Duolingo, Inc. (DUOL) Earnings Call Transcript & Summary

All right. So welcome, everyone. Let's get started. I'm Ron Josey. I lead Internet coverage here at Citi. And I am thrilled, psyched, excited to have with us today, Luis von Ahn, the Co-Founder and CEO of Duolingo. So Luis, thanks for being here.

Thank you for having me.

Duolingo is one of the, in my mind, most recognized consumer learning fun platforms out there. There's a lot going on. And so maybe we'll get started. And first of all, thanks for coming. So excited to see you. Thanks for being here.

I think most people know Duolingo, so we can sort of just jump into it. Maybe I'll start with some icebreakers. Just to tighten the mood, if you will. And the first one to lighten the mood is when I give you this one number or word like what's the first thing that comes to mind, 100 million.

That's the number of DAUs we want to get to in 2028.

Okay. That's the first thing that comes to mind.

That's it. That's our goal.

Chess.

Love it.

Okay. AI is like?

Exciting for Duolingo, scary for me personally because I don't know what's going to happen.

Okay. Green Machine, the name came from how -- where did the name come from? Green Machine?

Green Machine is our process of optimization at Duolingo, and it came from my Chief of Staff, Molly Brean. She invented it.

Yes. There was a -- I think there was a big wheel back in the day called The Green Machine as well. Okay. And maybe the last one, more fun, but Duo is so lovable, but at the same time, it's so demanding. So when you think about the character of Duo, what's your first -- when I say Duo, what do you think?

Well, Duo has a mind of his own, and he just wants you to do your lesson. That's all he wants in life. And so when you don't do your lesson, he will freak up. So that's it.

Yes. Well, he freaks out on me too often.

You got to do your lesson.

I need to do my lessons is sort of how it goes. I was debating whether to do this all in Spanish, but we'll stick to English for now. So we'll go through some questions. And of course, we'll open it up for -- from the audience for questions as well. So let's just kick off here specifically. And so it's been 8 to 9 months in sort of a strategy reset, if you will, around prioritizing engagement and user growth in '26 before we get back to sort of the monetization. Just take us back to late last year. I know we've talked to this a lot already, but take us back to late last year when you all were going through this idea of let's drive engagement. And walk us through sort of why do we do it? And then more specifically, we're now 8 to 9 months in. And so what are you seeing in the business that has made this sort of like the right approach thus far?

Yes. So yes, about a year ago, we had, I don't know how many quarters, something like 16 quarters or something of incredible revenue growth. Just every quarter was just we were growing quite a bit for a long time. And it was doing well. But one of the things that happened is we are an incredible optimization company. We optimize for things. And it was -- it had become clear to me that we were spending most of our time optimizing for revenue, which I thought was shortsighted. And what I thought the real thing we should be optimizing for is audience size, especially because we are at a unique time where because of AI, we really are going to be able to teach much better over the next few years. And I think there's a real opportunity of capturing an even larger audience than we originally thought. So I made the decision, which was not an easy decision to mainly concentrate on growing our user base, our active user base. And so that's what we've been doing for the last few months. It's going really well where our year-over-year DAU growth rate is very good. We're very happy with it. And so we've been able to reaccelerate our growth rate, and we feel quite good about our ability to get there. I mean, right now, whatever the latest -- I don't remember the exact number that we said for the latest DAU numbers. I know the DAU numbers from yesterday, but I don't think I can tell you that.

I think we know them at some point in August.

Yes. We know them at some point in August. But in any case, we feel pretty good about getting to 100 million in 2028. It's looking really good. And the really good thing about our DAU growth rate is that it's really all regions are growing very healthily. And so -- and ultimately, the larger the audience that we have, the more people are learning on Duolingo, the more they'll tell their friends, so we keep growing. But also the larger the audience we have, the more revenue we'll ultimately be able to make. So I think this is just going to be a much larger business than we originally thought.

Luis, that was super helpful and insightful. And in that, I think you said we want to teach better in the next few years or something along those lines. Talk to me about dive deeper into that teach better over the next few years because the product works great. Duo brings me in, maybe not every day because he gets mad at me. But just talk to me what do you mean by teach better or give us any examples to help us understand what that means?

Yes. So a couple of things about teaching. First of all, one of the things that we learned a long time ago was the hardest thing about learning something by yourself is staying motivated. That if you're going to learn something by yourself, it's different than learning something in school. Learning something in school, you kind of have to go to school because your parents are forcing you. It's just -- you kind of have to go. If you're going to learn something by yourself, especially on a phone, it's pretty hard to stay motivated because you are one tap away from going to TikTok or whatever it is. So the main thing that we have concentrated on for many, many years is getting people to stick around and stay motivated. And we have done a really good job. If you, for example, look at our DAU of our MAU ratio, it's incredibly high. It's better than most games actually. So we've done a really good job of getting people motivated. Now the other thing, of course, we have to do is make sure that we are actively teaching you as well as we can. We did a study a few years ago, and Duolingo was about as good -- I felt a few years ago, Duolingo was about as good as a classroom. And we felt really good that Duolingo was about as good as a classroom. Now it just turns out that the reason that was the case is because classrooms, particularly for languages, are just not particularly that good. So we were about as good as a classroom a few years ago, and we're like we feel great, but it's like it turns out classrooms are just not that great. What's really good about learning at actually teaching a language is a one-on-one human tutor. By the way, this is true for most subjects. If you want to learn something really well, getting a one-on-one human tutor is usually the most efficient best way to...

