Lenny's Podcast: Product | Career | Growth
00:53:36 · Lenny Rachitsky, Keith Rabois
[00:53:36] S1: And so the implication here is you need to rely on your instincts and gut and experience. [00:53:40] S0: Yeah. I mean, humans are humans. I have this other line I like, which is everything important you need to learn about humans was written by Shakespeare. Just read Shakespeare. That's better than all the customer research. Now you are producing a movie and ultimately, this movie doesn't just need to be critically acclaimed. You have to sell tickets. So if you're not selling tickets, you have to question, "Okay, is the trailer wrong? Is our distribution where we're trying to meet people to let them know about the movie, is that wrong?" Fortunately, unlike a movie, you can go back and say, "Have I casted this somewhat incorrectly? Is the script slightly off," et cetera? But the goal is selling tickets and that's what you want to optimize for. But if you don't sell tickets successfully, economically, efficiently, you definitely want to go back in a loop and try to reorient things so that you are selling tickets. [00:54:38] S1: So this is like CAC LTB kind of stuff is what I'm hearing here. And so your insight here is just, it's not going to help you. You're saying moreso it's actually harmful.
00:54:38 · Lenny Rachitsky, Keith Rabois
[00:54:38] S1: So this is like CAC LTB kind of stuff is what I'm hearing here. And so your insight here is just, it's not going to help you. You're saying moreso it's actually harmful. [00:54:49] S0: It's harmful. And then people will say, "Yeah, I've sat in so many meetings," and this would infuriate me, but where people will be like, "I talked to eight customers, blah, blah, blah, blah, blah, and I know that this isn't statistically represented," but then they pontificate for an hour. And then they're like, "Oh, I know this is not blah, blah, blah." But once you hear this stuff, it's like we can't take this out of your brain. And then every other subsequent meeting is like this stuff is just locked in the customer's brain. So yes, in the enterprise when you have ... I work with a company in AI that has 30 must win accounts. That's the goal for the company over the next few years, make sure all 30, and we're doing really well, get all 30 using our product. Great. We actually can talk to all 30 customers and we can actually meet the decision maker, all 30 customers. And we can influence the CEO at all 30 customers. That is a useful exercise. If you're targeting a billion people on the planet, you are not getting representative feedback. [00:55:46] S1: Being a contrarian take, many people would not believe this as good advice. Do you have a story, maybe an example of just, wow, someone talking to a customer, saying, "We're going in the wrong direction for a while"? Really-
00:56:00 · Keith Rabois
[00:56:00] S0: All the time. They're called failed companies. There's a reason why ... I mean, there's a Darwinistic efficiency to this too, which is just like, "Hey, there are things you can vet. Is it feasible to do X, Y, or Z?" So for example, let's go to DoorDash. I don't think customers told us that, "We want a button on our phone to click to deliver food," but you could talk to restaurants and say, "Hey, would you put this placard here so that people walking into your store know in the future that they can get delivered?" Okay. Yeah, maybe. Then could you run an experiment of how many deliveries per hour would you have to do to breakeven? And is there enough density within this? There are ways to improve the odds that you can make the business work, but I don't think launching the company saying, "Hey, we found 10 people in Palo Alto. Do you want this button on your phone?" So when Tony and Evan walked into my office originally, the epiphany I had was, well, they had a stat, which is 93% of the restaurants in the United States don't deliver. I was like, okay, seems like it should be a higher percentage than seven. Convinced. And then when they were describing what they wanted to create, Andrew Mason of Groupon fame had famously said, "These phones, these devices should have two buttons. I'm bored and I'm hungry." And I was like, "Oh my God, you're the I'm hungry button." And then so it just clicked in my brain and then it was like, okay, now we need to make it economically possible to scalably do this. Good luck, guys.
00:57:38 · Lenny Rachitsky, Keith Rabois
[00:57:38] S1: And this advice is not just consumer. You're also talking like DoorDash has SMB-ish- [00:57:43] S0: Yeah, like Square and things like that. [00:57:45] S1: Square, yeah. [00:57:46] S0: Square is a good example. Anything sub mid-market, I think it's directionally dangerous. [00:57:52] S1: And the advice here is basically trust your insights. You need to have the insight yourself. You can't find it [inaudible 00:57:57]. [00:57:57] S0: I think typically the best companies- [00:57:59] S1: Yeah, interesting. [00:58:00] S0: There's foundational insight. And people don't necessarily want to hear that, but there's logic, you can asset test and pressure test the logic. To some extent, when Brian first pitched me on Airbnb, there was some interesting evidence he already had that this was going to be successful. The number one, the one that stuck with me at the time was he gave me the exact number of Craigslist listings that said, "I want to rent someone's bedroom." And it was actually a reasonable number. It was 30 in the Bay Area. But given that you had to literally type it in and have the epiphany yourself, I was like, "That's a lot actually. That's probably a real market there." And as soon as he said that, I was already leaning in. And by the time he finished his three-minute monologue, I was like, "This is the coolest thing ever. I need to invest." [00:58:57] S1: Yeah. And I think Airbnb was a good example where he was solving his own problem, saw an opportunity. Wasn't talking to people, "Hey, would you do this sort of thing?"
00:58:57 · Lenny Rachitsky, Keith Rabois
[00:58:57] S1: Yeah. And I think Airbnb was a good example where he was solving his own problem, saw an opportunity. Wasn't talking to people, "Hey, would you do this sort of thing?" [00:59:04] S0: And people would've said if he'd sampled the wrong people, definitely would've got feedback that was like, "No, very high risk." That's a good example where you had sampled 10 random people, good chance that nine plus percent would say, "No, I would never do that." [00:59:19] S1: You know what's really interesting? I was just watching Taylor Swift's acceptance speech at this award show, iHeartMedia something or other. And she gave this really powerful speech that when she was starting out, she was just kind of at home working on songs, learning piano, just in a room on her own and had thousands of hours to just iterate and learn and get better. Versus today, if you were to do this, you'd be posting it, sharing it, people giving you feedback constantly. And her advice is just find ways to just not expose yourself to people for a long time.
00:59:19 · Lenny Rachitsky, Keith Rabois
[00:59:19] S1: You know what's really interesting? I was just watching Taylor Swift's acceptance speech at this award show, iHeartMedia something or other. And she gave this really powerful speech that when she was starting out, she was just kind of at home working on songs, learning piano, just in a room on her own and had thousands of hours to just iterate and learn and get better. Versus today, if you were to do this, you'd be posting it, sharing it, people giving you feedback constantly. And her advice is just find ways to just not expose yourself to people for a long time. [00:59:53] S0: So I have a couple of friends who are artists in the music industry, and I think what she's saying is one of the reasons why it's sometimes difficult for artists who had success to recreate the success. Because the first success was not data-driven, was not customer feedback driven. It was like, "I'm creating this and it's resonating." Then because they have an audience, someone, either they or their manager or whoever, the label, blah, blah, blah, blah, blah, wants them to get feedback. And it creates derivative works, not strictly legally, but derivative works, they're less inspired. There's a podcast that Jack Altman did with my friend, Alex, from The Chainsmokers. He actually talks about this at some length that they created this song that actually didn't resonate with their normal audience, but actually resonated with a different audience, which is interesting. So I think you can get trapped with success. It's a good illustration actually.