off the shelf.

Speaker 2:
[47:51] Yes, we were out there raising our hand, asking for a partner to the dance, so to speak, and someone who could specialize in that, we could specialize in the operations and things like this. And it turned out that, well, no one was that interested. A lot of people were interested in building robotaxis, a lot of it, and obviously we've seen that come to fruition. A lot of people did build, to your point, sidewalk robots, but we found those to be too slow, so back to what problems are you solving? Because you got to remember, back to opportunity costs, humans are very good at delivery actually, it turns out. We're also very good at driving too. And so, the bar is actually a fairly high bar. It's not as simple as just saying, oh, we can make the technology let it rip. And so, then we said, well, okay, well, it has to be fast enough. It probably doesn't need to be the size of a car because cars are very good at parking inside these busy locations where a lot of these restaurants are. And so, we had to think about all these things. We had to think about how to load the vehicle. We had to think about unloading the vehicle because unlike Robotexi, the passenger solves all of those problems, but in our case, we have to solve that. So, that's kind of how we ended up on this.

Speaker 1:
[49:02] Where are you enrolling at Dot?

Speaker 2:
[49:04] We're primarily testing right now. We really want to get it right in one market. We're doing a lot of this in Arizona. And because it's not just the technology. Yes, that is one of the things I've learned and come to appreciate about building something like Dot is that these autonomous vehicle companies are almost many companies inside one company or certainly many different types of skills you have to be good at. Yes, I think everyone obsesses over the autonomy. Okay, but there's also the hardware. There's also the manufacturing. There's also the operations.

Speaker 1:
[49:39] There's hardware reliability.

Speaker 2:
[49:40] There's also the maintenance. Yeah. There is also the regulatory. There are a lot of different components that you actually have to be good at. And then we can talk about the stack required to actually build the inputs to some of these things. For example, there's also understanding how do you procure supply when you have sometimes geopolitical tensions or when you have supply chain disruptions. Where do you do assembly versus where do you do construction? Not super obvious answers to some of these questions at times, especially when you have to make these decisions sometimes years out. And so I think that's the stage that we're in right now, which is, okay, we got to figure this out correctly before we can actually scale it.

Speaker 1:
[50:25] Where do drones fit in, if at all?

Speaker 2:
[50:26] They definitely do. I mean, as I mentioned, back to jobs to be done, I think drones obviously can do a lot of these longer distance orders. And so we've been doing drone deliveries actually for a couple years now, mostly outside of the United States. Outside of the US. Places like Australia, we're going to bring them to Europe, bring them to the United States as well. But again, you have all of those problems you have to solve. The autonomy is a little bit easier. You still have a routing problem, you have hardware problems. Obviously, you still have permits and regulation, set up, loading inside different stores, things like that.

Speaker 1:
[51:04] Very interesting. We're talking a lot about some of these scale tech problems and one of the ones that people might not think about is fraud, but I feel like Stripe and DoorDash obviously work together in many ways. One thing we work together on is fraud. And I feel like the number of potential fraud vectors is much more complex than people think. Maybe you can just talk about trust and safety at DoorDash, all the different ways that people try. Like you're running this complex system that people try to game and what it takes to run that.

Speaker 2:
[51:36] Yeah, I mean, many times I kind of think about my freshman year electrical engineering course on state machines and where DoorDash in some ways is like a large state machine, right? Where you have many systems in place and they're kind of observing what's happening. There are things that must happen when things are green to keep them green. But as we start degrading gracefully, from green to yellow to orange to red, something like fraud, as you mentioned, other systems have to kind of kick in and do things like exception handling. Obviously, you're spending most of your time building prevention systems, but of course, it's tricky. You also have to have the 911 response system that literally responds within minutes because sometimes we're talking about physical safety. We're not just talking about fraud, right? I mean, given the volumes that DoorDash carries billion dollars per year, the one in a million incident unfortunately does occur. And so, that's DoorDash, this is system. Now, in fraud, you're right. We partner, for example, a lot on online fraud. I mean, you have the largest database, right? Of all of these transactions and therefore, you can give us lots of information that we ourselves couldn't do on our own. On the flip side, there's also offline fraud, which is very tricky to catch. Okay, for example, let's say that a consumer suggested that an order was never dropped off. Let's say that a Dasher said that an order at a grocery store was already shopped and picked. But we're not sure. Or let's say that a Dasher said an item is missing inside of a store, any kind of store, maybe perhaps an apparel store. All of those, I would argue, have offline components that are difficult to verify. This is building the eval, if you will, for this set of conditions and use cases, it's actually extraordinarily difficult. And so, a lot of what we're trying to do is, we have to build those signals ourselves. There is no perfect science here. I wish there were. But in many ways, we kind of have to invent this. This is actually why, I'll give you a few examples. So, one of the things that we shipped, this is actually a couple years ago, was called SafeChat, where we noticed that prior to any physical altercation that may unfortunately happen between audiences, 90-something percent of the time, it's always preceded by a verbal altercation. Knowing that alone allows us to prevent a lot of tough situations, or building alert systems. For example, sadly, there are shootings, particularly in the United States. And there was one shooting in Manhattan, where several people died in the lobby of a large office building. But within minutes of a Dasher seeing the shooter walk in to the building, we have an alert system that doesn't just alert all Dasher's and consumers and merchants within that vicinity, but also all local law enforcement. And actually, we were the first to report that. To the NYPD, who tried their best to respond in time. But there are a lot of those events. And so, it's not always about fraud, I guess is what I'm trying to say. And that you have to build extremely responsive systems, and you also have to build as many signal detecting systems too.

