Understanding Customer Intelligence
Behavior data is surfaced where you decide on bookings, not in a separate mystery module.
Video tutorial coming soon
Overview
WellBooked surfaces guest reliability in two main places. On the customer detail panel, the Analytics section summarizes total bookings, show-up rate, on-time rate, and no-show count derived from past intents at your place. On the Reservations workflow, approving a pending request can open a modal with user metrics pie charts when the guest has enough history, showing diligence categories such as confirmed, seated, no-show, and punctuality bands. The main customer table repeats headline rates so you can scan for risk before opening a profile. These signals support judgment; they do not auto-approve or auto-reject bookings by themselves in the UI described here.
Start from the customer list
Sort mentally using show-up and on-time columns and no-show counts for quick triage.
Open Analytics in the profile
Confirm totals and percentages in context with tier and notes.
Cross-check booking history
Read individual statuses and sources to see whether a low rate comes from many cancels, true no-shows, or edge cases.
When approving, read the metric cards
If the approve modal shows overall and place-specific charts, compare them before accepting high-risk tables or peak times.
Watch for warnings
The product can call out elevated no-show counts when data exists, take that as a prompt, not a verdict.
Tips & Best Practices
Trends beat one-offs
A single late arrival matters less than a pattern across many visits.
Align with policy
Decide as a leadership team how metrics influence deposits, hold times, or VIP treatment.
Privacy
Share reliability context only with roles that need it at the host stand.
Use context, not just scores
Combine reliability metrics with booking details like party size, time, and source before making a decision.