The Exchanges

Q What have been your biggest lessons on what works for driver supply and what doesn't?

A At the end of the day, About 80% of volume is, uh, driven organically from word of mouth. So nothing can beat that even today. Uh, and all the paid channels make up about 20% in a mature phase. However, once you start in a market, of course it's different because nobody's heard of your product. So the question really is how do you get the first couple of hundred drivers and the first couple of hundred customers on board? And generally we see the most effective for both sides is a combination of PR. So you always got to get some first launch media and you get some exposure from that. And then the other thing is just paid online ads. And for us, generally, the most effective turned out to be Instagram and Facebook ads. So that's how you get the first couple of hundred people excited. And then after that, your product needs to be great, because if it's not, then all your cohorts will fall to zero. If you actually have a fantastic value proposition, then the other way around, your key factor is going to be positive. You're going to be exponentially growing.

AI assessment note: “About 80% of volume is, uh, driven organically from word of mouth.”

Q What did you do in those six months? I mean, we all remember nothing happened.

A So we did a couple of things. So first of all, we optimized every single thing we could in the business. We're already frugal going into COVID, but that really made us like question every single line of the P and L and we, we squeezed everything we could to, to make the business more efficient. The other thing we did was we really started preparing. How do we come out of this much stronger than going into it? So we actually launched the number of markets. So we were setting them up and it was great timing because all these drivers were low utilized. They obviously didn't get trips. There was no traffic going on. So it was very easy for us to get into these countries and sign up to drivers. They, they, they had no other alternative. And then what we did was that these markets.

AI assessment note: “we optimized every single thing we could in the business”

Q So everyone says in Europe, the trouble is that we don't have people who've seen growth like the U S before. Is that true? And where have you seen that?

A If so, I'd say that it's very hard to find, uh, strong people, uh, leaders in Europe, uh, who actually understand tech companies and who have actually built organizations of thousands of people that I agree with. There's just almost no tech companies of that size in Europe. However, um, When you think about all these other things, whether it's how do you do sophisticated marketing, or how do you build large scale engineering systems? I think those things you can find plenty of talent in Europe. I think that either you can get people who worked in the US and come back here, or you can just learn about how the best companies do it. A lot of their best practices are public. So I don't really agree that like you, you cannot figure out how to do world-class marketing or engineering from here.

AI assessment note: “who have actually built organizations of thousands of people that I agree with.”

Q What do you do then? You vertically integrate and buy them? You partner?

A My view is that most of these companies Like Waymo over the longterm don't want to operate a car network. It's just too much hassle. So I think that these companies can build what they're fantastic at, which is building the software. And then there's going to be companies like us that actually do the real world operations. Because I think most people underestimate how difficult it is to operate a million or five million or ten million vehicles in hundreds of cities, comply with all the local regulations. Collect the payments, deal with customer support, clean the cars, charge the cars, et cetera. I think it's, it's sort of just a scale of complexity. Most people can't even fathom, and they just hand wave and think it's going to be easy. No, it's not. Not to mention the insurance, the financing, the procurement of the cars, et cetera, et cetera. Like, I think that ride-hailing companies like us are absolutely going to be pivotal for these self-driving car companies to actually go to market.

AI assessment note: “companies like us that actually do the real world operations”

Q So everyone says in Europe, the trouble is that we don't have people who've seen growth like the U S before. Is that true? And where have you seen that?

A If so, I'd say that it's very hard to find, uh, strong people, uh, leaders in Europe, uh, who actually understand tech companies and who have actually built organizations of thousands of people that I agree with. There's just almost no tech companies of that size in Europe. However, um, When you think about all these other things, whether it's how do you do sophisticated marketing, or how do you build large scale engineering systems? I think those things you can find plenty of talent in Europe. I think that either you can get people who worked in the US and come back here, or you can just learn about how the best companies do it. A lot of their best practices are public. So I don't really agree that like you, you cannot figure out how to do world-class marketing or engineering from here.

AI assessment note: “There's just almost no tech companies of that size in Europe.”

