The problem
Facilities rarely cancel. Their trips just drift to another provider, and most owners notice after the revenue is gone.
What this shows
Which facilities are likely to leave, how much revenue is at stake, and why, so you can act before renewal.
Try it
Set Agreement Renewal to “Next 90 days,” then open Facility Detail and click a facility to see what’s driving its risk.
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Annual Revenue by Predicted Risk Tier
Risk by Facility Type
Highest Expected Loss
Ranked by annual revenue × chance of leaving
Highest Expected Growth
Biggest dollar opportunity first
Which facilities are likely to move their trips to another provider, and why?
Chance of Leaving vs Annual Revenue
DialysisHospital & ClinicSenior & Rehab
Primary Risk Driver
Biggest factor for each Medium and High facility, weighted by annual revenue
At-Risk Annual Revenue by Service Zone
At-Risk Annual Revenue by Tenure
Expected Loss by Agreement Renewal
Which facilities are likely to send more volume, and for which service levels?
Top Growth Candidates
Expected Growth by Facility Type
Service-Level Gaps
Share of likely-growth facility revenue not yet using each service level
What's Driving This Score
Starts from the average facility and adds each factor's effect
Key Observations
Quarterly Service History
Revenue by Quarter
Select a facility to open its journey.
Network
Facility Attrition
A facility moving most or all of its trips to another transportation provider. It rarely arrives as a formal cancellation; volume drains away.
Annual Revenue
Trip revenue from the facility over the last twelve months.
Revenue at Risk
Annual revenue of facilities at or above the Medium-risk threshold.
Expected Loss
Annual revenue multiplied by chance of leaving, summed across facilities.
Expected Growth
Growth opportunity multiplied by growth likelihood.
Forecast Revenue Retention
(Annual revenue − expected loss + expected growth) ÷ annual revenue.
Signals
On-Time Rate
Share of the facility's trips where pickup happened inside the scheduled window.
Turnback Rate
Share of the facility's scheduled trips that were not completed.
Trip Volume Trend
Change in trips, last six months versus the prior six.
Complaints (90 days)
Complaints from the facility or its patients in the last 90 days.
Standing-Order Share
Share of trips that are recurring standing orders, such as dialysis three times a week. Standing orders are stickier than one-off trips.
Tenure
Months since the facility's first trip.
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 trip and billing records, so you can see which customers are slipping before they’re gone.