Speaker 1:
[55:15] Yes. You're running a fairly large slice of the economy, and you're trying to have everything run smoothly, and there's quite a lot of failure modes that people might not think about that are possible when you're just seeing so many economic interactions all day.

Speaker 2:
[55:27] Exactly. We're trying to be the digital representation of these cities, right? Whether it's a city, a suburb, a neighborhood, a rural area. And sometimes, it's not always of what's transacting, but it's just what activities are occurring.

Speaker 1:
[55:42] Yes. One of the hardest kinds of fraud to prevent is, like the classic credit card fraud, one that people think about is your car got stolen, and it's actually someone overseas buying stuff for themselves, rather than you buying it for yourself. That, we've actually now got very good at detecting, it's quite hard to do, and there's just so much data we can bring to bear on that problem. A much harder one that we see businesses face is, the kind you're saying is the industry term of ours is kind of funny, is Friendly Rod, which is a bit of a euphemism. But the customer buys something and just says, it never arrived when it actually did, and they're just straight up lying, but you don't really want to call them on us, you also don't have proof that they're lying, but it definitely does happen to some degree. And so how do you deal with, I mean, maybe there's a photo of the Dasher having delivered it, but I'm curious how you deal with people just kind of defecting from the system.

Speaker 2:
[56:39] There's no one answer, as you know, with fraud, because as soon as you figure out how to measure the risk and contain the risk, obviously the incentive for the fraudster goes towards the next axis of breaking it. Exactly, exactly. And so I don't think there's a perfect solution to the problems that you're describing, but you're right. I mean, a lot of this is about, a lot of how you build systems, I think, where obviously the metric is around reliability and consistency and great customer outcomes. The inputs are a lot of measuring things before things happen. I talked about, I think, one of the most important things about logistics is the setup. That happens even before a delivery event, if somebody hits place order, right? The setup is extraordinarily important. Did you get the right catalog? Did you actually label correctly the catalog? Blah, blah, blah, blah, blah, blah. A lot of that's a short step.

Speaker 1:
[57:29] Okay.

Speaker 2:
[57:30] Now, in the case that you're describing, we can track several things. We obviously can track what is happening with the Dasher. You mentioned some of these ideas, taking photos of receipts or orders being dropped off. We have our own mapping system, for example, that we built. Why do we build our own? Well, it's because we care much more than any third-party mapping system of exactly where the last two feet, forget 20 or 200 feet, of some apartment unit door is, for example. And we know if we reliably deliver to that door, and that we saw that the pin actually hit exactly where, we have a little bit more fidelity in whether something was dropped off. We build profiles of customers, I'm sure you do too, of their behavior and what they tend to say. So there's lots of things that we're trying to do behind the scenes to build these signals to figure out what is the likelihood here of fraud.

Speaker 1:
[58:24] Yeah, makes a lot of sense. Tell me about DoorDash Tasks.

