Pinterest, Inc. (PINS) Earnings Call Transcript & Summary

Interest of time and for the webcast, we're going to get going. It's my privilege to kick off our first fireside chat of day 2 with Bill Ready, the CEO of Pinterest. I'm going to read a quick safe harbor, and then we're going to get into this. Some of the statements that Pinterest will make today may be considered forward-looking. These statements involve a number of risks and uncertainties that could cause actual results to differ materially. Any forward-looking statements that Pinterest makes are based on assumptions as of today, and Pinterest undertakes no obligation to update them. Please refer to Pinterest's latest Form 10-Q and Form 10-K for a discussion of the risk factors that may affect its results. Okay. Bill, thanks so much for being part of the conference this year.

Thanks...

It's always great to have a chance to talk to you. It's been a few years now since you've joined Pinterest as the CEO. I think the anchoring theme I always consistently hear from you is about making Pinterest as a platform more actionable. Can you talk about the journey you've been on measured against that goal from when you came into the company?

Yes, absolutely. I mean the headlines is like Pinterest has become an AI-driven shopping assistant for 640 million-plus users, becoming one of the fastest-growing platforms in social media, consistent double-digit growth in users, strong engagement growth. And at the core of that has been the actionability that you just mentioned. Coming into Pinterest 4 years ago, it was pretty much a platform for visual discovery and browsing, but it wasn't a place to buy things. And it's now the case that more than half the users that come to our platform are there to shop. Gen Z is the largest, fastest-growing cohort, more than half our users and primary use case is shopping. And at the core of that is making so that you can discover more of what you're looking for, make more of those purchases. And that has been at the core of the revitalization of the platform, both in terms of the user side of it, where we're getting much deeper engagement, particularly with those Gen Z users. Stated simply, Pinterest is where Gen Z goes to shop. And it's a place where they're thinking of as a first place to go search increasingly as well. So there's an Adobe study that we've cited previously that 39% of Gen Z thinks of Pinterest as the first place to go search. Why? 71% of Gen Z sees Pinterest as more personalized than other places to go search. So at the core of it is it's not just us using AI, it's us using really unique data that we get around the human curation on our platform. So AI doesn't have style and taste on its own, humans do, but that's what people do on our platform is curate that style and taste, and we've used AI to go really superpower our recommendations to users, giving them great recommendations before they even know what they're looking for, that users will say, "Oh my gosh, Pinterest just gets me," and increasingly make it so that they can shop and buy. And that's why now you see that from a platform that was almost entirely upper funnel ads 4 years ago, we've talked consistently about 2/3 plus of the business is lower funnel performance. We talked about more than 5x the number of clicks to advertisers over the last 3 years. Those things all get to like the deep actionability on the platform. And so we've had great progress there. At the same time, in the course of like monetizing a platform like this, we're still relatively early on. There's still a lot more opportunities. So one of the strongest parts of the story has been our growth in user engagement. And then the monetization, I talked about the shift to lower funnel. We've made great progress on that, especially in our home market here in the U.S. But then international, where we have more than 80% of our users, still roughly 20% of our monetization. So a lot more of that to go there. So when I sort of look at the progress, we've clearly proven out Pinterest as a shopping destination, clearly proven out we can make it actionable, clearly proven out that we have differentiated signal to train the AI on to give fantastic recommendations to users so they want to come back and shop more. That's a global phenomenon. And then the monetization always follows in behind the user behavior. And so we've made great progress in the U.S. We're translating more of that international, but there's a lot more of that to do.

Okay. Building on that answer about your future vision for the company, we got the news in the last week of Julia's departure from the CFO role. Can you talk to us when measured against where you want the platform to go, what you'll be looking for in a new CFO?

