A two-chair practice reactivates patients who quietly stopped coming

Illustrative build — full arithmetic

A two-chair practice reactivates patients who quietly stopped coming

Modelled on a practice with 1,800 patient records, of which 620 had not booked in over 18 months, at a $210 hygiene visit value.

Illustrative build — modelled scenario, not a named client

The starting situation

The schedule looks healthy because the front desk fills it from whoever calls. Meanwhile hundreds of existing patients have drifted, and nobody has the hours to work a list of 620 names by phone. The practice pays for new-patient acquisition while its cheapest available revenue sits in the practice-management system.

What was installed

  • AI Automation System recall workflow segmenting the list by last visit and treatment type
  • Three-touch reactivation sequence over email and SMS, written per segment
  • Booking link that respects real hygiene availability instead of a generic form
  • Membership and treatment-plan follow-up on every completed visit

Before and after

Modelled before and after figures for A two-chair practice reactivates patients who quietly stopped coming
MeasureBeforeAfter
Inactive patient records620620 worked
Reactivation outreach sentAd hoc620 across 3 touches
Appointments booked from the list~10 / year~55 in 90 days
Average visit value$210$210
Front-desk hours spentn/a (never done)Under 3 hours of review

The arithmetic

  1. 620 inactive patients × a 9% reactivation rate = about 55 booked visits.
  2. 55 × $210 = roughly $11,550 recovered from records already in the system.
  3. Treatment follow-on from a share of those visits is upside not counted here.
Payback

The $119 system clears on the first two reactivated patients.

Verdict: Recall is the highest-margin revenue in a practice because the acquisition cost was paid years ago. It only needs a system that actually sends the messages.

What to install to reproduce this

This build runs on AI Automation System, bundled inside the Dentists package.

  • · AI Automation System recall workflow segmenting the list by last visit and treatment type
  • · Three-touch reactivation sequence over email and SMS, written per segment
  • · Booking link that respects real hygiene availability instead of a generic form
  • · Membership and treatment-plan follow-up on every completed visit

Related pages

More build math

Definitions

Key terms on this page

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Sources & methodology

How the numbers on this page are measured

Every metric quoted for this modelled build has a stated definition, a formula, and an assumption you can test against your own books. Last reviewed 2026-08-05.

Metric definitions, formulas, and assumptions
MetricDefinitionHow it's calculatedAssumption
Speed to leadThe elapsed time between a prospect raising their hand (form, call, DM) and the first substantive reply reaching them.first_reply_timestamp − inbound_timestamp, measured per lead and reported as a median.An automated reply counts only if it asks a qualifying question or offers a booking action — an autoresponder that says 'we got your message' is not a reply.
Payback periodHow long the system takes to return its own cost in gross profit.total_setup_and_tool_cost ÷ (incremental_jobs_per_month × average_ticket × gross_margin).Uses gross margin, not revenue. Where a margin is not stated on a page, the model assumes the trade's typical margin and says so inline.

Sources

What this is — and isn't

Figures on this page are modelled, not audited client results. Inputs (call volume, ticket size, close rate) are stated next to every number so you can substitute your own. We do not publish named-client outcomes, aggregate ratings, or testimonials we cannot evidence.

Full modelling rules, attribution rules, and the correction policy are on our methodology page.

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