Invest Like the Best with Patrick O'Shaughnessy
· Gokul Rajaram
[00:00:00] S1: Consumer behavior change, where they don't open up the apps anymore, but they use agentic interfaces. They use AI interfaces, which are not owned by my company or this company, to do their transactions. If you assume that a big percentage of things are repeat, then could you put those repeat things on autopilot through an agent and you never open the app? And so you lose opportunities to then advertise. And you lose the relation with the customer over time because the customers are trusting the AI agent. You can't bury your head in the sand. You have to go and experiment. That's why when ChatGPT opened up their apps platform, all of the commerce platforms are experimenting. And the thing I would look for very carefully is, there are going to be early adopters in the app. Obviously, they're going to connect their Uber account with their ChatGPT account. I'm going to look to see these people who have connected. How's their behavior on my app? Are they going to my app or not? Are they opening the app much less frequently? Because if that's the case, then obviously this experience is so compelling that I would then have a choice to make. How do I make this experience maybe not as compelling as my app experience, or how do I incentivize them here to open up my app?
· Patrick O'Shaughnessy
[00:00:00] S0: There's a new battle happening for that first category, which is a new interface to be owned. We know ChatGPT does – I'm curious, if you think being the first mover matters to build a new ad network because there's Gemini, there's Anthropic, there's a bunch of people that have tons of users using this new interface. How do you think about the landscape of the new potential entrants to build the next dominant ad network? What advice would you give these various parties?
· Gokul Rajaram
[00:00:00] S1: The good news is being first doesn't matter because especially if you're in category one, which we described, you control your first party inventory. In fact, being second or third, you can learn from the iterations and mistakes that the first one makes. Your inventory is not going anywhere. Now, some might have more urgency to monetize than others, but Gemini doesn't need to monetize anytime soon. So they can just sit back. They have a lot of ads expertise and data from Google. They can sit back and wait till they need to monetize. In fact, a good strategic move for them might be to say, "I'm the zero ad platform." Google can claim that Gemini has no ads in it. And there is a certain set of customers or consumers who care about that. The biggest thing is, and OpenAI has done a good job of articulating this, ads should not influence the content that is served to me, or the recommendations that AI gives to me. I think they should be relevant, but they should not be influencing the recommendations. And second, you have to keep a high bar for engagement and usefulness. Unfortunately, however relevant ads are, the reality is – and this has been proven – is that once you start showing ads in a previously unmonetized zero ads surface, engagement of users goes down over time. Because some of the engagement gets siphoned off by ads, and some of it gets siphoned off in different ways. But there's many holdout groups across many companies that have proven this. So the question for any one of these companies is, how much engagement are we willing to take in exchange for monetization? First, you need to have a holdout group of people who never ever see any ads, because that's your fresh group that never sees ads. And you need to understand that's their behavior. And then you need to always understand how people with ads are behaving. And then you need to figure out what the engagement hit is from each quantum of ads. And you need to then give your ads team a certain engagement budget. So that's what, at Facebook, there was an engagement budget every year that between the News Feed team and the ads team, we had to adhere to. In other words, yes, we wanted this much revenue, but the check metric on the revenue was, we can't take more than X percent dip in engagement overall for News Feed.
· Patrick O'Shaughnessy
[00:00:00] S0: Picking that well, you've talked about like a North Star metric. What are the attributes of a good North Star metric? What advice would you give someone that's trying to pick the thing around which the company is going to optimize?
· Gokul Rajaram
[00:00:00] S1: The North Star metric is a metric that is an indicator of company growth and customer value. So it actually balances customer value and business value nicely. North Star metrics, in my opinion, should not be revenue. It should be something that is directly correlated to customer value. So for example, if customers are doing well, the North Star metric should go up and to the right, but it should also lead the business doing well. For example, for Square, the North Star metric was GPV, which is volume of payments processed. It was not correlated to revenue – it was somewhat correlated to revenue, but it most importantly showed that the amount of payments processed to the company was continuing to grow. At Facebook, the North Star metric was DAU. It was actually monthly active users, then it over time went to daily active users because it was an indication of how engaged users were. Now, one of the most important things about an NSM is that it needs to be coupled with what we call check metrics. In other words, incentives drive behavior. So if you tell a team, go and optimize this North Star metric, it is going to go up, 100%. But then many things that you don't want to go down, could go down. So for example, in the DoorDash case, you could say, "I want to grow GMV", which is the gross merchandising value, which is the North Star metric. Now, GMV is the total order of total value of all the orders that go to the marketplace. I could make it grow up by setting delivery fee to zero, by setting everything to zero. And what happens then? The company's revenue goes to zero. So you basically want a check metric around the health of the customer and a check metric around the health of the company. Those are the guardrails around this North Star metric. So in the case of DoorDash, it might be I want to maintain a certain gross margin percentage, or I want to maintain a certain customer retention percentage. Margin is typically a good one to use because in some ways, that is an indicator of the company health.
· Patrick O'Shaughnessy
[00:00:00] S0: There's these two ideas that we talked about when we first met. One was the need for the very best software companies to stand alone, in the sense that someone can just go use it without talking to a human and it just works for their problem. So like fully, fully self-serve. So I'd love to hear you talk about that. And a related idea was – that’s sort of on the builder side – on the investor side, you mentioned to me that all the great investments that you've had – the companies that have really had explosive growth – have had a high number of one of four qualities, which is, I think was gross margins, low cost to acquire the customer, high retention, and a tight sales cycle, which maybe maps back onto the self-serve thing. Talk about the relationship between those two things.