GTM Sauce

Duolingo · B2C · language learning app

Ship every change as an A/B test, even back-end tweaks

Credited for ~50% yearly DAU growth a decade after launch; no test-level numbers

Workedexperimentationanalytics-attribution

What they did

Every change, down to back-end changes with no UX impact, is released as an A/B test to catch regressions elsewhere in the app. In-house experimentation platform built by a data infrastructure/experimentation team: engineers set up tests once a feature is built, and reports on new data are generated every morning; PMs check the experiments dashboard first thing each day. One retention team runs ~20 experiments at a time. Each test yields 5-6 learnings that are turned straight into new tests. Different experiments may run on the same surface on iOS and Android, then the winner is aligned across platforms.

What happened

Guest says the formula works; Duolingo still grows DAU ~50% year over year about 10 years after launch.
8:29
“Even if it's just like a back-end change that doesn't change the UX experience at all, we'll just run it as an A/B test just to make sure there's no regressions where it impacts something else in the app.”
Osman Mansur
9:09
“every morning, every day, we generate reports on the new data that comes in from experiments, and as a PM, that's like my first thing I do when I wake up is check the experiments dashboard”
Osman Mansur
6:05
“So every time we run an A/B test, we will analyze the data, and from that data, we'll learn like five or six different things that we can then turn around immediately and test again.”
Osman Mansur

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