Q Just take me to that. You've only raised from Daimler and some telecoms and realize that when like, you know, Dan Sondheim and D one come in with a, Hey, you know, Marcus would love to chat. Was that a very natural, normal process? How did that go?

A So actually what I really liked about these, um, New York investors was that they were very numbers oriented. So they really did very deep, very sophisticated analysis about the numbers, the market shares, the trends, and they really liked the story on top of that, but they were mainly invested based on numbers. I think with VCs, it was their way around. So the numbers were great, but they didn't really focus on numbers. They sort of focused on what they thought was sort of the narrative in the industry. And that turned out to be completely wrong. So all these New York guys who bet based on the numbers were the ones who now made a killing on this.

AI assessment note: “what I really liked about these, um, New York investors was that they were very numbers oriented”

Q Where did having no money benefit you? And where did having no money hurt you?

A The biggest benefit for us was probably in terms of attracting the right people, because we could never pay even very attractive salaries in terms of cash. I think we're always paying sort of mid market or low, but what we did to compensate for that was that we, uh, gave people generous equity. So we tried to attract people who were really missionaries, not mercenaries, and that really worked out nicely. And the other big benefit was that it really, uh, defined the company culture. So the first couple dozen people who joined, we went through this brutal period the first couple of years where we couldn't raise any money while our competitors were raising literally billions of dollars. And that just forced us to be so effective at how we spent every single euro. We had this huge analytical dashboards of measuring ROI, measuring every single thing we do. Uh, and that just cascaded now down into what the company is today. But if we didn't have that cash crunch in the beginning, I don't think that ruthless sort of frugal culture would have ever formed otherwise.

AI assessment note: “The biggest benefit for us was probably in terms of attracting the right people”

Q What did you do that made you successful with these launches first?

A So now what is worth to mention is that we weren't the first to market in those places. And that's what really makes Polity unique company, because as I described already, this is a very heavy network effect business. So the first Player has a huge advantage. They have bigger density. They have therefore better pickup times in terms of the cars. Uh, they can therefore offer you a much better customer value proposition. So if you're coming in as a second player, it's generally almost impossible to ever catch up to that. Uh, unless you have something very unique that the other player isn't doing. So what we, we did, there was a couple of differentiators. First of all, we localized much better. So what was clear was that Especially these American players in these markets completely neglected the local needs.

AI assessment note: “First of all, we localized much better.”

Q What were they? Were they, respectfully, were they not as hardworking? Were they not as intelligent? Were they not as ambitious?

A I think it came down to all of those things to some extent, just We, we hire people without the proper vetting process in the first year. I was 19 years old, so I had no clue what I was doing. So many of these people joined with completely different expectations of what I had as a CEO. And looking back, I think it was actually a great exercise because, uh, I learned from that of which are the patterns you really want to find in people, which are the patterns you don't. And after that, I think we codified the hiring process to be much more specific. And then we had a lot of success with hiring in the years following that.

AI assessment note: “I think it came down to all of those things to some extent”

Q Just take me to that. You've only raised from Daimler and some telecoms and realize that when like, you know, Dan Sondheim and D one come in with a, Hey, you know, Marcus would love to chat. Was that a very natural, normal process? How did that go?

A So actually what I really liked about these, um, New York investors was that they were very numbers oriented. So they really did very deep, very sophisticated analysis about the numbers, the market shares, the trends, and they really liked the story on top of that, but they were mainly invested based on numbers. I think with VCs, it was their way around. So the numbers were great, but they didn't really focus on numbers. They sort of focused on what they thought was sort of the narrative in the industry. And that turned out to be completely wrong. So all these New York guys who bet based on the numbers were the ones who now made a killing on this.

AI assessment note: “what I really liked about these, um, New York investors was that they were very numbers oriented”

Q Listen, I'm an investor. We get shoved cap to LTV ratios the whole time by founders. And the question that I always kind of oscillate on is, Do CACs go down with time as you increase word of mouth and brand, or do they go up as you saturate your core ICP in the core target market? How would you advise me?