Speaker 2:
[58:29] DoorDash Tasks is something that we shipped recently, where actually it started with a project where we're trying to solve our own problems. So it started with trying to figure out where is every item inside the city. And so we have millions of dashers, and they're usually frequenting different types of stores. We know that consumers move around items a lot, which makes it extraordinarily difficult for any store to track their own inventory. And so dashers sometimes are collecting this information, right? That was one of the problems that we were solving. Interestingly, while we were doing this, we started getting calls actually from people you probably would expect. Retailers and CPG companies who might be interested in this information. And then especially as companies, I think it's well known at this point that a lot of the large LLM companies have been building lots of repositories of online information. Well, what about the offline information to bolster some of those models or just to help some of these companies building robotics and things of the sort? Well, we said, oh, interesting. Well, okay, we're building a catalog for ourselves, but we ought to be able to help other people too. And if it's an opportunity to help Dashers earn more or give them more choices to earn more, great. Why not build that solution? And so that's really the story of DoorDash tasks, which started organically probably a couple of years ago as we were solving our own problem. And we started realizing that there may be other people who have similar tasks.

Speaker 1:
[60:09] And so it is a platform for having fairly small tasks done. So you can give the task to DoorDash and you guys go complete it or kind of?

Speaker 2:
[60:17] Yeah.

Speaker 1:
[60:17] Do you get excited about an AR angle for DoorDash where are you one of the best use cases of the meta glasses? Where no, you can catch like directions within the store and everything, like you actually speed things up quite a bit rather than wandering around lost.

Speaker 2:
[60:30] I think we could be, but I think we definitely could be. But again, like back to the question of asking, what problem does this solve? That the human is pretty good with their eyes at some of this stuff. So the bar is pretty high in order to do some of the things you're talking about.

Speaker 1:
[60:46] Yeah. As I just think through AI applications for DoorDash, one of the things I'm struck by is that the LLMs are pretty good recommenders just by tossing things into context. You don't need to train a custom model. But I don't know if you've ever tried for like book recommendations or TV recommendations. You just tell it a bunch of the stuff you like already. Restaurant recommendations, it's like, here are 15 restaurants we like to go to, give us other recommendations and it'll do a really nice job. And yet within products, if I open DoorDash, it's kind of the same categories and things like that. And it's less personalized to me than if I took my DoorDash history and put it into an LLM. Isn't that, shouldn't we be somehow using the fact that LLMs are pretty good recommenders within products? It's not just DoorDash, it's every product I use. It feels like those recommender capabilities are underutilized.

Speaker 2:
[61:38] I think you're definitely right that there's an opportunity here where there's almost like the traditional school of thought, which is to use the information that you have, and you build the best personalized models that you can. And one of the things that LLMs obviously does is it throws efficiency out of the wall from the wall, and it throws as much compute towards it. And interestingly enough, one of the things that spits out when you put in enough tokens and have big enough context windows is you're right. It has actually better models because it's, I mean, it's just using much larger data sets. And it's a world model. And it's a world, exactly. And so I do think there's an opportunity in what you're saying, which is that products like DoorDash, like consumer products, will definitely have their own ordering agents. And I think we're all trying to figure out what is that right modality, right? Because it's not obvious to me that everything is going to be done through text. We don't buy things through text. And we don't always get inspired through text either. And so I think it's something that we're all figuring out.

Speaker 1:
[62:49] What else are you excited about these days from a product point of view? Like what's a new part of the product that is close to your heart? Or where do you want to take things?

Speaker 2:
[62:58] Well, we have a few missions that we're on, and we talked about several of them, I think, in this conversation. One of them is we got to bring you everything inside the city, and we're a long, long, long ways from that. We can go super deep on restaurants and food, but as you start going into category N plus one, we are just a smaller and smaller and smaller drop in the oceans. We got a lot of work to do. A second mission, obviously, is we also want all of the businesses that we support to have their own software. I mean, DoorDash's goal is not just to grow your business by sending you customers, we also want you to learn how to do it on your own. And that's why we have products like DoorDash Drive, or Storefront, or Seven Rooms, which are really B2B products, which is probably why consumers don't think of us for them, and help you build your own omni-channel business. We have a mission in which we want to actually bring you inside stores. That's actually something that we're trying to do, right? And we started that about a year ago. I mentioned earlier that one of the perennial challenges or trends for restaurants is, how do you grow your own brand? Well, if we can also help you with that, both by helping build for you a CRM of a 360 view of guests, where we can also send you customers inside stores, we'd love to do that. We're starting with restaurants with two products. One is called Going Out, the other is Reservations. That's a big mission that we're on. And so, we have several of these missions that I'm pretty excited about.

Speaker 1:
[64:31] Yes. When you mention Reservations, there's a number of quite established companies in that space, and restaurants are famously, they're not exactly just eager to wake up and switch all their systems one morning. So, how do you plan to unseat the existing guys in Reservations?

