The client
A multi-location dental group sitting on years of patient and practice data — and, like most, unable to turn it into a signal about who's about to churn or which leads are worth the front desk's time.
The challenge
Patient attrition in dentistry is quiet. A patient simply stops booking — no cancellation, no warning — and the practice notices months later, if at all. Meanwhile, new leads pile up with no way to tell the high-value ones from the noise. The data to predict both existed; the intelligence to act on it didn't.
- Silent attrition — patients lapse without any cancellation or warning, so the practice only notices the lost revenue long after it's gone.
- Unsorted leads — inbound and existing leads piled up with no way to separate the high-value ones from the noise.
- Latent data — the signal to predict both churn and lead value was already in the data, but nothing was reading it.
What we built
An AI layer on top of the group's existing data:
- Churn prediction — models that flag patients drifting toward lapse (overdue recalls, falling visit frequency, unbooked treatment) while there's still time to act.
- Lead scoring — ranking inbound and existing leads by likely value, so staff spend effort where it pays.
- Actionable surfacing — risk and opportunity pushed to the people who can do something about it, not buried in a dashboard.