Abay Ave club
64inside
46% load
- Next: Pilates 18:309/12
- Trainers on shift: 3
- Equipment is fine
Club numbers without
spreadsheets or exports
Every report lives in one place — the owner report. Revenue with a month-end forecast, member flow and reasons for leaving, cohort retention, trainer sales, app usage. Can’t find an answer? Ask the AI analyst: it runs the numbers on your data and draws the chart.
Core Included in every plan
Owner report
A report that comes
alive as you watch
Revenue against target and forecast, retention by cohort, the path from trial to purchase and hourly load. Switch the period or the club — everything recalculates.
Clubs switch on their own — click to pick one
Revenue0 M ₸
Period forecast0 M ₸
Active base0members
Churn0%per month
Cumulative revenue
ActualTargetForecast
Retention by purchase month
Trial → purchase
Booked a trial0
Showed up0
Bought within 30 days0
Load by hour
AI analyst
Ask your data
in plain words
The AI analyst writes the query, calculates on your data and draws a chart. Numbers come from the data, not from a retelling. It has read-only access.
Pick a question
Why did renewals drop in October?
- Taking memberships that ended in October
- Comparing renewals by club with September
- Checking first-month visits
61% renewed, down from 68% in September. The drop is at the Satpayev club: 52%, minus 14 pp. Members who came fewer than 4 times in their first month don’t renew: only 31% of them did, versus 74% of the rest.
How it was calculated Export CSV
Ask about your data in plain words
Clubs today
What’s happening
in your clubs right now
A screen with no money on it, so any staff member can open it. People inside, load, upcoming classes, trainers on shift and equipment.
Satpayev St club
41inside
37% load
- Next: Functional 19:0011/14
- Trainers on shift: 2
- Treadmill #4 under repair
Alatau club
23inside
26% load
- Next: Kids boxing 18:008/10
- Trainers on shift: 2
- Equipment is fine
Timiryazev St club
37inside
37% load
- Next: Yoga 20:006/15
- Trainers on shift: 1
- Ticket: no hot water in the shower
Updates in real time
Under the hood
Reports that
explain the numbers
3 280
Start
+214
New
+61
Returned
−143
Lost
3 412
End
Base movement
How many you had, how many joined and came back, how many were lost — and why the total is what it is.
Yerlan M.186,000 ₸No visits
Assel K.94,500 ₸Refund
Timur B.238,800 ₸Subscription cancelled
Dana O.59,700 ₸Club closed
Ilya S.119,400 ₸No visits
Churn with a reason
A card for everyone who left: lifetime spend and the reason based on facts.
Zhanna T.No visits for 16 days
Olzhas R.Hasn’t opened the app
Karina L.Charge failed
Risk signals
Stopped coming, stopped opening the app, a charge failed — a list with phones, ready for a journey.
Catalogue
100%
Membership
58%
Payment
34%
Bought
27%
In-app funnels
Which step people abandon a purchase at, how many payments fail and how many entries break.
96%
Abay
14,200 ₸/m²
81%
Satpayev
11,800 ₸/m²
104%
Alatau
15,600 ₸/m²
Targets by club
Sales targets, revenue per square metre and a completion forecast.
23:55 · snapshot saved
Mo
Tu
We
Th
Fr
Sa
Su
Nightly base snapshots
At 23:55 the base is saved — a late payment won’t rewrite past days.
RevenueClubsTrainers Owner
Manager
Trainers
CSV
Access per report
The owner sees everything, a manager sees their club, the head of trainers sees trainers. Lists export to CSV.
Revenue and the month’s forecast every morning
Churn reasons from facts, not hunches
An answer to any data question in a minute
What the owner sees
Revenue per metre
Enter club floor area — the report shows revenue per square metre and compares clubs side by side.
Products and categories
Memberships, subscriptions, trainers, classes and retail — with custom categories to group them your way.
Subscriptions
Monthly subscription revenue, sales, debtors and automatic checks of payment schedules.
Trainers and classes
Trainer sales by confirmed money, rent payback, trials and class fill rates.
The method behind every number
Each metric says how it was calculated. No more arguing over figures.
