Invest Like the Best with Patrick O'Shaughnessy
· Brian Chesky
[00:00:00] S1: This is such a great story. I had this conundrum. We had 7,000 people, we were down to 5,000. I wanted to basically take the magic of the founding of the company in the early stages, when we were in this little apartment working together, and I wanted to work with a team of 10 people, and I wanted to have that team work on one problem. So we ended up focusing on one problem, we said, let's put a team together to focus on improving the guest experience, improving conversion rate. Conversion rate is basically search to book, the conversion rate of people typing in the location and dates and booking. There's a funnel, and you can basically measure the funnel, and you can do A-B test. But more than A-B testing, I wanted to do something where the north star was let's make the experience better and increase conversion. We're going to start with a better user experience. So we put together a team, I think it was like 10 or 12 people. Designers, engineers, a couple of product people, data scientists. It was mostly just a pure software team. We treated it like a little startup. We said, we're going to just focus, and we're going to do a system of crawl, walk, run, then fly. Crawl, fix the bugs, fix the problems of conversion rate, just the easy things. Once you build a little bit more confidence, walk. Start to develop features, Really start to reframe the journey. Then run. Rethink the entire flow. Big features. Fly. Completely reinvent yourself. Everything's going to be measured. Everything is going to be operationalized. The team's results were phenomenal. They ended up delivering the equivalent of, I think in year one, $200 or $300 million in revenue for the company. The following year, it was like $400 or $500 million. Now, we're at a run rate of over 600 basis points, 600 basis points of $13, $14 billion. You get the sense of how much of a lever that is. It was just one team. It grew into dozens and dozens of people, maybe 50 or 60 people, but it was this really lean team. We took that team, and we said, what if we apply it to the next problem, pricing? Same people, another team, totally different team, same model, then another model, then another model. I really tried to work with a team. Initially, I would meet with them every week. Then it became every other week and then every month.
· Brian Chesky
My general philosophy is start really hands-on and let go over time. I'm not a golfer, but I took a couple of golf lessons. Here's an analogy for management. If you learn golf, you want to learn with a golf instructor before you build any habits, because if you learn on your own, you're going to have a weird swing. Then when you get a golf instructor, they've got to change your muscle memory. So the golf instructor's got to watch you swing thousands of times. Eventually, they don't need to see it. You let go over time. What most founders do is the opposite. They bring these people in, they let them figure it out, and then they intervene later, but they already have the wrong muscle memory. So I decided, I'm going to be totally hands-on, do everything with the team, teach them everything I know, and let go. Then do it with the next team. Then I had teams learn from other teams. Then when we launched Services and Experiences, we basically found this other way of innovating. So here's a riddle, or it was a riddle to me. Airbnb, we had this core business that was really successful. It did nearly $100 billion a year in gross sales. For every $1,000 spent in the world, $1 was spent on Airbnb. Except we had the problem where we're like a one-hit wonder. For 18 years, I couldn't get a second hit out. I kept wondering, why is this not working? The answer is too obvious. It was staring us in the face. We kept having the burden of trying to scale these businesses at a global scale from the beginning. When we started Airbnb, we started in one city, New York City. We had 100 users. I was in Y Combinator. Paul Graham goes, where are your users? I'm like, they're in New York. We have not many, but they're in New York. He goes, you're in Mountain View. Your users are in New York. What are you doing here? We went door-to-door meeting users. The basic philosophy is make the problem as small as possible. Get to product market fit, then scale. We launched Services and Experiences last year. It didn't work right away. I'm like, oh shit. We launched Services and Experiences in 100 cities. I went back and I thought to myself, wait a second. Airbnb launched in New York. Uber launched in San Francisco. DoorDash launched in Palo Alto. Let's make the problem small and just perfect a city. We started doing this with new businesses.
· Brian Chesky, Patrick O'Shaughnessy
We basically, with any new business, we're going to do one to 10 to many. We'll pilot in one market, any idea. If we get the market to work, we'll go to 10. If we get to 10 and it works, we'll industrialize. It took us 16 years to get to our second and third business. We started getting those two working. Now, we have 10 to 20 pilots. Eventually, we'll have 50 to 70 new verticals. This is the Hawaii system. It's basically taking this giant company, making it a really small elite team. It's like the Navy SEALs. I work with the teams really leanly. Make the problem as small as possible. I think that's a key thing – make the problem as small as possible, dominate a niche. Peter Thiel used to say this. He was one of our first investors. He said, it's better to have a monopoly of a tiny market than a small share of a big market. This is counterintuitive. Every investor wants to go into big markets. I don't like big markets. Big markets have a lot of competition. Go into a small market and make it big. [00:00:00] S0: Is the reason for both of these things, the idea that it works in Toronto but not at 100 city scale, and the reason a 10-person team can outperform a 100-person team – is the shared reason some sort of better contact with reality? Somehow reality starts getting distorted as you get bigger or something?
