Brian Tolkin, Head of Product @Opendoor: How to Hire the Best Product Teams | E1257

What was the single best product decision you made?

Upfront pricing for UberPool. When we first launched, it was variable pricing depending on whether you matched or not. You opened the Uber app, you say, "This is where I'm going," and, and it was just like, "Okay." And then based on minutes and miles, it, the cost would post how to calculate, and so we built upfront pricing where you'd see that beforehand.

Ready to go? (instrumental music plays) Brian, dude, I am so excited for this. I've wanted to make this happen for a while, so thank you so much for joining me today.

Thank you for having me. I'm, I'm super excited as well. This'll be great.

Dude, I spoke to so many people that worked with you at Uber, and I heard that you were instrumental in the China Pool Uber launch, which allowed Uber to compete directly with Didi in major cities. This is what everyone told me.

Yeah.

What are your biggest lessons from that time and launching China Pool so efficiently?

We were launching in China. At the same time, we were standing up a Chinese, uh, uh, a data center in China, and there was all sorts of technical issues with the day before launch getting everything to work properly. And we were launching for, uh, in Chengdu, um, uh, which is a city in China, um, that... By the way, a city of, like, 20 million people that most people at Uber had never heard of. And we were launching for, for rush hour 'cause the product re- relies heavily on liquidity to, to make efficient matches and, um, all that stuff. And so, uh, it, it wasn't working and it was, you know, 9:00 PM, 10:00 PM, 11:00 PM, uh, midnight, 1:00 AM. I think I s- slept 30 minutes on the floor of the Chengdu Uber office. Launched at, like, 5:30 or maybe 6:00 AM, um, and, uh, knock on wood, we were able to figure it out and, and it, and it sort of worked.

What are your biggest product lessons-

Yeah.

... from doing that launch-

Yeah.

... and from that time with Uber in China?

My biggest product lessons are (laughs) , uh, one, um, underlying data, like understanding the components that make your work, that make a product work really, really matter. So in our case, um, we are trying to do matches, um, between two riders for, for UberPool. The thing that works, the thing that customers care about is, uh, the quality of the match and the price of the ride. The thing that drivers care about is also somewhat, uh, the quality of the match. Um, and those things depend on having really good mapping and routing data. And the reality is, in China, there's no Google Maps. It's much more difficult to have, have, uh, routing and mapping data. And so we had to work really, really hard, uh, to try and figure out how we can make good matches work, and the reality is when we first launched, there, there weren't that good, that good of matches, and the road infrastructure in, in China is very, very challenging. You have massive highways and overpasses and, like, all this complexity that, that, um, is just a little bit simpler in, in, in places like the US. And I think we underappreciated the complexity of, um, how you would make good matches without awesome underlying road data.