How to Calculate Customer Visit Frequency
How to Calculate Customer Visit Frequency in a Gaming Club
Section titled “How to Calculate Customer Visit Frequency in a Gaming Club”Visit frequency is the number of unique calendar days a customer came to your club within a selected period. IZI calculates it automatically: the system merges gaming sessions and point-of-sale orders for each registered player, strips duplicate events within the same day, and produces a unique-day count. The result appears in two complementary widgets — Visit Funnel and Visit Frequency Distribution — found under Analytics → Clients. The funnel answers “how many customers came back at least N times”; the distribution answers “how is the audience spread across activity ranges.” Together they give a complete picture of retention without building manual cohorts. For an owner this is a health indicator for the customer base; for an administrator it is a segmentation tool for targeted promotions.
Where to Find the Report in the CRM
Section titled “Where to Find the Report in the CRM”- Select your club in the left sidebar.
- Go to Analytics → Clients.
- Set the date range using the date picker in the top-right corner.
- Scroll down past the Client Flow and Revenue & ARPU blocks — you will see two widgets: Visit Funnel and Visit Frequency Distribution.
The selected period affects all calculations. A longer period accumulates more visits per customer. For operational decisions use a 30-day window; for seasonal comparisons use a quarter.
How the Visit Funnel Works
Section titled “How the Visit Funnel Works”The funnel is a horizontal bar chart with five cumulative levels:
| Label | Reads as |
|---|---|
| ≥1 visit | All unique customers in the period |
| ≥2 visits | Returned at least once |
| ≥3 visits | Returned at least twice |
| ≥4 visits | Consistently active |
| ≥5+ visits | Loyalist core |
Each level is a subset of the one above it. The gap between levels shows how many customers dropped off after a given number of visits. A large gap between ≥1 and ≥2 means the club is not converting first-time guests into returning ones.
Practical benchmark. Take the ≥1 value (all customers) and the ≥3 value. If ≥3 is below 20% of ≥1, the club has a first-return problem. For a mature club, ≥3 visits typically represents 35–50% of the total base over a 30-day period.
How the Visit Frequency Distribution Works
Section titled “How the Visit Frequency Distribution Works”The distribution is a table with five ranges:
| Range | Segment meaning |
|---|---|
| 1 visit | One-time guests |
| 2–3 visits | Potentially returnable |
| 4–6 visits | Regular visitors |
| 7–10 visits | Active regulars |
| 10+ visits | Super-loyalists |
For each range the system shows:
- Customers — the absolute number of customers whose total unique-day count fell within that range during the period.
- Share (%) — that segment’s percentage of all customers in the period.
You can export the table to CSV directly from the interface using the button in the top-right corner of the card.
Step-by-Step Frequency Diagnostic
Section titled “Step-by-Step Frequency Diagnostic”Step 1. Choose a period
Section titled “Step 1. Choose a period”Start with the last 30 days. This is a neutral baseline that is not distorted by seasonal peaks.
Step 2. Record the one-time vs repeat split
Section titled “Step 2. Record the one-time vs repeat split”Find the share of the “1 visit” range. If it exceeds 60%, most customers visit once and do not return. This is normal for clubs with high tourist footfall but is a warning signal for neighbourhood clubs.
Step 3. Measure your loyalist core
Section titled “Step 3. Measure your loyalist core”Add the shares for the 4–6, 7–10, and 10+ ranges. This is your loyal audience. A stable club should see this combined figure at 25–30% or higher.
Step 4. Compare with the previous period
Section titled “Step 4. Compare with the previous period”Switch the date picker to the equivalent previous period and note or export the numbers. Growth in the 4+ visit segments means the base is maturing and retention is improving.
Step 5. Build segments for outreach
Section titled “Step 5. Build segments for outreach”| Segment | Recommended action |
|---|---|
| 1 visit | Send a reminder one week after the visit |
| 2–3 visits | Offer an incentive for the next visit (top-up bonus) |
| 4–6 visits | Introduce the loyalty program |
| 7+ visits | VIP recognition, exclusive offers |
How IZI Calculates a Visit Technically
Section titled “How IZI Calculates a Visit Technically”The system merges two data streams: gaming sessions and cashier orders. For each authenticated player it selects all events within the chosen period, extracts the calendar date from each event, and removes duplicates within the same day. The final count is the number of unique days.
A few edge cases to keep in mind:
- A customer who plays from 23:00 to 07:00 the next morning accumulates 2 unique days and therefore 2 visits.
- A customer who comes in three times on the same Friday counts as 1 visit.
- Unregistered customers (no phone number on file) cannot be counted by unique visits — they have no stable identifier. Both widgets count only authenticated players. This is an additional argument for encouraging guests to register.
Connection to Other Metrics
Section titled “Connection to Other Metrics”Visit frequency works best alongside a few other indicators:
- ARPU (average revenue per customer) — reading both together adds depth: a high-frequency customer with low ARPU may be coming only for promotions, while a high-frequency customer with high ARPU is your best segment.
- Average session length — the 1-visit segment may have very long sessions (a first-timer exploring the club), while the 10+ segment tends to have short, habitual visits. These are different behavioral profiles.
- Retention — visit frequency is a practical way to measure retention within a specific period without building full cohorts from the first-visit date.
Acting on the Results
Section titled “Acting on the Results”The report itself is a diagnostic tool. The right action depends on the shape of your base.
If 70%+ of customers have 1 visit: the problem is either the first impression or the absence of a reason to return. Check whether the club has a loyalty program, whether a top-up bonus is offered at registration, and how easily a guest can find and book the club again.
If the core (4+ visits) is growing month over month: the base is maturing. This is a good time to test subscriptions and packages for regulars — creating tariffs with zone-based structure can lock in their habit with a predictable offer.
If the 10+ visit share is significant: these are super-loyalists. They rarely need a discount — recognition and priority service matter more to them than price reductions.
The Visit Funnel and the distribution table share the same selected period. To compare two periods, switch the date picker manually and record the numbers from each run. There is no built-in period-comparison mode in these widgets.
Frequently asked questions
What is visit frequency and why does it matter?
Visit frequency is the number of unique calendar days a customer visited your club within a selected period. It measures engagement depth — one-time guests versus a regular audience. Clubs where more than 30% of customers make 4+ visits per month tend to hold revenue more steadily during slow seasons.
Where do I find visit frequency in IZI?
Go to Analytics → Clients. Scroll past the Client Flow and Revenue & ARPU blocks to find two widgets: Visit Funnel and Visit Frequency Distribution.
How does IZI count visits?
The system merges session and order events for each registered player, extracts the calendar date from each event, and deduplicates within a single day. The result is the number of unique days the player was present. Multiple sessions on the same day count as one visit.
What is the difference between Visit Funnel and Visit Frequency Distribution?
The funnel shows cumulative counts: how many customers made at least N visits (≥1, ≥2, ≥3…). This reveals drop-off. The distribution table shows how many customers fall into each range (1, 2–3, 4–6, 7–10, 10+) and their share — useful for segmentation.
What do the segments 1 / 2–3 / 4–6 / 7–10 / 10+ visits mean?
1 visit — one-time guests, typically the largest and most concerning segment. 2–3 — potentially returnable. 4–6 — regular visitors. 7–10 and 10+ — loyalists who form the core audience.
Can I export visit frequency data?
Yes. The Visit Funnel card has a chart export button; the distribution card lets you export the table as CSV. The export includes the range, customer count, and percentage share.
How does the selected period affect the numbers?
A longer period accumulates more visits per customer. A customer who visits twice a week will land in the 7+ range over a month but in the 1-visit range over a single week. Always compare periods of equal length.