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Member success · Client follow-up

Don't just report churn. Prevent it.

Many tools stop at an at-risk list. Workout OS closes the loop: it notices the change itself every night, explains it with numbers, suggests what to do and measures what happened. Called Member success in the gym product and Client follow-up in Workout Studio, and included in every plan.

DA

Deniz A.

Monthly membership · ends in 11 days

Example

Member success

Priority: high

  • Fewer visits

    Weekly visits 3.1 → 0.5

  • Renewal soon, low activity

    Membership ends in 11 days

Weekly visits, last 12 weeks

12 weeks agoOwn average 3.1this week

Why this order? A high-severity reason and a renewal coming up.

Not a churn prediction, a situation worth following up.

  • Review programmeTask for the trainer
  • Reach outNeutral draft ready
  • Follow-up taskPerson, date, note
Example screen. Sample data, not a real member.

The four-step loop

A list is not enough. We close the loop.

Noticing is the easy part. What matters is that what was noticed reaches a person at the right moment with something they can do, and that you can see afterwards whether it worked.

  1. 01Notice

    Every night, against each member's own history.

    Someone who comes once a week is not "low attendance". What we look for is a drift from that member's own normal.

    • Visits
    • Programme adherence
    • Renewal
    • Pack ending
  2. 02Explain

    The reason comes with numbers.

    "Weekly visits 3.1 → 0.5." Not a churn prediction, a situation worth following up.

    • 3.1 → 0.5
    • Rule + threshold
    • No black box
  3. 03Act

    One tap turns it into an action.

    The trainer reviews the programme, staff send a personal message from a neutral draft, and a follow-up task is created.

    • Programme
    • Personal message
    • Task
  4. 04Measure

    14 and 30 days later, it shows what happened.

    Did they come back, are they active again, did they renew? Members you followed up shown next to members nobody contacted.

    • 14 days
    • 30 days
    • Side by side

The same loop runs in both products: for members in the gym product, for clients in Workout Studio.

1 · Notice

Eight explainable rules, each measured against the member's own normal.

No black box and no score. Each rule reads as a sentence and each reason comes with a number. You can switch rules on and off and change their thresholds in settings.

01Both
Fewer visits
Weekly visits over the last 14 days are below half of the member's own 8-week average (average of at least one a week).
02Both
Not seen lately
No visits for 14 days or more while the membership or pack is active.
03Both
Programme slipping
Less than 40% of planned workouts completed in the last 2 weeks (at least 60% before).
04Gym
Renewal soon, low activity
The membership ends in 14 days or less and activity is low.
05Studio
Package ending, no booking
2 or fewer sessions left or 10 days to expiry, with nothing booked ahead.
06Both
Slow start
Fewer than 4 visits in a gym member's first 30 days, or fewer than 2 in a studio client's first 3 weeks. The most critical period.
07Both
Missed bookings
At least 2 of the last 3 bookings were no-shows or late cancellations.
08Gym
Quiet after freeze
The freeze ended and there have been no visits for 7 days.

These are the default thresholds. Rules stay quiet when there is not enough data: a member with less than 4 weeks of history gets no personal-baseline comparison, only slow start and long absence are checked. That avoids a "everyone is at risk" screen in the first days.

2 · Explain

Every case carries its "why" in numbers.

When a case opens, staff do not just see a name. They see which rule fired and with what number, a 12-week chart and why the case sits where it does in the list.

  • Reason chips with numbers: "Weekly visits 3.1 → 0.5"
  • A 12-week mini chart against the member's own average
  • A "why this order?" note: severity, how close the renewal is, membership value, new member
  • The language of "worth following up", never a prediction that someone will leave
  • One open case per member; new reasons are added to the existing case
SK

Selin K.

8-session pack · 1 session left

Example

Client follow-up

Priority: medium

  • Package ending, no booking

    1 session left, nothing booked ahead

  • Missed bookings

    2 of the last 3 bookings were no-shows or late cancellations

Weekly sessions, last 12 weeks

12 weeks agoOwn average 1.8this week

Why this order? The pack is about to run out.

Not a churn prediction, a situation worth following up.

  • Review programmeTask for the trainer
  • Reach outNeutral draft ready
  • Follow-up taskPerson, date, note
Example screen. Sample data, not a real client.

3 · Act

A person decides. The work takes one tap.

The system suggests what to do but never messages anyone on its own. Your team edits a neutral, warm draft and sends it personally.

  1. 01

    Review the programme

    A task goes to the assigned trainer and opens the programme editor. When the programme is published the action is marked done automatically.

  2. 02

    Reach out

    A neutral draft matched to the reason is prepared. Staff edit it and send it themselves by SMS or email, or call. The send is logged on the case.

  3. 03

    Follow-up task

    Create a task with a person, a date and a note. In the gym product it joins your existing tasks; in Studio it sits with the case's actions.

Closing a case asks for a reason (on holiday, injury, moved away, could not reach). Injury and holiday silence the case until the date you choose. If the member comes back, the case resolves itself.