Speaker 2:
[64:46] Well, I think it starts with the idea that I believe that no restaurants should own their own reservations, ideally technology. It starts with that. Reservations book, we can get into super deep here, it's actually quite complicated to run a book actually. I mentioned earlier this idea that restaurants, North Star really should be to build regulars, right? But that's not how every reservation system is designed. And so, I actually think the most important thing is that restaurants can have reservations on any platform actually. That's actually what I believe. And so, that's one of the main premises behind seven rooms too, it's that it's agnostic to who generates the demand for you. What it's trying to do is to make sure it achieves your objective function. It may be to grow profits one year, it may be to grow locations the next year, maybe to get a certain type of customer the next year, so on and so forth. And so, I think it starts by building what's best for the merchant. And then, hopefully, DoorDash can make a difference, too, where we just have more customers than people that play with restaurants, and also more information that we can supply to these restaurants on how do you make more money to achieve whatever outcome you want. And so, if we can help achieve a restaurant's objective function better than anyone else, well, then hopefully, we have a seat at the table.

Speaker 1:
[66:17] Talk in reservations, they carved out a successful niche in high-end reservations, and I think about one of the beliefs that informed their products most strongly was that no shows are terrible for restaurants, and a restaurant reservation should be like a flight reservation, where you don't just get to decide you're not going to go to the restaurant.

Speaker 2:
[66:36] You put a little deposit.

Speaker 1:
[66:37] Yeah, exactly. You put a little deposit down. Do you subscribe to that philosophy? Do you think it's maybe less relevant, again, they're really dealing with very high-end restaurants. Do you think it's less relevant for regular restaurants? I'm just curious what you think of that viewpoint, that we're doing reservations all wrong, was I think one of the founding insights of Talk.

Speaker 2:
[66:55] I think it makes a ton of sense. The implementation of the idea is what's difficult, right? And restaurants that have very limited seating and very long seedings, the opportunity cost for a cancellation is very high versus a restaurant that may have infinite production capacity, if you will. So I think the implementation idea is what matters, but I think the idea itself makes a ton of sense.

Speaker 1:
[67:23] How do you, with reservations, plan to ensure that people aren't no-showing to restaurants?

Speaker 2:
[67:29] Well, we're working on that problem right now, but I don't think there is one thing. I think the first thing is we have to help you find reservations that you want to go to. I think there's a lot of room left in the space to innovate there. I don't think there's been that much innovation in that area.

Speaker 1:
[67:47] So discovery is almost a bigger problem.

Speaker 2:
[67:48] I think discovery is very difficult. I mean, how do you find out about restaurants today? I'm curious.

Speaker 1:
[67:55] My wife finds them on Instagram.

Speaker 2:
[67:56] Yeah.

Speaker 1:
[67:57] Okay.

Speaker 2:
[67:58] Yeah. And I think that that's right, because there are so many different sources now. Instagram is one I'm sure other social channels are another. LLM, as you mentioned earlier about throwing things in there and getting something out. Friends, I'm sure. I think it's really difficult still. When I think about no matter the sources of input, most restaurants still struggle generating their own demand.

Speaker 1:
[68:23] Yeah.

Speaker 2:
[68:23] And so, I think that's so long as that's true, I think that we have a shot at making a difference.

Speaker 1:
[68:30] Yes. You talked about European expansion. You just acquired Deliveroo. In what ways are the Deliveroo and DoorDash businesses different?

Speaker 2:
[68:40] Well, fundamentally, they're more of the same. I served that actually.

Speaker 1:
[68:43] Hence the acquisition.

Speaker 2:
[68:45] Yeah. But okay, well, we talked a lot about systems and logistics. Have you been to London? I'm sure you've probably been there many times. You probably know it better than I do. But it is an interesting city in that it doesn't actually have a lot of the grid-like hub-and-spoke properties of a lot of cities. And there's a lot of reasons for that. I know we can go into the history.

Speaker 1:
[69:10] Mostly age, but yes.

Speaker 2:
[69:11] Yeah. But well, no, no. There are other cities that were actually designed differently in other parts of Europe, actually. We can get into other countries and cities. But age is one of them. It's not meant to be a city where you drive a lot of vehicles, no vehicles are managed.

Speaker 1:
[69:24] I think it's older than even a lot of other European cities.

Speaker 2:
[69:27] It is.

Speaker 1:
[69:27] Even as European cities go, London is really old.

