7-day retention: where most new users disappear

In this episode of Datadrivet, Joni Lindgren and Jasmin Yaya look at 7-day retention, the share of new users who are still around a week after they sign up, and why it decides whether acquisition spend pays off at all.

The episode opens with a real case. A company Jasmin had contacted was losing 80% of its new registrations: people signed up and never came back. As the hosts put it, it makes no difference how many new users you get if they do not keep using the product. Every marketing krona that brings in a user who leaves within a week is spent on someone who was never going to stay.

Their argument is that the fix usually comes from a better first-time experience rather than from more traffic or more features. If the first 7 days are designed so that a new user actually gets going, more of them return at 1 day, 7 days, and 30 days, and the acquisition budget starts to earn its keep.

They give three practical steps:

• Build the chart first. Plot signup day on the x-axis and retained users on the y-axis so you can see the curve instead of guessing at it.
• Plan the first 7 days of the user experience before you launch, rather than hoping onboarding sorts itself out.
• Test your fixes one at a time and iterate, instead of assuming the first version of onboarding is the best one.

Along the way the hosts point to products worth studying for how they handle a new user’s first week, including Trello, Mentimeter, Blocket, Memmo, Shopify, and Havenly. This is also the episode where Jasmin has joined scilla.studio and now works alongside Joni.

The takeaway: retention is set early. If users do not come back within the first 7 days, look at the start of the experience before you spend more on getting them in the door.

Listen to the full episode of Datadrivet for the examples in detail. If you want to know whether your own retention curve is normal for your model, that is what the benchmark tool is for: https://benchmark.scilla.studio