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Gaming Club Network Dashboard in IZI

Published: · IZI Team

The aggregate network dashboard is the primary management tool for a multi-club owner. The dashboard’s job: answer the question “is everything OK at each club and where are there anomalies” in 5–10 minutes, without drilling into each location individually.

Organisation level — aggregate data for the whole network: total revenue, total traffic, overall client base. Gives the big picture.

Club level — detailed data for a specific club: hourly utilisation, AOV, detailed rate breakdown, bonus analytics. Provides the detail needed for decisions.

Effective workflow: view aggregate level → spot an anomaly → drill into the specific club for diagnosis.

What to look at: each club’s revenue for the period, trend vs previous period.

How to interpret:

  • Club A: +12% vs last week → normal or growth
  • Club B: -18% vs last week → anomaly, needs diagnosis
  • Club C: stable, no change → stagnation, growth potential not realised

More on club comparison → Comparing Network Clubs by Metrics.

What to look at: utilisation heatmap for each club, pattern comparison.

How to interpret: if club A has 45% daytime utilisation but club B has 15% in a similar-area location — this is a signal to either study what club A does (better off-peak marketing?) or launch a daytime bonus at club B.

What to look at: each club’s AOV, trend over the past 4 weeks.

Signals: AOV dropped → issue with loyalty programme or rates. AOV grew → programme is working, can replicate to other clubs.

What to look at: how many new clients came to each club in the period, what % returned within 30 days.

Signals: high new client intake + low retention → club acquires but doesn’t retain. Low intake + high retention → good base, needs marketing for growth.

Daily (5 minutes):

  • Yesterday’s revenue per club
  • Flags: any club with an anomalous drop (>20% vs same day last week)
  • Technical incidents from manager reports

Weekly (20–30 minutes):

  • Week’s revenue by club vs previous week
  • Hourly and day-of-week utilisation breakdown — new patterns
  • AOV trend
  • New clients and early retention signals

Monthly (1–2 hours):

  • D30 retention by cohort
  • Churn and reactivation
  • AOV 3-month trend
  • All-club comparison on key metrics — who is an outlier in both good and bad directions, and why

Signal: one club significantly underperforms on revenue

Section titled “Signal: one club significantly underperforms on revenue”

Diagnosis: first rule out external causes (nearby construction, competitor opened, location-specific seasonality). If no external causes — compare hourly utilisation, AOV, new clients. The problem is usually in one of the three.

Signal: all clubs declining simultaneously

Section titled “Signal: all clubs declining simultaneously”

This is seasonality or an external factor (school holidays, public holidays, general economic slowdown). Tool: seasonal promotions, special events. Methodology → Seasonal Promotions for Clubs.

Signal: one club significantly outperforms the rest

Section titled “Signal: one club significantly outperforms the rest”

This is your best practices laboratory. Study what that club does differently: which Automations are active, how the admin operates, what programme they’re running. Replicate to others.

For deeper analysis, export data from IZI to CSV/Excel. This allows:

  • Building cross-club pivot tables
  • Comparing client cohorts between clubs
  • Building forecast models from historical data

Related: Comparing Clubs by Metrics · Switching Between Clubs · How to Scale to a Second Location

Frequently asked questions

How do you view aggregate analytics for all network clubs?

In IZI CRM, select the organisation level (not a specific club) in the left panel. The Analytics section shows aggregate data for the whole network: total revenue, total traffic, overall client base.

Can you compare two network clubs on one screen?

Switch between clubs via the left panel — period filters are preserved, enabling quick comparison of the same period across two clubs. For a single combined view, use data export and a pivot table outside IZI.

Which metrics matter most to track for a network?

For a network owner, key metrics are: revenue per club (absolute and comparative), hourly utilisation (reveals off-peak patterns), AOV, D30 newcomer retention, new clients. Comparing these between clubs identifies outliers and growth points.

How often should you check the aggregate dashboard?

Operational metrics (revenue, utilisation) — daily for each club, 5 minutes. Weekly comparative metrics review — 20–30 minutes. Monthly deep analysis (retention, churn, AOV trend) — 1–2 hours.

Does organisation-level analytics automatically include all clubs' data?

Yes. When viewing analytics at the organisation level, data from all clubs is included automatically. A new club added to the organisation immediately appears in aggregate analytics.