A 340-member gym was churning 8–10 members a month and replacing them with roughly the same number of new members. Revenue looked flat. The owner thought the business was stable. It wasn't.
The gym had 340 members and had been at roughly that number for two years. Revenue was flat — $47,000 one month, $49,000 the next, $46,000 the one after. The owner called it stable. The business was not stable. It was a treadmill.
When we pulled the actual cohort data, the picture was different. The gym was losing 8–10 members a month and gaining 8–10 members a month. Net member count: flat. The owner had no visibility into this because her software showed her the balance, not the movement. She could see that she had 340 members. She could not see that she was replacing 100 of them every year.
Here's the math she hadn't run. Average membership: $140/month. Annual value of a retained member: $1,680. Members churned per year: approximately 110 (based on 8–10/month over 12 months, slightly higher in January and August). Annual revenue lost to churn: $184,800. Annual revenue from replacement members: $100,800 (new members cost acquisition money and many don't stay past month 3).
Net: she was spending time, energy, and acquisition budget to replace $184,800 in lost revenue with $100,800 in new revenue — a structural $84,000/year hole that looked like stability on the surface because new members kept arriving at roughly the same rate as departing ones.
She knew her monthly revenue. She did not know her annual churn rate, her member LTV, or how long the average member actually stayed. Her software — a mid-tier platform she'd been on for three years — showed her booking counts and monthly revenue totals. It did not show her the cohort breakdown that would have made this visible.
The number that changed her thinking wasn't the $84,000. It was the LTV chart.
When we built her cohort view — members who joined in Q1 2023 vs. Q1 2024 vs. Q3 2024 — the survival curves looked almost identical. 60% of members were gone by month 6. Another 20% were gone by month 12. Only 20% of any given monthly cohort was still a member at the one-year mark.
The gym had been running a discount intro offer ($49 for the first month) to drive new member volume. What the cohort data showed was that intro-offer members churned faster than full-price members — month 1 to month 2 conversion was 68% for intro members vs. 84% for members who signed up at full price. She was spending on acquisition to fill a leaky bucket with the fastest-churning segment of her audience.
Three operational changes came from this analysis, none of which required new staff or major program changes.
At-risk member flagging. Any member who had attended fewer than 2 classes in the past 3 weeks got automatically flagged. Staff could see these members in the daily dashboard and do a personal outreach — a text or a call, not an automated email. The personal touch was the key. Generic "we miss you" emails had a negligible recovery rate. Staff members calling a flagged member by name and asking if everything was okay recovered roughly 30% of the at-risk cohort.
Intro conversion sequence. The 30-day window after a new member's intro period ended was treated as its own retention phase. Automated check-ins at day 3, day 10, and day 20 of month 2. The message wasn't promotional — it was operational: "Here's what you've attended, here's a class that might fit your schedule better." Intro-to-month-2 conversion moved from 68% to 79%.
Kill the discount intro offer. This was the hardest decision. Dropping the $49 first month and moving to a free 7-day trial (no billing until day 8) changed the composition of new members significantly. People who signed up for the trial and stayed were better-fit members. First-month-to-month-2 conversion on trial members was 81%. New member volume dropped 15% initially, then recovered as word-of-mouth improved.
Twelve months later: member count was 367 (up from 340), monthly revenue was $53,000 (up from an average of $47,500), and monthly churn had dropped from 8–10 members to 5–6. Annual churn rate went from roughly 32% to roughly 19%.
None of this required a marketing budget increase. It required visibility into what was already happening — and a system that surfaced at-risk members automatically rather than requiring the owner to manually scan a spreadsheet every week for attendance drops she might catch or might miss.
The gym wasn't doing anything dramatically wrong. The owner was competent, her coaches were good, the facility was clean and well-run. The problem was informational: she had no way to see churn as a rate, members as cohorts, or LTV as a measurement. Her software gave her a snapshot — how many members today, how much revenue this month. She needed a film, not a photograph.
Most gym owners are in the same position. They can tell you how many members they have right now. Very few can tell you what their average member LTV is, what their 6-month retention rate is by cohort, or what the difference in churn rate is between members who were acquired through an intro offer vs. members who signed up at full price. That information exists in the data. Getting to it requires software that's built to show it.
The $84,000 gap wasn't created in one bad month. It was the accumulated cost of making decisions without the numbers that would have changed them.
See Mako in action — no sales call required
Mako is built for independent studio and service-business owners who'd rather spend their time on clients than on demo calls. Open the live demo, poke around, and see exactly how scheduling, billing, and financial intelligence come together in one place.
Try the demo: https://app.makocrm.so/demo
Self-serve. Instant access. No forms, no calendars, no "talk to sales."
A gym owner thought her admin overhead was 'a few hours a week.' The time audit showed 11.3 hours. Here's the full breakdown of where it went, which tasks were automatable, and what the gym looked like six months later when manual work had been cut by two-thirds.
A 300-member gym was paying $600/month for a bookkeeper whose primary job was telling the owner three numbers: revenue, member count, and whether cash was okay. When the gym moved to Mako, those three numbers were on the dashboard. The bookkeeper's job got smaller. Then it disappeared.
.avif)