Gaming Club Load Report: Read & Act

Gaming Club Load Report: How to Read It and Drive Revenue

The Load report in IZI CRM shows what percentage of seats in your hall were occupied each hour of a selected period. It lives at Analytics → Session Report → Load and is built directly from billing data: every active session counts as an occupied seat. Occupancy is calculated automatically — seats in active sessions divided by total active devices, multiplied by 100%. Select a date range and optionally a zone (VIP, standard, consoles) to get an hourly demand picture across your hall. Data is presented as a table broken down by hour; for a quick visual read, the companion Load Heatmap shows the same information as a color matrix. Owners who review this report regularly see their actual demand structure — and make pricing decisions from data, not intuition.

What the Report Shows and How to Read It

Data Structure

The report is a hour × day table: rows are hours of the day (00:00–23:00), columns are dates in the selected period. Each cell shows the occupancy percentage for that hour on that day.

What you see	What it means
% occupancy by hour	Share of occupied seats out of all active devices
Zone breakdown	Separate figures for each hall zone
Day summary row	Average occupancy for the full day
Period summary column	Average occupancy per hour across all selected days

The period summary column is the most important for decisions: it averages out random fluctuations and reveals the stable demand structure of your club.

Reading a Single Day

Open yesterday’s data. Identify the peak hours — when occupancy is highest — and the troughs. If a normally busy evening slot shows 30% instead of the usual 70%, that’s a signal: equipment issue, local holiday, weather, or a competing event nearby. Cross-referencing with the daily revenue data confirms what actually affected your AOV and total take.

Reading a Period

Select the last 28 days. The summary column on the right gives you your club’s demand profile — the hours when people actually want to visit. A typical pattern across most clubs:

Time slot	Occupancy range	Suggested action
09:00–14:00 (weekdays)	10–25%	Daytime tariff, school-age audience promotions
14:00–18:00 (weekdays)	25–50%	Student deals, afternoon passes
18:00–23:00 (weekdays)	50–75%	Main traffic, standard tariff
18:00–02:00 (Fri–Sat)	70–95%	Peak tariff, queue management
23:00–09:00 (overnight)	Depends on night tariff	Evaluate overnight shift profitability

These are illustrative ranges — your numbers will differ by neighborhood, audience, and operating hours. Compare your own periods against each other rather than against any abstract benchmark.

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Connecting Load to Revenue

Occupancy is not an end in itself. It is a tool for revenue growth through two distinct levers.

Lever 1 — Off-peak: bring in more visitors

If morning hours run at 15–20% occupancy, every additional percentage point in those hours is direct additional revenue with no price change. The formula:

Off-peak revenue potential (per hour) =
  (Target occupancy % – Current occupancy %) × Number of seats × Hourly AOV

Plug in your numbers: if you have 30 seats, your daytime hourly AOV is T, and mornings fill 5 seats instead of a potential 15 — that is 10 additional seats × T. This is the business case for a dedicated morning tariff or a school-hour promotion.

Lever 2 — Peak: increase price per seat

When peak hours consistently run at 85–95%, you cannot add more traffic — you are already full. Revenue growth here comes from AOV: a higher peak tariff, an upgrade to a premium zone, bar upsells. IZI’s pricing simulator lets you model how changing a tariff by a given percentage will shift revenue at current occupancy levels — no blind guessing required.

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Practical Step-by-Step

Step 1. Map Your Demand Profile

Open a 28-day period. Review the summary column — average occupancy per hour. Note:

• Peak hours (occupancy at its highest)
• Trough hours (occupancy below 30%)
• Transition zones (hours of rapid rise or drop)

This profile becomes the foundation for every tariff and marketing decision going forward.

Step 2. Break Down by Zone

If you have zones configured in IZI — VIP, standard, consoles — check occupancy for each separately. A common finding: the standard zone is at 90% on Friday evenings while VIP sits at 50%. That gap signals one of three things: VIP pricing is too high, guests are unaware of the upgrade option, or there is no active upsell flow at the front desk.

Step 3. Build a Tariff Matrix

Use your demand profile to set a tariff logic:

• Hours below 30% occupancy → special daytime tariff (discount to base). Goal: attract incremental traffic that would not come at the standard price.
• Hours 30–70% occupancy → standard tariff. No intervention needed.
• Hours above 85% occupancy → peak tariff (premium over base). Demand exists — you can raise price without losing traffic.

For a full guide on building a peak/off-peak pricing matrix, see Peak and Off-Peak Pricing Strategy.

Step 4. Optimize Staff Scheduling

Load data is a direct input into staffing. At forecasted occupancy above 70%, your admin needs to simultaneously open sessions, handle payments, and serve the bar — one person may not be enough. During quiet daytime hours, a single staff member is sufficient. Review your weekly demand profile and align shift schedules to it.

Step 5. Measure the Effect of Changes

Raised a tariff or launched a promotion? Compare occupancy in equivalent hours before and after. IZI stores historical data with no archive depth limit — you can compare all Tuesdays in April against all Tuesdays in May. For a detailed side-by-side of two arbitrary periods, use the Period Comparison report.

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Parametric Target: Calculating Your Personal Occupancy Goal

There is no universal norm — every club has its own demand structure. But there is a formula for setting your own target:

Target average occupancy = (Revenue target for period) / (Number of seats × Operating hours × Hourly tariff)

If you know the monthly revenue you want to hit, divide it by the product of your seat count, operating hours in the month, and average hourly tariff. The result is the occupancy percentage you need to reach that target. Compare it with actual — and you will know exactly how far you are from plan and in which hours you are falling short.

Formula with variables (substitute your own numbers):

Revenue target  = N
Number of seats = M
Operating hours = H
Average hourly tariff = T

Target occupancy = N / (M × H × T) × 100%

If the result is above 80%, your plan is aggressive — either expand the hall or revisit pricing. If it is below 50%, there is substantial untapped capacity that marketing can address.

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Related Analytics Sections

Load is one of several lenses on session data. For the full picture:

Question	Where to go
Visual load overview by day	Load Heatmap
Revenue from sessions in a period	Session Metrics
How load connects to ARPU	ARPU Tracking
Which tariffs sold during busy hours	Tariff Sales
Model the effect of a price change	Pricing Simulator
Compare two periods side by side	Period Comparison
What happened on a specific day (shift)	Shift Report