Hall Occupancy Report: How to Read and Use It

Hall Occupancy Report: How to Read Metrics and Find Weak Slots

Hall occupancy analytics in IZI shows you how many hours devices ran, what share of total capacity was actually used, and which hours and days are consistently underloaded. The data is split across two sidebar sections: Analytics → Clients holds the session and client KPIs for the period (with period-over-period comparison); Analytics → Occupancy holds the hourly heatmap by day of week and the zone/device breakdown table. The date range is set at the top of each page. All tables support CSV export.

Clients: Session and Client KPIs

The Analytics → Clients page shows 13 KPIs grouped into three blocks: clients, sessions, and financials.

Client block

Metric	What it counts
Total clients	Unique clients with at least one session during the period
New registered	Clients with a phone number who registered in this period
New unregistered	Clients without a phone number who appeared this period
Returning registered	Clients with a phone number registered before the period
Returning unregistered	Clients without a phone number registered before the period

The four-way split shows the quality of your client base. A high share of “new unregistered” means a large portion of your audience passes through without identification — loyalty mechanics don’t reach them. Growing “returning registered” means your loyal base is strengthening.

Session block

Session count — total gaming sessions for the period. Extensions count as part of the same session, not as separate ones.

Sessions < 10 min — sessions shorter than ten minutes. A high count points to device issues, startup errors, or customers misunderstanding tariff terms.

Hours played — total time across all sessions in hours. This is the numerator in the occupancy formula.

Average session length — hours played ÷ session count. Describes a typical customer visit.

Average Occupancy % — the core hall efficiency metric:

Average Occupancy % is the core efficiency metric:

Average Occupancy % = Hours Played ÷ (Shift Duration × Number of Devices) × 100%

This is an average across the selected period, not a live snapshot. For most clubs, 60–70% represents a healthy operating rhythm; below 40% indicates significant untapped revenue potential.

Financial block

Metric	What it counts
Session revenue (cash + bonuses)	Total balance debits for sessions and combos (gaming balance + bonus balance), net of refunds
Paid with gaming balance	Real money only: gaming balance debits for sessions and combos, net of refunds
Paid with bonuses	Bonus balance spend on sessions
Average session value	Average ticket from gaming balance only (bonuses excluded): (debits − refunds) ÷ session count

The gap between “Session revenue” and “Paid with gaming balance” shows how much of your revenue is covered by bonuses. When measuring cash performance, use the gaming-balance line.

Occupancy: Heatmap

The Analytics → Occupancy page contains the heatmap — the main tool for identifying load patterns. It is a 7-day (Mon–Sun) × 24-hour matrix. Each cell shows the average number of occupied devices at that hour on that day of the week across the selected period. Cell values are device counts, not percentages. Deeper red means higher occupancy; light cells indicate minimal activity.

Reading patterns:

• Consistent time-of-day gap — an entire row is steadily light across all days. Morning hours 11:00–14:00 light every day of the week signal a prime candidate for a daytime tariff or off-peak promotions.
• Day-of-week gap — certain days are uniformly lighter. Monday and Tuesday consistently paler than Friday and Saturday points to an underloaded start of the week.
• Peak bottleneck — Friday and Saturday evening cells are maximally red, values close to your total device count. This signals a queue risk or an expansion opportunity.

Use the zone dropdown above the heatmap to view a specific zone in isolation — a VIP area may sit idle while the standard floor runs at capacity.

The Export button downloads the matrix as CSV — rows are days of the week, columns are hours, values are average occupied device counts.

Occupancy: Zone Table

The “Hall Occupancy” section on the same Analytics → Occupancy page shows three summary figures — Average Occupancy %, Number of Hours, and Maximum Possible Hours — plus a sortable table of each zone and device.

The table ranks zones by occupancy in descending order. Columns:

Column	Description
Zone / Device	Zone name — click to expand and see individual devices
Device count	Number of devices in the zone with sessions during the period
Hours	Total session time in hours
Occupancy %	Load for the zone or device
Session count	Number of sessions in the zone or on the device
Unique clients	Number of distinct clients (available at device level)

Only devices with at least one session in the period are shown; devices in maintenance or switched off are hidden. Sorting works on Hours, Occupancy %, Session count, and Zone/Device — click a column header to toggle direction.

Turning the Report into a Decision

1. Find weak slots — open the heatmap for the last four weeks; identify cells where average occupied devices is 1–2 while your total fleet is 20 or more.
2. Estimate lost revenue — idle hours × average session value × devices in zone. Take Average Session Value from the Clients page.
3. Match the pattern to a tool:
   • Weekday gap 10:00–16:00 → scheduled tariff that switches pricing automatically.
   • Specific day underloaded → weekly promotion or boosted bonus for that day; check back after two or three cycles.
   • VIP zone idle while standard zone is full → zone-based tariffs with an upsell prompt for the administrator.
   • Peak bottleneck with no room to expand → multipass with time restrictions or advance booking to redistribute demand.
4. Verify — two to three weeks after the change, reopen the heatmap and compare. If the weak slot is now darker, the mechanic worked. If not, the cause is not price — look at external factors such as a nearby competitor or transport access.

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See also: Hall Utilisation — Report Overview · Scheduled Tariffs · Peak / Off-Peak Pricing Strategy · Analytics: All Reports Overview