Speaker 2:
[69:29] Yes. And as a result, that alone makes the logistics problem very, very different. And the logistics, not just the algorithm, which I think is just one part of the system, but the signals that you'd want to collect are very, very different. Vehicles are very different. We predominately are non-autos in the city of London, which is very different in the states as an example. That's very different. The regulatory setup is different. It has parts that rhyme with the US, but as you well know, each country is slightly different even though, I guess, the UK is not under the EU, but even within the EU, each country has their own local version of regulation. That's very, very different. You know this probably better than anyone in the world. Payment processing is very different. There are many more card types in parts of Europe than say in the US. So industry dynamics on retail are very different. In the US, we have a fragmented retail industry that has a lot of different players.

Speaker 1:
[70:37] That's more concentrated in the UK?

Speaker 2:
[70:39] In the UK, in Germany, in France, in a lot of European countries, actually. This is more the norm than the exception, whereas in the US, you have maybe hundreds of different big brands that are strong in certain regions, but in Europe, that's less true. Those are some of the immediate differences that come to mind.

Speaker 1:
[70:59] A mystery to me is why the pharmacies are so much better in the UK versus the US. You go into a Boots versus you go into a CVS or Walgreens, and it's like night and day.

Speaker 2:
[71:12] Yeah, well, one of the things I would say, just as a standard matter, is because of the concentration. And it's really concentrated by category. Pharmacies could be a category, certain apparel can be another category, etc. And this is true in Australia, this is true in Germany. The standards are higher and they're more consistent of that service. But where in the US, when you have tens of thousands of supermarkets, hundreds of big brands, it's different, it's different. And then if you look even more upper funnel, say CPG, there's a lot more CPGs in the US market that are competing than say in some of these other countries, which make things like inventory management, the skew count, the size of the stores, all of that, therefore is different.

Speaker 1:
[72:03] Yeah. You referenced some of the stuff we're doing together. I think of Stripe and DoorDash as almost having grown up together, funded at very similar times, and then you guys were early users of all manner of products, like Stripe Connect or Radar or issuing for cards or things. What would you like to see Stripe do that it doesn't today? Either because you guys would like to use it, or just because you think it's something we should be doing. I've been giving you all my silly product suggestions. This is where you get to turn the tables.

Speaker 2:
[72:30] I see.

Speaker 1:
[72:30] King of the years.

Speaker 2:
[72:32] I would always start with what our teams would say. So probably the first piece of advice always is, what problems are you solving for us? Because I think especially as companies grow in size, success, variety of products, I think there's a natural temptation to start imposing what the companies want to do or want to solve or want to sell, versus say, what problem does it solve for the customer? So I am sure one of the things that could be true is, making sure that you're solving our top problems, versus just introducing the range of products. That's probably one thing that we probably both share as advice for one another.

Speaker 1:
[73:21] Oh wow.

Speaker 2:
[73:22] We got Dot coming.

Speaker 1:
[73:25] Oh awesome. So this is Dot?

Speaker 2:
[73:26] This is Dot. Well, there you go.

Speaker 1:
[73:29] It's kind of like a TARDIS. Oh yeah, we're talking about, what were we talking about?

Speaker 2:
[73:34] One of the things I'll never forget talking to you and Patrick about, as we kind of grew up together in the years of building our companies was, I think both of you have always had the idea that Stripe is a technology company that happens to be in payments. It's not a payments company. And you've always challenged, I remember, your customers to think about, don't just think about accepting payments and there's more that you can do. So I am curious, what more can we do, should we be doing with things like crypto or stable coins?

Speaker 1:
[74:08] Two topics that are on the minds of all our customers today are, yes, stable coins and then AI, specifically with respect to changing buying and agentic commerce. Unstable coins, I think maybe DoorDash is not where I would start. Two places that we're seeing tons of interesting stuff is, one, any kind of cross-border use case where if you want to send money to 100 countries, it's already the case that stable coins are a much better way to do that than anything else. And that's where we're seeing a ton of adoption, where just that long tail coverage and they really work for that. The second, and this is where Tempo, our new initiative that you guys were nice enough to work with us on, is coming in is very scalable crypto payments. And obviously, agents is what we have in mind as we're developing Tempo, where if you want to pay for your API consumption, or if your agent wants to be able to pay for things around the Internet, you actually need a really good scalable blockchain for that. So, that's all the crypto side of things. The other thing that we're thinking about a lot is just how does commerce change? Now that people's expectations are increasingly they ask their AI for stuff. And so, it feels like you should be able to ask your AI, whether that's ChatGPT or Gemini, or whether that's Siri, or whatever your interface is to AI. It's like, let's just order again what we ordered on Sunday. You should be able to make that natural language query and have it take care of interfacing with DoorDash and payment and everything like that. I'm curious how you guys think about the interface changing. I mean, you just thought a lot. Do you want to enable people to order within the AI apps? Do you want to have just more of a natural language input to DoorDash? Just how is that going to happen, given this? That is presumably what people want in terms of the low friction AI experience.

