Do the customers I win
actually stay?
One honest question. Answer a few things and it resolves into a Mark.
Who are we looking at?
A name makes it yours; the four choices fit the benchmarks to your world.
Do new customers reach value —
and survive the early window?
Two signals: how many new customers get to first value, and how many are still with you at day 90.
e.g. 34 — the share of new customers reaching first value within ~30 days
e.g. 91 — the share of a new cohort still active at day 90
A year in, are they still here —
and who's quietly slipping?
The long-run hold, and the leak that's forming right now — the one forward-looking signal in the system.
e.g. 86 — the share of last year's customers still with you today
e.g. 10 — the share of your active base showing lapse signals right now
What does your gut say?
We'll hold this against what the data shows — the gap is where the insight lives.
Retention Intelligence answers one question: do the customers you win actually stay. It reads the retention curve at four points — whether new customers reach first value, whether they survive the fragile early window, whether they're still with you a year in, and how much of your base is quietly slipping right now — resolved into one verdict.
This is the behavioral counterpart to Revenue Health. That engine reads what the money did — retention revenue, churn, unit economics — which are lagging, financial outcomes. This engine reads what your customers are doing — the leading signals that produce those outcomes. When Revenue Health says churn is high, this engine tells you where in the customer's life the leak formed. What it doesn't tell you is whether those customers were worth acquiring, or whether they converted efficiently in the first place. Those are different questions for different engines.