How to Track Customer Visit Frequency in IZI

How to Track Customer Visit Frequency in IZI

Visit frequency is one of the core retention metrics for a gaming or computer club: it tells you how regularly customers come back. In IZI, this metric lives under Analytics → Client Report, in the retention charts section. You get two complementary views: the Visit Funnel and the Visit Frequency Distribution. The funnel answers “how many customers came back at least N times?” The distribution answers “how is our audience spread across visit-count buckets?” Together they give a complete loyalty picture for any selected period and help you separate one-time visitors from your regular core. Understanding this picture directly informs decisions about customer segments, loyalty programs, and promotional timing.

What Counts as a Visit

In IZI, a visit is a unique calendar day on which a customer completed at least one gaming session or placed a bar order. Multiple sessions on the same day count as one visit.

This distinction matters in practice: if a player arrives on Friday evening and leaves early Saturday morning, that spans two calendar days and counts as two visits. IZI merges session and bar-order data, deduplicates by calendar day per player, and returns the total number of unique visit days within the selected period.

This approach reflects real customer behavior more accurately than counting raw sessions. A customer who buys three back-to-back tariffs on Friday night appears as one visit — not three.

Where to Find the Report

Path in the CRM: Analytics → [click your club] → Client Report → retention charts section.

The page shows two blocks stacked in order:

1. Visit Funnel — a horizontal bar chart.
2. Visit Frequency Distribution — a table with visit-count buckets.

Both blocks respond to the same date filter at the top of the page. Change the period and both charts recalculate automatically.

Visit Funnel

What It Shows

The funnel displays the cumulative number of customers who reached or exceeded each visit threshold during the selected period:

Row	Meaning
≥ 1 visit	All unique customers in the period (total audience)
≥ 2 visits	Customers who returned at least once
≥ 3 visits	Customers showing regular behavior
≥ 4 visits	Consistently engaged customers
≥ 5+ visits	Loyal core audience

The gap between ≥ 1 and ≥ 2 is the share of customers who visited exactly once — your “first-visit churn.” A steep drop between row one and row two is typical for clubs with high walk-in traffic, but it signals work to do on the first impression and the conversion to a second visit.

How to Read It

Focus on the slope of the funnel. If 70% of your audience drops off between ≥ 1 and ≥ 2, that is common for high-footfall locations, but it points to first-experience improvements. If the sharpest drop is between ≥ 2 and ≥ 3, the second visit is not becoming a habit — check your loyalty mechanics and segment strategies and the interval between offers.

Visit Frequency Distribution

What It Shows

The distribution table divides the entire period audience into exact buckets:

Bucket	Interpretation
1 visit	One-time visitors
2–3 visits	Occasionally returning
4–6 visits	Periodic customers
7–10 visits	Regular customers
10+ visits	Club core — most loyal

Each bucket shows two figures: the absolute number of customers and the percentage share of the total period audience.

How to Read It

A healthy club sees its audience gradually shift toward higher buckets when you compare periods over time. If 80% of your audience stays in the “1 visit” bucket month after month, that is not automatically a sign of a failing club — it may reflect tourist-heavy foot traffic, one-off events, or gaps in your re-engagement mechanics. The number gives context; the trend gives direction.

Compare distributions month over month: if the share of “7–10” is growing, your retention mechanics are working. Export the table to CSV using the Export button in the top-right corner of the block.

Step-by-Step Instructions

1. Log in to the CRM and open the target club.
2. Navigate to Analytics → Client Report.
3. Set the date range using the top filter (for example, the last 30 days or the previous calendar month).
4. Scroll to the Visit Funnel block.
   • Note how many customers reached ≥ 2 visits. This is your primary return rate.
   • Record the share of your loyal core (≥ 5+ visits) relative to the total audience (≥ 1 visit).
5. Continue scrolling to the Visit Frequency Distribution block.
   • Identify which buckets hold the largest share.
   • Export the table if you need the data in a spreadsheet.
6. Switch the date filter to the previous equivalent period (for example, the month before) and repeat steps 4–5.
7. Compare bucket shares across both periods — that delta is your retention trend.

Formulas for Your Own Calculations

If you want to extend the IZI data with custom calculations:

First-return rate:

Return % = (customers with ≥2 visits / customers with ≥1 visit) × 100

Loyal core share:

Core % = (customers with ≥5+ visits / customers with ≥1 visit) × 100

Average visit frequency for the period — not shown directly in this block, but derivable from the key metrics dashboard combined with the unique customer count.

Connection to Other Metrics

Visit frequency does not exist in isolation. It interacts with several other indicators available in IZI:

• Sessions per player — a related metric counting sessions rather than days. It will be higher than visit frequency whenever customers play multiple sessions in a single visit.
• Churn Rate — the other side of frequency: a customer who has not returned in 30+ days moves into the churn category.
• Retention cohorts — lets you view visit frequency broken down by first-visit cohort rather than just by period, giving a lifecycle view.
• ARPU — high visit frequency does not automatically mean high revenue; cross-reference it with the revenue and ARPU report for a complete picture.

Common Analysis Mistakes

Confusing a session with a visit. In IZI, a visit is a unique day; a session is a single gaming slot. Three sessions in one evening equal one visit in the report.

Comparing periods of different lengths. A customer has more calendar days available in a quarter than in a month, so raw visit counts will naturally differ. Always compare equal-length time windows.

Ignoring seasonality. Visit frequency rises naturally around holidays and weekends. The most meaningful comparison is the same period in the prior year or a rolling four-week average.

Reading absolute numbers without the percentage. Fifty customers in the “7–10” bucket means something different at a 100-customer club versus a 1,000-customer club. Always check the share column alongside the absolute count.

Acting on the Data

The report directly suggests what to do next:

• Large share in the “1 visit” bucket → work on the first-visit experience: onboarding flow, prompting registration, a balance top-up bonus on the first day.
• Sharp drop between ≥ 2 and ≥ 3 → activate customers after their second visit: a reminder message, a personalized offer timed to when they typically return.
• Stable loyal core at ≥ 5+ → these are your VIP customers; engage them separately with exclusive events, priority booking, and expanded privileges.
• Declining share of “7–10” and “10+” quarter over quarter → a sign that regulars are drifting away; review whether the value proposition for loyal customers is keeping pace with their expectations.

IZI surfaces the picture — the next steps belong to you and your team.