· Brian Chesky
[00:00:00] S1: This comes back to the most important piece of advice I ever got. The first day at Y Combinator, Paul Graham said, "It's better to have 100 people love you than a million people sort of like you." That came from Paul Buchheit. Paul Buchheit was a partner at Y Combinator. He created Gmail. The old famous story was he created Gmail, and it took him two years. They said, you can't ship it until 100 people inside of Google love it. It actually took two years to get 100 people to actually like the product. But once 100 people like something, 100 million people like it. It's like, the sample size is enough. The problem is when you try to make something a million people like – you can't talk to a million people. So you end up with this shallow swimming pool. It's like you're trying to heat up an ocean. The ocean just – it takes too long to heat up and you can't tell. Instead of heating up an ocean, heat up a bathtub. Make the problem as small as possible. And you're close to the customer. In fact, if you only are focused on one city or even a subset of city, you can talk to every person. You can put all of these resources on a tiny problem. I guarantee if you take a ton of resources and you put them on a tiny problem, the smaller the problem, the more you'll change the numbers, the trajectory. That will teach you lessons. And they're to do things that don't scale, then you scale. The scaling is industrialization. But product-market fit is a distinct problem from industrialization. You want to basically make the problem as small as possible, understand the user, put yourself in their shoes, blow their mind, do things you've never thought before, do them by hand, make them unscalable, don't worry how much it costs. Just prove the model. It's like R&D. That is a lot like industrial design. It's what we call prototyping. Before you manufacture something, you prototype, and you make prototype after prototype after prototype. Until you make something that you love for yourself or someone loves. So yes, the smaller the problem, the more there's fewer abstraction layers. You're actually on the ground. You're talking to people. That's how you prove it. Hawaii to these pilots, it's all the same thing. By the way, same thing with AI. You're removing abstraction layers, you're making the problem as small as possible, and you're going directly to the source.
· Brian Chesky, Patrick O'Shaughnessy
I think that's a principle that all these things have in common. [00:00:00] S0: It's like we're playing this game of telephone if we don't do it that way, and you just lose information. [00:00:00] S1: This is why founders don't like running large companies. They end up in a game of telephone. They say something and then it goes down like five layers and then it goes back up five layers, and then there are these meetings, and the meetings become like system reviews. Literally, the lowest point for me when I was having meetings about meetings. [00:00:00] S0: You've gotten into this new mode. It's called founder mode. It's not called CEO mode. Do you think you're now a good CEO?
· Brian Chesky
[00:00:00] S1: I think I am. I think I was naturally a good founder, although I would say I also got really lucky, because I had two great co-founders, and damn, did that I luck out on that. I think I was a very good early stage CEO, and I think the moment I had to have an executive team, I really struggled to make the shift from a founder to CEO. I really struggled. And I think in the 2010s, I do not think I was a great CEO. I think we paid the price for my learning curve. And I think the pandemic was a rude awakening for me. I think I was conflict averse. By the way, somebody once said a pitcher never takes himself off the mound. As a manager, you've got to go take them off the mound. And I was always helping people. I didn't want to hurt people's feelings. I didn't want to take them to take them off the mound. And the longer you leave a pitcher on the mound, the more home runs they give up, the more upset they're getting, and they're still going to be angry at you no matter when you take off the mound. So I don't think I was naturally a good CEO. And I remember up to the pandemic, at one point I wondered if I'm just not meant to be a CEO. Maybe I'm not meant to do it. And then the pandemic happened. We had a near death experience. And I said, well screw all the rumination. It's do or die. And I feel like I learned how to do the job. There's really a few phases of CEO. Have an idea, get to product-market fit, product market fit to hyper growth, hyper growth scale to become a real company – real company as in profitable and public, like, and then the last stage, and I did all that, you know, we have like 40% free cash flow margin. We're very profitable. We do a hundred billion dollars in sales, customer sales. The last phase of a CEO is reinventing the company – product extension. And the reason our stock has been flat is because we only do one thing. And we have started to saturate a little bit of the core idea. So we've had to reinvent ourselves. We've had to do product extension. So I've still got to prove myself. And then there's another proof point. Can I navigate this transformation of AI? I think founder mode is going to be the only way to operate in the age of AI. If you're a giant professional CEO, I think you can operate in a founder mode.