Accessing the stats page
In the admin portal, open Stats (or Reporting). You’ll be able to filter by store and date range. Start broad (last 7 days) and narrow once you spot patterns.
Date range presets
Common presets include 24h, 7d, 30d, and Custom. Use:
- 24h for diagnosing “today feels chaotic”
- 7d for week-to-week staffing
- 30d for trend spotting (seasonality, school holidays)
- Custom for promotions or specific periods
Understanding wait time metrics
Wait time metrics are only as good as the data. Encourage barbers to tap Start/Done consistently.
Average
Useful, but can be skewed by outliers (one wild Saturday can inflate it).
P50 (median)
The “typical” experience. Half of customers waited less than this, half waited more.
P95
The “bad day” experience. If P95 is high, it means a chunk of customers are having a rough time — often due to peak-hour understaffing.
Service breakdown chart
This shows what customers are actually buying: haircuts vs fades vs beard work. If fades are trending up, build more time into schedules and ensure booking slots reflect reality.
Barber performance table
Use this responsibly. It typically includes:
- Tickets completed
- Average service time
- No-show rate
Don’t treat “fastest” as “best”. Context matters: complex services take longer, and junior staff may need more time. Use the table to spot training needs and staffing balance — not to race.
Busiest hours heatmap
The heatmap is the most actionable view. It tells you when demand spikes. Aim to have more barbers active before the spike begins (not after it’s already red).
No-show rate and what to do about it
If no-shows are high:
- Confirm phone details during booking.
- Consider reminder messaging (if your workflow supports it).
- For repeat offenders, apply your shop policy (deposit, stricter cancellation rules, etc.).
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