Reach out

Draft · staff edit it and send it themselves

Reason: fewer visits

Hi Deniz, how are things going? If life is busy right now, we can make your programme fit better. Shall we put together a short, effective plan?

Example draft

  1. 1Edit the draft
  2. 2Send by SMS or email
  3. 3Logged on the case

The draft never says "risk", "churn" or "your attendance dropped". It goes to one person, from a member of staff, and the send is logged on the case.

4 · Measure

Did it work? We show it honestly.

14 and 30 days after a case opens, the system checks three things: did the member come back, are they back to at least 75% of their own average, did they buy a new membership or pack. The result is shown next to cases nobody followed up.

  • A comparison group: cases that opened but where nobody acted
  • Under 10 cases in a group, you see counts instead of percentages
  • No "revenue saved" claim; instead, "amount renewed by members you followed up"
  • We do not overstate small samples; the numbers stay as they are

Monthly outcome report

Day-14 check · sample data, not customer results

Example

Followed up

7 cases

Came back
5/ 7
Active again
4/ 7
Renewed
3/ 7

Not followed up

4 cases

Came back
1/ 4
Active again
1/ 4
Renewed
1/ 4

With fewer than 10 cases in a group we show counts, not percentages. We do not say "revenue saved"; we say "amount renewed by members you followed up".

What it does not do

Limits you can rely on.

A feature that touches your relationship with members should be defined by what it does not do as well.

  • 01

    No AI churn prediction

    We are not selling a machine-learning model. There are explainable rules, and you can read why each one fired.

  • 02

    No automatic or bulk messaging

    This feature never sends a message by itself. It prepares a draft and staff send it personally. One person, one message.

  • 03

    Members never see a "risk" label

    Only authorised staff see cases. Message drafts never use words like "risk", "churn" or "your attendance dropped".

  • 04

    No health data in the rules

    The rules do not read form answers or interpret measurements; for measurements they look only at the date of the last one.

For details on personal data, see the KVKK notice and the data processing agreement.

Data sources

No extra hardware.

Activity does not come from a single source. It brings together records you already keep, which is why we say "activity" and not "door entries".

Workout OS (gym)

  • Check-in from the member app (QR, member app coming soon)
  • Check-in recorded at the front desk
  • Class attendance and no-show records
  • Training logs and programme adherence
  • Membership end dates and freezes
  • Optional: a connected door system (API, signed webhooks, CSV)

Workout Studio

  • Booking records: attended, no-show, late cancellation
  • Packs: sessions left and expiry date
  • Upcoming bookings
  • Client programmes and the date of the last measurement

We sell no door or turnstile hardware. If you already have a system, you can connect it through the API; if not, the records from the app and the front desk are enough.

FAQ

Member retention questions.

What is member retention in Workout OS?

Member success (called Client follow-up in Workout Studio) compares each member's or client's activity with their own history every night and, when it sees a change, opens a follow-up case for staff. The case shows its reasons with numbers, suggests a programme review for the trainer, a personal message draft for the team and a follow-up task, and measures the result 14 and 30 days later. It is included in every plan.

What data does it use?

In the gym product: check-ins recorded at the front desk (and from the member app once it launches; coming soon), class attendance, workout logs and, optionally, records from a door system you connect, plus programmes, membership end dates and freezes. In Workout Studio: booking records (attended, no-show, late cancellation), packs, upcoming bookings and programmes. No extra hardware is needed, and we do not sell door or turnstile systems.

Is it AI? Does it predict who will leave?

No. We are not selling an AI or machine-learning prediction. There are eight transparent rules and each one is explained with a number (for example "Weekly visits 3.1 → 0.5"). You can change the thresholds in settings or switch a rule off. The output is not "this member will leave", it is "this situation is worth following up", and a person decides what to do.

Does it message members automatically?

No. This feature does not send automatic or bulk messages. It prepares a neutral, warm draft matched to the reason (for example "We haven't seen you for a while, shall we update your programme together?"), and staff edit it and send it personally. Staff send it by SMS or email, or call instead. One message goes to one person at a time.

What about privacy and KVKK? Does it use health data?

The rules do not use health data: form answers and measurement values are not interpreted, and for measurements only the date of the last one is checked. Members never see a "risk" label or score; only authorised staff see cases, and a trainer sees only their own members. The system does not decide anything about anyone, a person does. Cases are anonymised after 12 months and deleted when the member is deleted. Your business is the data controller and we act as processor under our data processing agreement.

Is it useful for a small gym or a one-person studio?

Yes. Because each rule compares a member with their own history, it works with few members, and in a small business it is hard to keep track of who has gone quiet. The limits are explicit: a member with less than 4 weeks of history gets no personal-baseline comparison (only slow start and long absence are checked), and with fewer than 10 cases in a group the outcome report shows counts instead of percentages.

Does it cost extra?

No. Member success and Client follow-up are included in every plan, the free plans included, at no extra charge.

Demo

See who is drifting before they are gone.

In the demo we look at your own member list and packs. No commitment.