Churn risk diagnostic
A three-week reading of how people stall, lapse, or cancel in one live app, delivered as a ranked memo.
app analytics · churn risk
The leaving often starts in a quiet week, not on the cancel screen.
Content Harborgrid sits with product and success teams while they still have the event log, the tickets, and the copy from the last billing cycle. We write a churn-risk reading of how people actually drift, stall, or leave a live app.
What you can actually commission
This is a Birmingham practice for teams who already ship an app and need a human reading of churn risk. You are not buying a login. You are asking for a diagnostic, a cohort sitting, or a pre-launch retention check.
Cohort review sitting
A half-day at the table with one cohort cut, naming which week the leaving actually concentrates.
Quarterly churn watch
A repeating read of the same leaving patterns, to see whether last quarter’s memo still holds.
Retention readiness review
A pre-launch check of cancel language, trial length, and the first-week path before paying users arrive.
How a reading is assembled
We start from the places people already argue about: the trial week, the first unpaid invoice, the feature nobody finishes, the help-desk pile that repeats the same verb. Those traces sit next to a cohort table, not instead of it. The output is a ranked list of leaving patterns with the evidence that made each one worth worrying about.
If you want the sequence of a typical three-week diagnostic, the engagement page walks through access, interviews, and the memo hand-over.
From recent sit-downs
They asked us not to “fix retention” in the abstract. They asked why Wednesday-night listeners vanished after a skip-heavy session. The memo named the skip cluster and left the growth slogans out of it.