Dental recall math, without invented benchmarks.
This page shows how a practice can model recall economics from its own numbers. Every output below is arithmetic from disclosed assumptions—not an analysis of 1,200 practices, not an observed Retention IQ customer result, and not a guarantee.
Start with numbers you can replace.
The sample practice exists only to demonstrate the formula. A real analysis should use source-system counts and a documented definition of “dormant.”
Show the range. Keep the assumptions attached.
Each scenario assumes the displayed percentage of the modeled dormant pool becomes a verified completed return. A click, booking, cancellation, or no-show is not counted as a completed return.
- Completed returns
- 86
- Gross recovered revenue
- $24,624
- Retention IQ fees
- $6,450
- Completed returns
- 144
- Gross recovered revenue
- $41,040
- Retention IQ fees
- $10,800
- Completed returns
- 216
- Gross recovered revenue
- $61,560
- Retention IQ fees
- $16,200
Replace assumptions with evidence.
Define dormancy
Use the practice's service cadence and source-system dates. Do not treat every patient past one global threshold as equivalent.
Count reachable, consented recipients
Remove suppressions, invalid contacts, and anyone who lacks the consent required for the intended channel and use case.
Track the full funnel
Keep delivered sends, clicks, bookings, cancellations, no-shows, and verified completed services visible.
Use completed-service value
Recovered revenue should come from the source of truth after the service occurs, not from a projected booking value.
Version attribution rules
Document the window, matching rules, reschedules, duplicates, and dispute handling before calculating results.
Publish only after release gates
A future cross-practice benchmark must use de-identified production data, minimum cohort sizes, reconciled funnels, and independent review.
Cite this page only as a planning methodology. Do not cite its scenario outputs as a dental-industry average, Retention IQ customer benchmark, or forecast.
Replace the sample inputs with your measured recall data.
A managed walkthrough can map your source system, dormancy definition, consent posture, attribution rules, and completed-service evidence before any production campaign is activated.