Kilo&Co cut churn 31% in one quarter by catching onboarding drop-offs early

Kilo&Co had grown to 40,000 monthly shoppers with a data team of two. Churn was climbing, but nobody could say which of the twelve changes shipped that month had caused it.

Every investigation started the same way: a chart in Signalroom, three theories, and a week lost before the loudest voice won.

Trace connected to their warehouse in an afternoon and began annotating every release automatically. Within a week it flagged that shoppers who hit step 3 of the new onboarding were abandoning at 2.6× the normal rate.

The fix shipped the next morning. The same cohort recovered inside two weeks — and the annotation stayed attached, so the whole team could see the story.

Churn fell 31% over the following quarter. The data team stopped fielding ad-hoc “why did this move?” requests and moved onto modelling work they'd deferred for a year.

• 31% reduction in monthly churn
• Root-cause time down from days to minutes
• Two engineers freed from reporting duty