Speaker 2:
[76:06] Yeah, well, I think what people want is definitely low friction, but I think people also want the products to show up on time, and I think they want...

Speaker 1:
[76:13] You only get a right to do this cool UI stuff if the logistics is right.

Speaker 2:
[76:17] And the challenge with the product like a DoorDash is, you kind of have to do the whole thing end to end, or you have to have great coordination or communication mechanisms. And so, we definitely agree with you that I think there's definitely going to be a place where, in the future, as these AIs develop their, whatever we want to call them, app ecosystems, relationships, I think, with companies like ourselves, that can exactly what you just said, like do the jobs to be done in their regular life. I think that will be a source of top of funnel for us. I think the hard part is making sure that we can actually deliver on the promise. Sometimes, in the cautionary tale of the past, I remember Google Food Ordering launched in, I forget, 2015 or 16, and they allowed you to order delivery, for example, from various Google surfaces, Google Maps, Google Search, etc. And while on the one hand, it was low friction and they could send lots of traffic, they couldn't get the retention. And this is where we're talking about consumer businesses and retention kind of be the name of the game. And the reason was because they didn't know how to contact the driver. They didn't know if the driver couldn't find you, if something was taking a little bit longer, if something was out of stock. So there's a lot of things that happen after the checkout button. And I think this is one thing, back to what we were talking about earlier about what is the correct UI. It's not obvious to me that it's just a chat interface, and that there are all of these different components that have to be solved. And so I think, the way I think about it is, okay, regardless of whatever we ship, whether it's on our own surface, other people's surfaces, are we solving the end to end job? If we are not solving the end end job, it's not going to matter.

Speaker 1:
[78:08] Last question. What is food that you can get in other places when you visit London, when you visit some other city, that you wish you could get in the Bay Area, but you can't?

Speaker 2:
[78:19] Actually, I really like tea sandwiches. I was literally in London. And for whatever-

Speaker 1:
[78:23] Like afternoon tea?

Speaker 2:
[78:24] Yeah, like little cucumber sandwiches. I'm always looking for a healthy snack in the afternoon. Today I had an awesome thanks to you.

Speaker 1:
[78:33] Healthy snack?

Speaker 2:
[78:34] Oh, delicious, delicious, delicious.

Speaker 1:
[78:35] Have you done the proper afternoon tea with like the free-level platters and the little cakes and everything?

Speaker 2:
[78:41] I did it once with my- I took my kids a couple of summers ago. That was an experience. I think in part because it was new to me and my kids, and in part because I had kids with me, playing with all the different things that they gave us. But yeah, no, I think there's- yeah, one of the things that's really interesting about some of the grocery stores, for example, in European markets is prepared meals is a massive focus, massive. And we have some of that here in the US, to be fair. But in London, I just found myself finding that in every store as I went to shop, you would see so many.

Speaker 1:
[79:19] No, there's a few of these things that I find that are so much better back home in Ireland, the UK, Europe. And prepared food is one of them. Like a sandwich you get in Heathrow will probably be pretty good. A sandwich you get in JFK, don't go there. And like in a shelf in a shop. And some of the stores we have, the cookies obviously much better back home.

Speaker 2:
[79:42] There's some delicious cookies. Yeah, there's some, the teas, there's a lot more choices of teas inside restaurants I found. Yeah, it's been, I think one of the coolest part and greatest privileges frankly that I have at DoorDash is, because we get to interface with all the businesses, of all these different wonderful cities, and really get to meet the people who are building the GDP of those cities. It's not just like the cool economic impact that they're having, but you get to find out about all their passion projects. Everyone is passionate about this stuff. Everyone is passionate about something, and that's one of the coolest things about my job, where you asked me a bunch of questions about different IP and process and things like this. I promise you there is that for every single business inside every city.

Speaker 1:
[80:30] Yeah. It's a cool job where you get to work with people who are incredibly passionate about what they do all day long.

Speaker 2:
[80:37] Yes.

Speaker 1:
[80:37] Yeah. Well, Tony, thank you.

Speaker 2:
[80:39] Thanks so much, John.