Retention
Predict who is about to cancel before they do
Five members slipping. Three trending stable. Two newly active. Every Monday morning.
The pattern of three sessions a week becoming two becoming one is the strongest signal a member is about to cancel. AI flags it before the cancellation form gets opened.
What happens
Connect access logs, class bookings, or appointment history.
Workflow scores each member weekly: stable, slipping, or recovering.
Flagged members get a personal outreach drafted in your trainer's voice, referencing their last session.
You see the list every Monday. Approve the messages. Send.
Included
- Weekly churn risk list, not a generic engagement score
- Outreach drafts that reference real session history, not a template
- Save table — track who came back after the nudge
When this becomes bigger
If this workflow starts touching inventory, staff, dashboards, customer history, or several locations, move into a custom AI system.
Questions
Plain answers before we build.
Does this work without a fancy access system?
Yes — even a simple class booking spreadsheet or POS check-in log gives the workflow enough signal.
Are messages auto-sent?
No. Every retention message is drafted and waits for trainer approval. Trust matters more than speed here.
How early does it catch dropouts?
Usually 4 to 6 weeks before cancellation. The earlier you reach out, the higher the save rate.