Yes, certainly. So having built from zero to many billions multiple times, these things are like relay races, right? When you think about sort of what's the team and the things you need to do for each leg of the race. And I sort of touched on this a little bit in the last comment of like what were the things that we needed to address. And 4 years ago, this is basically a single product platform in a single geography. And we're now moving into multiple products, much more -- many more geographies, much greater complexity. And we've been building up a team for that leg of the race. And so if you look at what we've been doing more recently across the team, started with a new Chief Product and Technology Officer that led shopping at Google, is doing a fantastic job with what we're doing with the tech platform, bringing in a great team there, recently a new Head of Product Engineering for ads, new Head of Infrastructure, that new head of sort of the internationalization of the platform on the product side, new Chief Business Officer, new Chief Marketing Officer. And so we're really building up the team for where we need to go next. And so similarly for the CFO, when I think about that, we have now proven out that we can monetize our audience beyond just one surface. We did the acquisition of tvScientific. We've got multiple products within Pinterest, now monetizing beyond the one surface, going into many more geographies. So when you look at that complexity of the next leg of the race, we've been building a team around that. And these are things that we'll be solving for with our next CFO and that we'll want a deep operational partner. Grateful to Julia, she ran her leg of the race well, a very good partner through that. I'm sure she'll be great in the next thing that she goes and does. But if you look at where we were 4 years ago, there's a lot of what we were doing was sort of addressing a lot of things that ideally probably should have been done before the company was public. And so we were really getting a lot of that operational rigor and hygiene. And now we're in this place of expanding to more products, more geos that brings greater complexity. So we'll look for another great operational partner, but one that has done a lot of that kind of operational complexity at scale and across the rest of the team, that's what we've been building for. And we're seeing really great talent, really great candidates for our CFO search. So I'm quite confident that we'll get a really exceptional person in that role that will be a great partner for the next leg of the race.

Okay. There's so many themes of convergence that we've been talking about over the last 12, 18 months, search, social media, commerce, AI. When you think about the broader discovery process that consumers are going on right now against those themes of convergence, how do you think about positioning Pinterest against consumer discovery over the medium to long term?

Yes. Well, I touched on this a little bit but we've made tremendous progress. I think it's been the strongest part of our story is the, and it's a big change in the story. 4 years ago, Pinterest was a platform that was rapidly declining in users, had missed the next generation. Now to a platform of 12 straight quarters of record high users. Gen Z is more than half the platform, our largest, fastest-growing audience. We've talked about many times how we're growing across every geography that we track, across the generations that we track. And so it's broad-based. And so at the core of that is people are thinking about different ways to engage in their shopping experiences than what they did previously. I said this before that the first 25 years of e-commerce in a lot of ways sort of solved buying but killed shopping. And the distinction being that if you knew what you wanted and then you wanted to get the cheapest and the fastest, there are a lot of things built for helping you do that. But a lot of the rest of the shopping journey was about, well, I don't know what I want to buy yet. It's the sort of I'll know it when I see a problem. And if you think about how people shop in the real world, that's a lot of it, that whether they want to update the wardrobe for fall or they're thinking about what to make for dinner that night, they'll go into a shopping setting with a sort of loose idea, but if you ask them like, "Hey, tell me exactly what it is you want to buy," they say, "No, I know when I see it." And that's what Pinterest is solving. But we're solving it now in a way that is going from that upper funnel discovery all the way to basically sort of dream, decide and do. So like what's that initial kernel of the idea? How do I refine that? How do I make a decision and then how do I easily take action on that? And we're solving across all of those. And a thing I'll share one of the questions that we'll often get, especially on the strength of our Gen Z usage. And it's funny, I used to get this question all the time in the early days of Venmo where people say, are these millennials ever going to like spend money? And it's like, of course, they're going to graduate college, and they're going to spend money in like all of these things. And then we get that question about Gen Z, a lot of like, well, can you monetize those users? And with Gen Z, not only are they our largest, fastest-growing demographic, more than half the platform, they have the deepest engagement, the highest retention. They're also the most AI native. So they're building AI native capabilities, things like that. They are deeply versed in those things, like so our assistant capabilities we put out there, deeply versed in those things. But Gen Z on our platform, we now see the ARPU of our Gen Z users in the U.S. is roughly consistent with the ARPU of our older generations like millennials. And so I think that bodes really well for the future monetization of those Gen Z users that, of course, they're going to shop. They are shopping. They're shopping quite a bit, which is why their ARPU is now consistent with the next generation up with millennials. And I think that bodes really well for the future monetization of our platform because the purchasing power of those Gen Z users is only going to increase, and they see Pinterest as a place for them. Again, Pinterest is where Gen Z goes to shop. And so we see that, even as their purchasing power is early in its growth, they've already equaled the ARPU of millennials on our platform. So we hadn't shared that previously, but that's what we're seeing on the platform. It's exactly what I would have expected having built commerce experiences previously as these generations mature, but the depth of the engagement with our Gen Z users is just quite significant and it outpaces the other generations on our platform.

