The problem
Clients don’t announce they’re leaving. They just stop booking, and you find out months later when they don’t come back.
What this shows
Which clients are likely to lapse, how much yearly value is at stake, and who’s ready for an upgrade.
Try it
Set Next Visit Due to “Overdue now,” then open Client Detail and click a client to see why they’re at risk.
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Annual Value by Predicted Risk Tier
Risk by Primary Service
Highest Expected Loss
Ranked by annual value × chance of lapsing
Highest Expected Upgrade
Biggest dollar opportunity first
Which clients are likely to lapse before their next treatment, and why?
Chance of Lapsing vs Annual Value
InjectablesLaser & SkinFacials & Body
Primary Risk Driver
Biggest factor for each Medium and High client, weighted by annual value
At-Risk Annual Value by Source
At-Risk Annual Value by Tenure
Expected Loss by Visit Timing
Which clients are ready to upgrade, and to what?
Top Upgrade Candidates
Expected Upgrade by Primary Service
Upgrade Gaps
Share of likely-upgrade client value not yet using each offering
What's Driving This Score
Starts from the average client and adds each factor's effect
Key Observations
Visit History
Spend per Visit
Select a client to open its journey.
Practice
Lapsed Client
A client who has not returned within a reasonable window after their usual treatment interval.
Annual Value
Expected spend from the client over the next twelve months at their current pattern.
Value at Risk
Annual value of clients at or above the Medium-risk threshold.
Expected Loss
Annual value multiplied by chance of lapsing, summed across clients.
Expected Upgrade
Upgrade opportunity multiplied by upgrade likelihood.
Forecast Value Retention
(Annual value − expected loss + expected upgrade) ÷ annual value.
Signals
Interval Elapsed
Time since the last visit as a share of the client's usual treatment interval. 120% means 20% past due.
Rebooked at Checkout
Whether the client booked their next appointment before leaving the last visit.
Missed Appointments
No-shows and late cancellations in the last twelve months.
Spend Trend
Change in spend per visit, last six months versus the prior six.
Tenure
Months since the client's first visit.
Membership
Whether the client holds an active membership.
How the Scores Work
Risk Score
The estimated chance a customer leaves in the coming period, based on patterns in past history. In a client engagement, scores are built from the client's own records.
Risk Tier
Low, Medium, or High, based on the risk score.
Top Driver
The factor pushing a score up the most, and usually the first thing to address.
Want to see this for your business?
This is sample data. For a client, it’s built from your own booking and sales records, so you know who to call before they drift away.