Break the journey to long term usage into smaller steps

If someone successfully uses your product once that doesn’t automatically turn them into a long term user.

Behavioural data lets you reverse engineer how often people need to use your app to become long term users.

You’ll need two things to do this: behavioural data and long term users.

The definition of a long term user is fluid but 6 months is usually a good place to start.

The thing you are looking for almost always boils down to performing your core action a certain number of times within a specific timeframe.

If you’re thinking of Facebooks ‘7 friends in 10 days’ metric then I’d like to point out that adding friends is probably not their core activity. I have no idea what action they track but if I had to guess it’s probably scrolling through the feed.

The feed is what gets people hooked, that the things people build an unhealthy relationship with. It’s the kick I’m looking for when I get bored. Who knows, maybe their data shows that liking photos or publishing posts have a higher correlation with long term usage.

The point is that whatever core action they track, ‘7 friends in 10 days’ is likely just a pre-requisite. You can’t scroll through your feed if you don’t have any friends to populate it.

If your core action has a strong correlation with long term usage the what behaviour correlates with your core action?

You can use data reverse engineer and then chart a sequence of your best correlations to help people become long term users.

Every step is an opportunity for people to drop off so you don’t want to build a long chain of correlations. The sooner you solve the problem the more likely you are to help people build a habit around your solution.