Name: How Duolingo Rakes in $500M Yearly When 80% of Its Users Don’t Pay | WSJ The Economics Of
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Around 34 million people use the language learning app every single day, some for well over a decade, making the company around $500 million annually and making it one of the top education apps in Apple's App Store for the past decade.

And yet, most people who use Duolingo do not pay.

All of its lessons are completely free to access.

Only around 9% of its users pay, and less than 8% of its revenue comes from advertising.

So how does a free educational app manage to also have a valuation of $7.7 billion?

And is the company's strategy sustainable?

The answer lies in AI, A-B testing, and this little green owl.

If you've ever used Duolingo, you'll have noticed it's less like a traditional language lesson and a lot more like a game.

Get five answers wrong in a day and you'll run out of lives for that day.

Lessons have progress bars and are laid out in a journey.

And streaks encourage users to play every day.

The company says that's part of what helped attract some 3 million users within the first few years.

When we launched, we had a thing that was mobile, free, and fun.

And because of that, very quickly, it overtook all methods to learn languages.

But before long, Duolingo ran into an issue with its mission to try and deliver free language lessons.

One of our board members who had just invested in Duolingo, she said, look, you can't continue doing this.

We had not given ourselves permission to make any money from our app.

It's hard to build up new capabilities in an organization.

We were in a bit of a pickle because we wanted Duolingo to be a free way to learn languages.

So in 2017, the company introduced advertising, which now accounts for under 8% of its revenue.

It also launched a subscription tier where users could pay $10 a month to remove ads and get unlimited lives.

The company went public in the summer of 2021 and saw a boom during the pandemic as users practiced languages while travel was limited.

Today, analysts say Duolingo is around 12 times bigger than its main rival, Babbel, by downloads, with some 8 million users who are now paying for the app.

And while that's only a small fraction of its overall user base, The majority of the money is made from this, you know, under 10% of the active users.

But while Duolingo's growth through gamification and subscriptions may seem pretty simple, there's a lot more going on behind the curtain.

Every move the company makes is meticulously crafted down to the pixel, tested on unknowing users, and refined using AI, rigorous A-B testing, and constant tweaks to its app.

Whenever people are using the app, we measure how long they use it for.

Do they come back the next day, et cetera?

We try, when do we send you a notification?

Do we make them a little easier, a little longer, a little shorter?

If you forget to do your lessons and risk ending your streak, you'll get a little notification from Duo, the company's mascot, reminding you to return to the app.

The messages on the push notifications started out simple enough, but quickly evolved to become the stuff of memes.

Including one particularly effective guilt trip.

We decided that the last notification we would send you was telling you, hey, these notifications don't seem to be working.

We're going to stop sending them for now.

Sending that got people to come back a lot because they felt guilty.

It's like your mother telling you, like, okay, well, I'll stop, like, guilt tripping you.

Duolingo says that this led to a 3% rise in retention.

But crucially, the messages that you receive aren't the same as everybody else's.

AI is used to start figuring out basically, like, which ones of these are more effective for particular users or at particular times of day or whatever, and letting the more effective ones rise to the top and then get sent to more people.

To figure out which messages work best, Duolingo built something called a bandit algorithm, named after a reference to a one-armed bandit, a term for a slot machine in a casino.

Say there are, you know, several different slot machines.

In this case, think of them as several different notifications we might send people.

And we've tried each one some number of times and seen what it paid out each time.

So we have limited information about all these different options.

And so the algorithm has to figure out, do I just go back to the one that has so far given me the most money and just go back to that one every time?

Or how do I balance that with exploring different options to see, maybe they're actually better, but I just got a little unlucky earlier?

And each time we send a notification, we track, did it work?

Basically, did they come back to Duolingo, do their daily practice?

For example, the algorithm found out that the notification, Time for the Language You're Learning, worked better on Chinese learners than English learners.

We must have about 100 different things that we can send you.

They're written by people who are pretty funny, and some of them are also written by AI.

And that could be part of the secret to Duolingo's success.

The company gets so much data back from those attempting its free lessons, that it has a huge database of information that it can feed to its AI algorithms.

They do something like 13 billion exercises every week.

We are throwing all that data to AI and using that to personalise the learning experience for everyone to make sure people are learning effectively and staying engaged.

At any given moment, the company is running hundreds of A-B tests like these, where one user is given a different experience to another to see which one wins out.

Some of the tests are AI-powered, others aren't.

And for most tests, around 5% of its user base act as unknowing guinea pigs.

I don't know how many A-B tests we run at this point.

We've A-B tested our way into getting more people to pay us, into getting more people to use Duolingo, more people to recommend it to their friends, etc.

So without having run those, we would not be a successful company.

So if Duolingo's algorithms and A-B testing mean that the company knows exactly what makes its users tick, why are subscriptions only at 8%?

After all, while the company may have 12 times more downloads than Babbel, analysts say its revenue is only two to three times that of its rival.

We could tomorrow massively increase the fraction of subscribers by doing certain things.

For example, right now you get one ad at the end of a lesson.

We could play five ads at the end of a lesson.

That would get a lot more people to subscribe.

We could maybe even force people to subscribe.

And it is true, we would have an amazing next quarter.

However, that would also stifle our growth.

But analysts say that while Duolingo's leading market position may have been achieved by giving away much of its lessons for free, that growth strategy may start to slow, especially as some users leave the app after mastering a language or giving up on it.

And that may lead to Duolingo trying to increase the number of paying customers.

So the company is exploring some new ways to get users to part with their cash.

Its new AI-powered Duolingo Max tier costs around $30 a month and allows players to roleplay with AI-powered bots, something the company had previously tried to offer with humans.

We would say, okay, so you're telling me that if you could on Duolingo, press a button and you could have another human on the other side, be able to practice, you would use it?

And then came the very revealing question.

We'd say, okay, do you want to do it right now?

A hundred percent of people would say, no, no, no, not right now.

What I love about AI is that people don't feel like the AI is judging them.

Even though it actually is judging them, but who cares, right?

 But for now, at least, Duolingo says it will continue giving away most of its product for free.