Okay. Understood. You spent some time on the Q2 earnings call talking about your approach to AI as a company. Against the landscape of what's available to you, models, products, things you can bring into your ecosystem. Talk to us a little bit about your AI strategy, both in terms of what you can pull into your ecosystem from the AI landscape and then how you can take elements of your data and build personalized unique experiences at Pinterest in a cost-efficient manner.

Yes. So this is, from the time I came over from Google, I spoke most consistently that in this coming wave of AI, the sort of model capabilities will be available to many, but then there's going to be a lot of opportunity for places that had unique data that AI thrives on feedback loops. So what are the places that had unique data, unique user feedback loops. And for Pinterest, I talked about how we're using that unique human curation on our platform to train our AI to give really, really distinct recommendations. That's at the core of the reacceleration of the platform that basically everything you see on Pinterest is served by AI and has been for a couple of years. That's one of the first things I said about doing coming into Pinterest. But we use a combination of compact fit-for-purpose models and taking open-source, open-weight models and post-training on our data to really great effect. And we've been talking about this for years. Now there's a lot of discussion of open-source, open-weight. We are very early on that. There's a lot of discussion like model routing. We are very early on that. There's a lot of talk about, oh, well, maybe you don't need the frontier for every task. Maybe that is oversolving a problem at much too great an expense. Well, check the tape, like we've been on this for several years. And it's part of why even as we have made it so that everything you see on Pinterest is served by AI, we've also had significant expansion of margins in our business over that period of time because we have been able to not only align those AI use cases with highly monetizable events that are very, very commercial. It's also the case that we've been able to do it at very, very good cost effectiveness, and that's because we use compact models trained on our unique data. We get great results from post-training open-source, open-weight. And I think that's a really important thing as you look forward that in the initial sort of wave of adoption, sort of everybody is just racing to make sure they didn't miss out and particularly less sophisticated companies like that, which is like just give me whatever I can adopt. And as you now see token bills coming in and things like that, people are thinking a lot more about, I probably should think about the right tool for the job. And like using the frontier for everything, it might be a little bit like using a Formula 1 engine to like mow your lawn. You may have like not only massively overpaid, you may not have solved the problem as well as something that was built fit for purpose for the thing that you're trying to do. And I think one of the most exciting things that has happened in the industry is the advancement of open-source and open-weight. I said on our last earnings call that, and I'll say it again because I think it's really important. A CEO that's not heavily leveraging open-source, open-weight models is almost certainly wasting a lot of shareholder money because you can get similar capabilities at dramatically lower cost. For us, we shared that when we use open-source, open-weight compared to a comparable sized model, we are able to get cost at less than 8% of what the comparable closed models would be. But we also see greater effectiveness because you can't train the closed models on your own data. So when you can train on your own data, that's greater effectiveness. And it's actually greater safety as well because you can run it in your own secure environment, which you can't do with the closed models. And so you know where your data is going with the open-weight models when you're running in your own environment. And not only do you have a very good thriving open-source, open-weight ecosystem now, including here in the U.S. with U.S.-based models, you have the hyperscalers leaning in and doing what they've always done. If you look at how important open-source software was over the last 30 years, a big part of that was that hyperscalers came and sort of packaged up open-source to make it easy for others to use like most of the Internet runs on Linux. Well, Linux, most people would have thought it like sort of harder to use earlier on, but then you had hyperscalers sort of package that up and make it really easy for others to consume. And the same thing is happening with models now that you have these open-source, open-weight models that are just only a few months behind on any comparable size, tend to be only a few months behind the frontier. And then you can post-train on your data, get better results, much lower cost and now much easier and safer to do because you can do it in your own environment, whatever hyperscaler you use, you can do it in the environment where your data already exists, your data is secure, it's not going out someplace else. And so I think that's a really important trend. And it's a good thing for the thriving of the overall ecosystem just as open-source was. Most of the companies in the valley wouldn't exist if not for open-source software. And so I think that just says that this sort of world-changing technology will be in the hands of the many rather than the few. The innovation will be for the many rather than a few because of what's happening with open-source and open-weight and having chip makers like NVIDIA really behind that, having hyperscalers behind that. I think just says like there's clearly a good ecosystem there. And it's what we've been doing for several years now, saying like right tool for the right task gets you better effectiveness, better cost and you can do it safely and securely. And so I think that's a really, really good thing for the broader tech ecosystem.