Short answer: The 85% versus 72% comparison is a conditional scenario, not a universal benchmark. On 300 members, the 13-point difference equals 39 members; at $140 monthly billing for 12 months, that is $65,520 in conditional gross billings before refunds, costs, and timing. Local cohorts determine actual retention.
Source and method note (checked 2026-09-01): Benchmark context comes from the Health & Fitness Association’s 2025 Fitness Industry Benchmarking Report and its 2019 IHRSA Profiles of Success. The dollar figures below are author arithmetic from stated assumptions, not observed revenue. No source establishes that 85% or 72% is a universal gym standard or that a listed practice causes the gap.
Applied to a starting base of 300 members, a 72% annual-retention scenario leaves 216 members retained and 84 not retained. An 85% scenario leaves 255 retained and 45 not retained. The difference is 39 members, or 13 percentage points. If every retained member is billed $140 each month for a full 12 months, the difference in gross billings is 39 × $140 × 12 = $65,520.
| Scenario | Annual rate | Retained from 300 | Not retained | Conditional gross billings |
|---|---|---|---|---|
| Lower scenario | 72% | 216 | 84 | 216 × $140 × 12 = $362,880 |
| Higher scenario | 85% | 255 | 45 | 255 × $140 × 12 = $428,400 |
| Difference | 13 percentage points | +39 | −39 | +$65,520 |
This table is sensitivity arithmetic, not a forecast. It assumes the same starting denominator, price, billing continuity, and observation window. It excludes refunds, discounts, failed payments, taxes, payment fees, costs, replacements, and the timing of each member’s departure. “Gross billings” should not be relabeled as profit, realized revenue, or customer lifetime value.
The HFA 2025 report says its 2024 data produced a 66.4% median member-retention rate. Its published methodology describes confidential responses from 175 companies representing more than 17,000 facilities across 27 countries. That is a dated participant benchmark, not an average for every independent gym, and it does not validate an 85% target.
The HFA 2019 report is also a selected sample. It says 98 firms representing 10,859 clubs participated and reports 73.2% retention for independent facilities and 62.3% for chain clubs. Because the samples, years, definitions, and participating operators differ, the 73.2% figure should not be combined mechanically with the 2025 median or treated as a current industry norm.
No. A retention percentage is an outcome, not an explanation. The benchmark pages do not test whether coach assignment, a two-week check-in, milestone recognition, faster payment follow-up, or exit interviews caused a particular rate. Those ideas may be reasonable operating hypotheses, but the available primary sources do not establish their causal lift or a universal recovery percentage. Present them as practices to test, not as what every 85% gym does.
Do not infer causation from two groups that differ in price, contract length, location, class mix, staffing, member age, acquisition channel, or reporting definition. A higher rate may reflect selection, measurement, mix, or timing. A lower rate may reflect a different cancellation rule rather than a worse member experience.
Define the denominator and period before collecting a comparison. A useful local review can include:
Report counts as well as rates. A rate without its numerator, denominator, window, and exclusions is difficult to audit. Keep a separate table for cohorts that have not reached the full observation period, and do not call a partial cohort’s result annual retention.
Choose one intervention and one measurable outcome before launch. Define the eligible cohort, comparison period, exposure, retention event, and follow-up window. Record material confounders such as season, pricing changes, instructor changes, location, and membership type. Compare the result with a pre-specified baseline or a suitable concurrent comparison when feasible. Report uncertainty and missing data, and stop short of claiming causation from a before-and-after change.
For the 85% versus 72% illustration, the decision question is not “Which gym is better?” It is “Under the same stated assumptions, how does a 13-point difference translate into member counts and conditional billings, and what local evidence might explain it?” That framing keeps the calculation useful without turning a scenario into a ranking.
It can establish the arithmetic of the stated scenario and summarize the scope of two HFA participant samples. It cannot establish a universal retention target, a typical independent-gym rate, a causal playbook, a payback period, or the profit impact of any intervention. Recalculate the table when price, starting members, window, or retention definition changes.
Mako disclosure: Mako publishes this guide and offers software for independent service businesses. No Mako feature, customer outcome, or comparative superiority is used as evidence for the retention figures above. Evaluate any workflow with your own cohort definitions, records, and consent practices.
No. The cited HFA sources report participant samples with different years and scopes. The 85% figure here is a scenario used for arithmetic, while the 72% figure is a comparison assumption. Use a local definition and denominator before setting a target.
No. The amount is conditional gross billings under 300 starting members, $140 monthly billing, 12 uninterrupted months, and no adjustments. Refunds, discounts, failed payments, costs, and timing can materially change realized results.
Build a cohort table with member status, attendance, billing events, pauses, cancellations, and exit reasons. Review one defined period at a time, preserve unknowns, and test any operational change against a stated outcome before describing it as effective.
Next step: If you want to inspect a workflow for organizing membership, billing, and retention records, open the Mako demo and compare it with your own data process.
Related reading: Member Retention Strategies: How Top Gyms Keep Clients for Years; Churn Prediction for Gyms: Using CRM Data to Save Members Before They Quit; How to Calculate Member Lifetime Value.