AI assistant in numbers
How many questions it closed on its own, what it cost and when an operator stepped in.
Owner report
One report instead of a dozen spreadsheets
The owner opens one page and sees the whole network: money, members, products and clubs. The methodology behind every number is right there.
- Filter by club and period
- Export any list to CSV
- Nightly snapshots of the base — history isn’t rewritten after the fact
- A “What matters” block with takeaways
01
Revenue
Sales, renewals, forecast and member flow
02
Attendance
Visits by day and hour, growth by club
03
Products
Memberships, subscriptions, trainers, classes and goods
04
Clubs
Network comparison and details for each club
05
Subscriptions
Subscription sales and their effect on visits
06
New and lost
Where members came from, what they bought first, who left and why
07
Retention and growth
Cohorts, risk signals, the path from trial to purchase
08
App and trainers
Section usage, funnels, trainer sales and content
Method
Numbers you can trust
Every metric follows one rule across all reports. Money comes from a single payment ledger, the member base from nightly snapshots.
- The method opens right next to the number
- Late payments don’t rewrite past days
- The same figures in the owner report and team reports
01
Money
One payment ledger: sales, subscriptions, trainers, retail
02
Base
A snapshot at 23:55 every day
03
Forecast
Day profile of past months plus the subscription schedule
04
Renewals
Matured windows: no gap, within 7 and within 30 days
05
Churned
Reason from facts: refund, club closure, subscription, visits
06
Trials
30 days from booking to purchase
Team reports
A report for every department head
Each department head sees a report at the right depth, from summary down to an individual member. Access is granted per report.
- Lists export to CSV
- Every report opens with a club filter
- Money is counted from the single payment ledger
01
Memberships
Sales, renewals, expiring plans and billing checks
02
Trainers
Workload, clients and income for each trainer
03
Trainer sales
Confirmed money vs. price-list grants, rent payback
04
Trials
The trial session funnel and purchases afterwards
05
Classes
Class occupancy and revenue
06
AI assistant
How many questions it resolved alone, its cost, when an operator stepped in
07
Security
Suspicious entries and membership sharing
Autonomous club
An owner’s morning
-
System
Saves an end-of-day snapshot of the base — late payments won’t rewrite history.
-
System
Refreshes churn-risk signals: members who stopped visiting or opening the app.
-
Owner
Opens the report: yesterday’s revenue, the month’s forecast and the gap to target.
-
Owner
Asks the AI analyst why renewals dropped at one of the clubs.
-
AI analyst
Counts renewals by club, draws a chart and shows that most non-renewers barely visited in their first month.
-
Owner
Exports the list of lost members to CSV and switches on a win-back journey.
Getting started
Reports are built from data the system collects on its own.
- 01
Data
Sales, visits, subscriptions and app activity accumulate from day one.
- 02
Targets
Set sales targets and club floor area — the report shows progress and revenue per metre.
- 03
Access
Decide who sees which report: owner, club manager, head of trainers.
- 04
Questions
Anything the report doesn’t cover, ask the AI analyst.
Also included
- Sales targets per club
- Revenue per square metre and occupancy
- Manual product categories
- Methodology behind every number
- Trial-to-paid conversion
- Newcomer cohorts
- Churn-risk signals
- In-app purchase funnels
- Payment declines and club entry failures
- Reach of trainer posts and stories
- Renewals over matured windows
- List exports with phone numbers
- Access granted per report
Questions about the module
Where do the numbers come from?
From payments, visits, subscriptions and app activity that the system records itself. No spreadsheets, no manual entry.
Why doesn’t history change after the fact?
A snapshot of the base is saved every night. A late subscription payment doesn’t rewrite how many members were active on a past day.
Can the AI analyst break anything?
No. It has read-only access, and charts are built from its query to the data — numbers aren’t retold.
How do we understand why members leave?
The Lost tab shows a fact-based reason: refund, club closure, what happened to the subscription, visits in the last month. Plus churn broken down by plan, age and source.
Can we look at a single club?
Yes. The owner report drills down to each club, and team reports filter by club and period.