Converse yourself.

And with the tutor, like it actually works really well. We are not yet as good as a one-on-one human tutor. But every year, we get better at teaching. If you just -- we do measurements about how well we teach. And my sense is that in the next -- I don't know the exact time line, but in the next, call it, 2 to 3 years, and again, I could be off on this, but in the next, call it, 2 to 3 years, I think we will be as good as a one-on-one tutor in terms of learning outcomes. And I think that's incredible for a couple of reasons. First, we're going to be way cheaper than one-on-one human tutor. I mean one of the problems with one-on-one human tutors is they're quite expensive. If you want a good one. This -- we're talking $100 an hour easily if you want a good one. So we're way cheaper than that. But secondly, most importantly, the problem that one-on-one human tutors have is that for most people, they're very boring. So they just don't do it, whereas we are going to be as effective as a one-on-one tutor, but it will feel as fun as a game. So I think that's a real game changer in terms of -- it really will be kind of a no-brainer to use Duolingo to learn certainly, languages, which is where we're most advanced. But I think we're going to get there as well with chess and with math in terms of teaching as well as one-on-one human tutor in the next few years. And I think that will be a real game changer.

So within Green Machine, and I'd love to have any insights on just the data on the path to that 2 to 3 years we get to that one-on-one tutor. Any insights or maybe aha moments on the product that you've seen that says, ah, this is something that will bring people coming back and get those streaks going. Anything in there like...

For coming back, yes. I mean it is an incredible thing when you look at the behavioral tricks, I'll call them, that get people to come back because we have data from so many users, I mean, really literally millions of users every hour using Duolingo. We have data from that, and we use that to get people to come back. And there's just some pretty amazing things. So for example, it really matters what you say in the notification to get people to come back. This is why the owl, for example, has a personality. It turns out that the awl being disappointed in you really works well. I'll be motivated, yes. Well, it really works well. And by the way, how well that works depends on the culture. In certain countries, disappointment works a lot better than in other countries. So this is all the stuff that our AI finds out or either AI or our team just we find out that in certain geographies, certain types of motivations are better than others. Another really good example is the -- if you start a lesson on Duolingo, the progress bar is actually not linear. It's in fact, what happens is the first few exercises you do, it grows a lot. So very quickly, you get to halfway. And the thing about getting to halfway is that humans just have an instinctive need to fill a half filled progress bar fully. So we just get you very quickly halfway and then you're like, well, may as well finish the lesson because I'm halfway. Now you're actually not halfway. We lie to you. You're actually just, I don't know, 20% of the way, but you feel like you're halfway so you may as well finish. So there's just -- there are thousands of these little tricks to try to get people to come back. Because ultimately, what we're doing is we're doing something that you say you want to do, but that ultimately, you don't really have the self-discipline to do. So we're trying to just give you that self-discipline. I mean it's kind of similar to we're just helping you to go to the gym or we're just helping you to do the thing. So we're helping you to stay to be good for yourself long term.

Yes, I would agree with that. And you're building a lifelong skill upon doing it. So I am certainly guilty of the halfway, let's finish it up. So that's -- I try to go faster on the Spanish ones because that's easy for me. But anyway, let's maybe talk a little bit more just on that 100 million path and bring it back into 2Q. Specifically, I think you said we talked about DAU growth is accelerating. I would love to talk a little bit more about what are the drivers of that accelerating growth. And the question we get is the drivers and the durability. How do you continue and I'm not asking about it I would love to -- but how do you just -- what were the product changes that sort of got to this level of accelerating growth that you laid out last year when you said we need to get to this metric?

Yes. I mean -- so when people ask us, is this durable? I mean the answer is an easy yes because these are not one-off things or anything. These are just simply the product is stickier. We have done a number of changes. By the way, in terms of the acceleration, the majority of the reason why we've accelerated and why we're beating our own internal forecast in terms of DAU growth is because the product is stickier. So we've just done an incredible job in terms of running tests that make the product stickier. We -- every single week, we run hundreds of A/B tests to try to make the product stickier. Now some of them don't work, some of them work, about half of them work. It's hard to attribute to a single thing that why we're stickier, but it's just little things about like we tune the time in which we're going to send a notification. We change the animation of when you get a streak, how explosive it looks. So it's all this stuff that we do, and it just becomes stickier and stickier. At this point, we had it in our last shareholder letter. This metric that we look at internally is called current user retention rate, which is basically if you are here today and you are here another day in the last 7 days, what is the probability you'll come back tomorrow. That number for us now is 84%, which is extremely high. And it's at an all-time high. It keeps growing. It grew by about a percentage point in the last year. And it's because the product is just stickier. So that's probably the biggest reason. There's another reason that is less impactful, but another important reason is our marketing has done an incredible pivot over the last year. I think, hopefully, a lot of people are familiar with our marketing. It's pretty unhinged if you go to our TikTok or Instagram, like our social media has been pretty unhinged. And it has really worked very well. But over the last year, we've done a pretty incredible pivot where it remains unhinged, but it's a lot more brand aligned to kind of efficacy and teaching well, et cetera. So we're just seeing that the marketing is doing better than it was about a year ago. And in addition to that, we've diversified our marketing. It used to be the case that the main thing that we only looked at was we just had a really popular YouTube, TikTok and Instagram channels. We now have diversified. It's not just our own channels. We have thousands of user-generated content that is helping like other people talking about us, that's helped quite a bit. And in addition to that, we've started doing some performance marketing. It's not a huge amount, but we've just gotten much better at performance marketing. And I think the combination of this just makes our marketing more effective. And so that's why we're accelerating.

