Analytics answers the questions an owner actually decides on: whether this month beats last, who is busy, how many customers are new, when the rush is, and how far ahead people book. It is in the free wordpress.org plugin, and it covers every booking engine on the site at once.
Where: WP Admin → Tiger Booking → Analytics.
Choosing a period
Pick Last 7 days, Last 30 days or Last 90 days, or set an explicit start and end date. Thirty days is the default.
Every headline figure is shown against the immediately preceding period of the same length, so a 30-day view compares to the 30 days before it. That is what the up and down arrows mean — they are period-over-period, not year-over-year.
Filtering to one engine
A site running several engines can scope the whole screen to one of them. That matters: a venue running a hotel and a restaurant off one install has two businesses whose averages mean nothing blended together. With the filter off, a Revenue by Business breakdown shows each engine separately; with it on, the headline figures are that engine’s. If a filter cannot be resolved the screen falls back to the whole business and says so, rather than showing figures for a scope you did not get.
The headline figures
- Total Revenue and Total Bookings for the period.
- Avg Booking Value — revenue divided by bookings.
- New Customers and Returning Customers — a split, not a total, so you can see whether growth is coming from reach or from loyalty.
- Cancellation Rate — cancellations as a share of everything placed in the period, cancelled bookings included in the denominator. That is why it cannot exceed 100% on a bad week.
- No-shows — a count.
- Fees Recovered — late-cancellation and no-show fees actually collected. Always zero on the free plugin, which has no payment gateway to collect with.
- Still Owed — outstanding balances across the period.
- Next 7 Days — bookings whose work falls in the coming week. Forward-looking, unlike everything above it.
- Busiest Slot — the day and hour with the most demand.
Two clocks, kept apart
This is the single most useful thing to understand about the screen. Two different dates are in play and mixing them would be a lie, so the split is deliberate and consistent:
- When the booking was taken drives revenue, booking counts, the new-versus-returning split, and every period-over-period comparison.
- When the work happens drives staff load, the demand heatmap and lead time.
So a busy Tuesday in your heatmap is a Tuesday people attend, while a revenue spike is a day people booked.
Staff load
For each person: bookings, revenue, hours booked and hours available, presented as booked hours against available hours. Availability comes from working hours, and where you run a staff roster it comes from actual shifts instead. Somebody at 95% has no room to sell; somebody at 20% has capacity you are not filling.
Demand heatmap and lead time
The heatmap plots demand by day and hour so you can see the rush at a glance — and see the hours you are open but nobody wants, which is usually the more actionable half.
Lead time buckets how far ahead people book: Same day, 1–2 days, 3–7 days, 1–4 weeks and 30+ days. A business that is mostly same-day needs different staffing from one booked out a month.
Performance
Everything on this screen is aggregated on the server and sent as small summaries — the page never receives raw booking rows to add up. That is what keeps it usable on a site with tens of thousands of bookings.
Troubleshooting
Revenue is zero but I have bookings.
Revenue counts money recorded against bookings. On the free plugin there is no online payment, so unless you are setting payment status by hand from the booking detail screen, there is nothing to total. Bookings, customers, staff load, heatmap and lead time all still work.
Fees Recovered is always zero.
Late-cancellation and no-show fees need a payment gateway to collect, and gateways ship in the Tiger Booking Pro add-on. On the free plugin the figure is correct at zero.
A staff member shows no utilisation.
Utilisation needs both halves: hours booked, and hours available. Someone with no working hours set under Availability has no denominator, so nothing to show.
The engine filter didn’t change anything.
An engine the site cannot resolve degrades to the whole business, and the screen reports the scope it actually applied. Check the engine is installed and active under Settings → Modules.
Numbers differ from my bookings list.
Cancelled and other dead statuses are excluded from revenue and booking counts, but cancellations are added back into the denominator of the cancellation rate. Check which clock a figure uses, too — booked-on versus happens-on will not agree for a period with a lot of forward bookings.