[case] CRM for a sports / fitness club · ПУЛЬС (під NDA)
A CRM for a sports club with AI analytics: retention and occupancy — the PULS case
Custom CRM from scratch + AI modules (churn forecast, schedule optimization, revenue forecast) · ПУЛЬС (під NDA)
[01] challenge
What the project had to solve
A sports club with over 1,200 active members. Memberships, group-class bookings, finances, personal training — all in different spreadsheets and in the administrators' heads. Hence three expensive problems. First — churn flying blind: no one could see that a client had stopped coming or was about to not renew, so they reacted only after the client was already gone. For a club where the money is repeat membership sales, every such client is a direct loss of revenue. Second — a schedule built "by eye": somewhere a full house and a waitlist, somewhere an empty hall at the very same hour. Third — the owner couldn't see the club's picture in real time: how many people are inside right now, where the revenue is going, where the slack is. What was needed wasn't just a client database, but a system that looks ahead: warns about churn and suggests how to fill the club.
[02] solution
What we did — and why
A real-time club dashboard. Active members, today's attendance, monthly revenue, occupancy, and how many people are in the club right now — broken down by zone (gym, pool, CrossFit, yoga). The owner sees the club's state on a single screen. A member database with history and LTV. Over 1,200 members with statuses (active / paused / expired), remaining visits, each member's LTV, and a card: contacts, current membership, recent visits, trainer notes, balance. A schedule that keeps occupancy up. A weekly schedule by trainer and hall with each group's capacity (spots available / nearly full / full house), a waitlist, and fill rates by hall. You can see where demand outstrips supply and where the hall is empty. Finances and revenue structure. Revenue, expenses, profit, structure (memberships, personal training, bar, merch), transactions, average ticket, repeat payments, and receivables — with no manual roll-up. Memberships about to expire — and not slipping through. A dedicated list of those whose membership lapses in the coming days, a "Renew" button, and a task for the administrator. AI inside the system — the heart of the product. AI retention analysis calculates churn risk for each member and names the reason (hasn't visited in 18 days, didn't renew, drop in frequency), rolls it into a forecast ("this month the club could lose 34 members = 71,400 UAH if it does nothing"), and immediately suggests actions: who gets a freeze, who gets a bonus week, who needs a call. AI schedule optimization forecasts the week's demand and gives specifics: add 2 CrossFit groups on Thursday at 19:00 (demand +40%), move the morning yoga, redistribute the trainer's load. The AI revenue forecast is a monthly plan based on current momentum. How we built it: a CRM from scratch tailored to the club's processes + AI modules, SMS / email integrations for reminders and reactivation campaigns, data on the client's server. Development was led by our engineer paired with AI-assisted development.
project frames
[03] result
→ +12% on the club's key metrics in the first month after launch (an early read, with momentum building) → Retention became proactive: AI flags the at-risk group before the client is lost, not after → The schedule rests on a demand forecast: fewer empty halls and fewer full houses with no spots → The owner sees the club on a single screen — money, occupancy, churn in real time → Building the system was a one-time $2200 instead of an endless monthly subscription for an off-the-shelf fitness CRM. After that — hosting only
Key metrics
+12%
Members in database
1200+
Churn forecast
AI
Development
$2200
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