Yes. Super helpful. One of the things that I wanted to ask a little bit more is I think the comment was you run hundreds of A/B tests, and we'll see what works, maybe it's a 50-50. Talk to us a little bit more just the internal process to run those tests. So specifically, I was a product manager a long, long time ago at an old company called AOL. And we would.

I was the user, what's the year?

Most people were [ back and ] they're dead. And now everyone knows how old I am. But we used to very much manage every single release. And then, of course, you just measure everything. And so talk to us more about the hundreds of A/B tests. I'd love to hear about how that has maybe ramped up over time. And how do you manage that process? AI, I'm assuming, has really helped to understand what's coming through.

Yes. I mean, so we have -- there's a new version of Duolingo every single week. So our iPhone app and our Android app. Every single week, there's a new version of Duolingo. That version of Duolingo, every time it comes out, comes out with some large number of new A/B tests, hundreds that we're testing. The way this works is we have -- there's 3 big things we work on Duolingo. One is user growth, another one is revenue and another one is teaching better, whatever the subject that we're teaching. So all A/B tests are based on one of these. So they're trying to do one of these things, either it's meant to teach you better or it's meant to keep you more engaged with the product or it's meant to make more money. There's large -- each of the teams that own one of these is about 100 people. So it's about 100 people working on Duolingo that are either engineers or designers or product managers that are working on teaching better and about 100 that are working on monetization, et cetera. And the way it works is the combination of these 100 people, one of them comes up with an idea for an A/B test. Of late, it's either the 100 people or AI also comes up with ideas for A/B tests. Then we sketch it. It gets reviewed by a group of people in the company that reviews all changes to see if this is a good change that we're going to do or not. Then it gets built. These days, it's mostly built by AI, and then it goes into the product. From idea to product, it's about a month that it takes from idea to product. And then we run it and literally about 50% of them are successful in whatever the metric they were trying to improve. So either it improves revenue or improves how we teach or it improves daily active users. That's kind of what happens. But the velocity that we're getting A/B tests out is very high. By the way, the number of A/B tests that we run per capita, so per employee of Duolingo that is working on the product has significantly improved over the last few months. And that's a lot thanks to AI, not entirely, but a lot thanks to AI. It's not quite doubled in the last few months, but it has -- it's close to doubled in the last few months.

And I think we saw that in 2Q with The Green Machine testing optimization came through. And also in 2Q, you benefited from maybe not test, but events, streak revival being one of them, I think, video calling now available in Super Duolingo. Was that part of the testing as well? Or that was the idea and it just sort of stuck? And I had one more question on The Green Machine, then we'll move on.

The streak revival was just an idea that one of our product managers had. Oh, maybe we can -- there's a lot of people who have lost their streak. Maybe we can have a onetime event where we let them revive their street. It was very popular. We had about 15 million people revive their street worldwide. That helped for sure. But that was a minority. It sounds like a really big event. But in terms of when we do the actual calculations of how much this helps with DAUs, it helped, but it was a minority. The majority was just long-lasting changes.

Got it. When we think -- now we'll take a step back, I guess, and talk bigger picture. And I know this year is not the year we're maximizing monetization, but it's helpful to hear those 3 sort of buckets, if you will, between user growth, revenue and teaching better. Talk to us about how you think you balance those 3? Or maybe I get the question all the time, how do we get back to revenue growth, right, if we're optimizing user growth and -- I guess, user and teaching growth here in the short term?

I guess that question only from Wall Street. So let's see. This year, our goal really has been -- from the beginning of the year, we decided we were going to set some financial kind of box or financial boundaries that we're going to say, look, this year, we're going to grow whatever we said at the beginning of the year, bookings by something like 10% or something that we said something. And we're going to operate like this with this year, we're going to have adjusted EBITDA in this range, et cetera. And subject to that, we're going to try everything we can to try to increase our audience size. So that's how we're operating this year, and that's what we've been doing. I mean, in fact, every quarter, you've seen we're within the box and trying to accelerate our user growth. And I think it's been very successful in accelerating user growth. In terms of kind of monetization, we're not giving any actual guidance for next year or anything. But what I will say is that we'll probably have not just be concentrating on user growth next year. I think that's safe to say that we understand -- obviously, this is a business, and we understand that the ultimate goal is really revenue, but we really thought that this year, we should spend it on user growth.