A So marketplaces have this very unique dynamic, which is that in your first six months, the unit economics are always horrible because you don't have enough liquidity in the marketplace. So you constantly need to subsidize the drivers, otherwise they're going to drop off. You constantly need to subsidize the customers, otherwise they're going to go away. So your first six months of unit economics will tell you effectively absolutely nothing. So they always look bad. And then you just got to have faith in the model that as long as you keep on investing long enough, then you will hit some threshold and then it's going to flip into profitability. And that is almost impossible for any financial person normally to understand. And then that was why it was very difficult for us to raise funding initially as well.

AI assessment note: “So marketplaces have this very unique dynamic, which is that in your first six months”

Q I didn't know that story. I love that. And so we have Oliver then, and we start building out the back end, the front end. The product is now starting to hum. Talk to me about going live. When did we go live and how did that response go?

A Tricky bit is that marketplaces are probably the toughest businesses to get going. So if you build a B to B SaaS application, for example, you can fully control the consumer experience. Uh, that's not the case with marketplaces because you need to overcome this chicken and egg problem. You need the drivers and you need the customers at the same time. And both of them are very impatient. So if a driver signs up, they expect to get trips at most in a couple of hours. Otherwise, they're not going to bother keeping the app online. Especially back then when data was more expensive as well. And then on the consumer side, it's even worse because if they open the app, they need to get a ride in a couple of minutes. If you don't have a car nearby in that area, they're just going to move on. So it's a very tricky marketplace, especially in ride hailing, to get it off the ground. There's many marketplaces that are far easier. So for example, you can contrast this to Airbnb. Like a supplier might sign up, It's completely fine. They don't get any bookings for a few days. They can wait. But that's not the case with a driver. So, um, now, how, how did we overcome that was very tricky. So, first of all, we didn't have any budget because, um.

AI assessment note: “Tricky bit is that marketplaces are probably the toughest businesses to get going.”

Q Listen, I'm an investor. We get shoved cap to LTV ratios the whole time by founders. And the question that I always kind of oscillate on is, Do CACs go down with time as you increase word of mouth and brand, or do they go up as you saturate your core ICP in the core target market? How would you advise me?

A So marketplaces have this very unique dynamic, which is that in your first six months, the unit economics are always horrible because you don't have enough liquidity in the marketplace. So you constantly need to subsidize the drivers, otherwise they're going to drop off. You constantly need to subsidize the customers, otherwise they're going to go away. So your first six months of unit economics will tell you effectively absolutely nothing. So they always look bad. And then you just got to have faith in the model that as long as you keep on investing long enough, then you will hit some threshold and then it's going to flip into profitability. And that is almost impossible for any financial person normally to understand. And then that was why it was very difficult for us to raise funding initially as well.

AI assessment note: “first six months of unit economics will tell you effectively absolutely nothing”

Q I didn't know that story. I love that. And so we have Oliver then, and we start building out the back end, the front end. The product is now starting to hum. Talk to me about going live. When did we go live and how did that response go?

A Tricky bit is that marketplaces are probably the toughest businesses to get going. So if you build a B to B SaaS application, for example, you can fully control the consumer experience. Uh, that's not the case with marketplaces because you need to overcome this chicken and egg problem. You need the drivers and you need the customers at the same time. And both of them are very impatient. So if a driver signs up, they expect to get trips at most in a couple of hours. Otherwise, they're not going to bother keeping the app online. Especially back then when data was more expensive as well. And then on the consumer side, it's even worse because if they open the app, they need to get a ride in a couple of minutes. If you don't have a car nearby in that area, they're just going to move on. So it's a very tricky marketplace, especially in ride hailing, to get it off the ground. There's many marketplaces that are far easier. So for example, you can contrast this to Airbnb. Like a supplier might sign up, It's completely fine. They don't get any bookings for a few days. They can wait. But that's not the case with a driver. So, um, now, how, how did we overcome that was very tricky. So, first of all, we didn't have any budget because, um.

AI assessment note: “marketplaces are probably the toughest businesses to get going.”