Duolingo: come hanno fatto a migliorare il loro prodotto e a diventare l'app educativa #1

Duolingo’s mission: making language education personalized, fun and universally accessible

Faced by the inequalities of traditional education, especially in his hometown of Guatemala city, Duolingo’s co-founder Luis von Ahn, felt like something needed a change. 🧐

He figured that, particularly in poorer countries, education was broken. People who have money can get top education, while people who don’t have money barely know how to read and write. And because of that, don’t make any money. A vicious circle. 😔

Luis saw there was language learning software out there, like Rosetta Stone, but it was prohibitively expensive, and it therefore didn’t help to close the education gap.

That’s when Duolingo was born, promising free language learning to everyone. Accessible to everyone who wants to learn. ✨

Sulla base della sua missione, Duolingo ha attirato da allora utenti, dipendenti e investitori.

Naturalmente, per sopravvivere, Duolingo ha dovuto fare soldi in qualche modo. La scelta si basa su annunci, abbonamenti mensili che rimuovono gli annunci, acquisti in-app e il Duolingo English Test.

And besides making it universally accessible, they also focused on making the learning personalized and fun. 😍

Credevano che il software fosse perfettamente adatto a offrire un'esperienza personalizzata a ogni singolo studente di lingue.

And that language learning should be less boring and more like a fun game. Who’d want to come back to a language learning app otherwise? 😉

A product organization, focused on design and data

Universally accessible, personalized and fun. Sounds great. 👍

Come si fa a far sì che ciò accada?

Duolingo’s strategy is to relentlessly improve its product design to incite the right user behavior based on data. 👈

And they mean it. More than 3/4 of Duolingo’s team works on engineering, design, product or research.

Questo è in netto contrasto con l'altro grande software per l'apprendimento delle lingue: Rosetta Stone. Solo poco più di 1/4 del suo team lavora in questi stessi settori (in base ai dati di LinkedIn Premium).

It’s the classic battle: product organization v.s. marketing-sales organization.

And if you investigate Rosetta Stone v.s. Duolingo growth, Duolingo’s product strategy proves to be superior. 💪

Secondo Google, ottengono un maggiore interesse nelle ricerche.

E fanno crescere la loro azienda a un tasso molto più alto, secondo LinkedIn.

As a mathematician and computer scientist, Duolingo’s co-founder Luis von Ahn did not always believe in the power of product design.

But now, when asked for the most life changing book he’s ever read, he’d tell you it’s “The Design of Everyday Things” by Don Norman. Since he’s read the book, he’s obsessed with how products are designed.

And as a team lead by scientists, Duolingo doesn’t just improve design based on personal feelings. It uses data as its guiding star. 🌟

Tre obiettivi, tre team Duolingo: apprendimento, crescita e monetizzazione

Per Duolingo, il corretto comportamento dell'utente significa:

• Apprendimento: le persone hanno più successo nell'apprendimento
• Crescita: più persone imparano
• Monetizzazione: maggiori entrate per sostenere la causa

That’s why Duolingo decided to create three teams to work on these three goals: a learning team, a growth team and a monetization team. 💡

Ogni team è responsabile del miglioramento delle metriche legate al proprio obiettivo specifico, organizzando esperimenti di prodotto.

5 Esperimenti sui prodotti Duolingo

La homepage di Duolingo dà già una buona idea di alcuni dei modi in cui il prodotto è costruito per stimolare il giusto comportamento dell'utente.

The fact that the software doesn’t even use “hearts” anymore, and doesn’t mention badges or its in-app coach “Duo”, is a clear example of how quick and often Duolingo runs product experiments to improve the product.

Here’s 5 notable experiments and the concrete impact they had. 👇

1/ Delayed signup

The Duolingo team found that by allowing users to sign up later and experience some Duolingo lessons first, it could boost the amount of daily active users by 20%. 💥

Based on these experiments the team introduced “soft walls”. Those are optional pages that ask people to sign up, but still allow them to hit “Later”.

Finally, after a series of lessons, there’s a “hard wall” that requires users to sign up. 🛑 The team found that the performance of this wall was actually also improved by the presence of the “soft walls” as users were already primed to sign up.

