Retention IQ
The math · No magic, just multiplication

What recovery could produce.

Find a dormant-book size on the left axis and an average ticket on the right. The cell where they meet shows the output of one formula-driven scenario at the selected conversion assumption.

The formula
Recovered revenue = dormant clients × reactivation rate × average ticket

Dormant count and average completed-service value can come from your source system. Reactivation rate is still an assumption until a reconciled campaign produces verified completed returns.

Table 1 · Per-campaign recovery

What one campaign produces.

At a 10% planning assumption. Each cell is the arithmetic output if that share of the dormant pool becomes a verified completed return at the displayed ticket value.

Avg ticket ↓   Dormant → dormant 250 dormant 500 dormant 1,000 dormant 2,500 dormant 5,000
$100 $3K $5K $10K $25K $50K
$200 $5K $10K $20K $50K $100K
$300 $8K $15K $30K $75K $150K
$500 $13K $25K $50K $125K $250K
$750 $19K $38K $75K $188K $375K
$1,000 $25K $50K $100K $250K $500K

Read it like this: a salon with 1,000 dormant clients at $200 avg ticket recovers $20,000 from one campaign. A dental practice with 2,500 dormant patients at $300 ticket recovers $75,000. Multi-location and DSO numbers compound from there.

Table 2 · Annual recovery

What 12 months of consistent cadence produces.

At a $300 average ticket and 10% per-campaign planning assumption. The model applies diminishing returns and an explicit 55% cumulative cap. The cap is a modeling choice, not an observed Retention IQ benchmark.

Cadence ↓   Dormant → dormant 250 dormant 500 dormant 1,000 dormant 2,500 dormant 5,000
1 / quarter
Conservative — most practices
34% reactivated
$26K $52K $103K $258K $516K
1 / 2 months
Standard cadence
47% reactivated
$35K $70K $141K $351K $703K
1 / month
Aggressive — high-engagement verticals
55% reactivated
$41K $83K $165K $413K $825K

Model behavior: increasing cadence raises the arithmetic output while diminishing returns reduce each incremental gain. Real cadence must respect service timing, consent, frequency limits, customer experience, and measured results.

Table 3 · Rate sensitivity

What happens if reactivation runs conservative or aggressive.

The same per-campaign formula at three user-visible assumptions: 6%, 10%, and 15%. These are sensitivity inputs, not customer benchmarks or promised campaign results.

Conservative · 6%

Lower sensitivity input

Dormant $300 ticket
250 $5K
500 $9K
1,000 $18K
2,500 $45K
5,000 $90K
Midpoint · 10%

Planning midpoint

Dormant $300 ticket
250 $8K
500 $15K
1,000 $30K
2,500 $75K
5,000 $150K
High scenario · 15%

Upper sensitivity input

Dormant $300 ticket
250 $11K
500 $23K
1,000 $45K
2,500 $113K
5,000 $225K
Table 4 · Your vertical

What recovery looks like in your category.

Illustrative defaults by vertical. The recovery column applies the displayed ticket and reactivation assumptions to 1,000 dormant clients. Replace every default with measured source-system data before making a decision.

Vertical Typical dormant Avg ticket Reactivation Per campaign
(1,000 dormant)
Dental practice
Hygiene recall + cosmetic case acceptance
45% of active $285 11% $31K
Med spa / aesthetics
Tox fade-clock + filler + skincare packages
55% of active $540 12% $65K
Optometry / vision
Annual exam + VSP/EyeMed benefit windows
50% of active $385 10% $39K
Specialty medical
Deductible-met windows + deferred procedures
60% of active $720 13% $94K
Hair salon / colorist
Color refresh + cut cadence (5-7 week)
50% of active $138 11% $15K
Massage therapy
Monthly habit + package buyers
50% of active $128 9% $12K
Fitness studio
28-day cliff + class-pack drift
50% of active $189 10% $19K
HVAC contractor
Seasonal tune-up + maintenance plan
40% of active $179 9% $16K
Plumber
Emergency-to-recurring + water heater age
60% of active $445 14% $62K
Pet grooming
Breed-specific coat cadence
45% of active $85 10% $9K

Multiply for your book size: if your practice has 3,000 dormant clients in a vertical showing $30K per 1,000 dormant, that's $90K per campaign. Annualize at your chosen cadence using Table 2.

Where the numbers come from

The assumptions — in plain English.

01

10% planning midpoint

The model uses 10% as a visible midpoint between 6% and 15%. It is not described as an industry average or Retention IQ customer benchmark. Replace it with a measured completed-return rate when reliable campaign data exists.

02

55% cumulative model cap

The annual model caps the original dormant pool at 55% to prevent indefinite compounding. This is an explicit constraint for scenario planning, not a claim that every business has the same addressable ceiling.

03

Diminishing returns per campaign

Each campaign reactivates 10% of CURRENTLY-DORMANT clients, not 10% of original dormant. After 4 campaigns at 10% each, cumulative reactivation is 1-(0.9)^4 = 34%, not 40%. The math flattens as the pool shrinks.

04

Average ticket is gross, not net

We use your gross ticket because that's the number a dormant-client recovery is worth to the practice — same payer mix, same in-network discount profile, same redemption rate on packages. Net margin varies wildly by vertical and is your decision to make against this gross-revenue baseline.

05

Execution is not modeled

The arithmetic does not predict list quality, reachability, consent, delivery, message quality, service demand, cancellations, no-shows, or operational capacity. Those factors can move completed-return results materially.

06

What's not in these numbers

The model excludes cross-sell, referrals, discounts, delivery costs, refunds, disputes, and downstream relationship effects. Do not assume those omitted effects are positive; measure them separately.

Replace the sample assumptions with measured inputs.

Start with a sample-data walkthrough. If the workflow fits, we will confirm the permitted source data, dormancy definition, consent posture, attribution rules, and completed-service evidence before customer data moves.

15 minutes · no sales pitch Works with your booking platform