In the process of introducing the “soft walls”, Duolingo made a mistake it later had to correct: the team created a big red “Discard my progress” button. What it found later is that this button actually invited people to click on it instead of scaring them from clicking. Replacing it afterwards with a more subtle grey “Later” button made performance shoot up.

The team was able to improve daily active users by another 8.2% with these subsequent experiments. An extremely significant amount. 😲

2/ Streak

Another important product aspect the Duolingo team experimented with a lot, is the concept of the “streak”, which it borrowed from the gaming industry.

That means: if a user uses Duolingo for x consecutive days he or she builds up a streak. Users start feeling invested and they try not to break this streak. They reward persistence. 🎁

I’m personally on a 152 day streak right now and it’s my best motivation to keep going. 💪

Il potere della striscia sulla conservazione è così forte che il team di Duolingo dedica molto tempo alla sua ottimizzazione. In particolare, rende più difficile perdere la striscia e più facile recuperarla con alcuni esercizi.

The team introduced “weekend amulets”, “streak repair”, “streak freeze”, … so that people can make up for their human failures. Introducing the amulet alone was responsible for a 4% increase in 14 day retention. ✨

3/ Notifiche

Inoltre, il team è stato in grado di migliorare le conversioni rispetto alle notifiche di circa 5% solo modificando la copia e testando diversi orari.

One of the most famous copy experiments is this passive aggressive notification: “Hi! It’s Duo. These reminders don’t seem to be working. We’ll stop sending them for now.”

In termini di tempistica, il team ha scoperto che 23,5 ore dopo la sessione di apprendimento passata era il momento migliore per ricordare alle persone di fare la sessione successiva, poiché le persone di solito imparano nello stesso momento della giornata.

4/ Distintivi

Un classico aspetto di gamification aggiunto dal team di Duolingo sono i badge.

Badges display the user behavior Duolingo wants to promote. This includes: spending lingots (Duolingo’s virtual currency), starting wagers, keeping streaks, learning during weekends, being active in Duolingo’s built-in language clubs, …

La prima versione del sistema di badge da sola (anche senza i livelli di badge, cioè le stelle nello screenshot qui sopra) ha già aumentato gli utenti attivi giornalieri di 2,4%.

Ma ha anche stimolato un comportamento positivo molto specifico: ha aumentato gli acquisti dal negozio di Duolingo di 13% e ha aumentato la quantità di amici aggiunti di 116%.

5/ In-app coach

One of the more controversial experiments within the Duolingo team was the introduction of the in-app coach called “Duo”, the supportive owl mascot. Some team members loved it, some disliked it and found it annoying.

Personal tastes aside, the guiding data star is always right. 🌟

The introduction of Duo improved 14 day retention by 7.2%. Almost as big a success as the badges. 🚀

Duolingo continua a mettere in fila esperimenti di prodotto

Duolingo sa che fermare il processo di miglioramento significa restare fermi. E restare fermi significa alla fine fallire.

On the other hand, there’s an infinite amount of product experiments one can run and mindlessly starting experiments can prove to be a total waste of time.

That’s why the Duolingo team diligently keeps track of all possible product experiments, prioritizes them, and then plans them in accordingly.

A tenere tracciaDuolingo aggiunge l'elenco degli esperimenti a JIRA. (Nota: utilizzare quello che funziona. Noi di Salesflare usiamo GitHub invece di JIRA).

Per prioritizzare, hanno 2 semplici regole di priorità costi-benefici:

1. What’s the impatto potenziale dell'esperimento? Il team di Duolingo ha persino deciso che gli esperimenti con un impatto inferiore a 1% non valgono la pena.
2. Quanto tempo ci vorrà per eseguire gli esperimenti?

Infine, quando pianificano, scelgono coerentemente di non ignorare i piccoli esperimenti a favore di quelli grandi. They believe that it’s the succession of an enormous amount of tiny improvements that leads to big results.

Way to go, Duolingo! 🙌 Keep going strong on your awesome mission.

The Salesflare team loves you. 😍

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