Check-in rates & no-shows
Use confirmed bookings and check-ins to understand attendance quality after the event starts.
See how many of your confirmed bookings actually showed up, and where you're losing people between booking and arrival. This page helps you separate demand from attendance so you can plan the next event more accurately.
What this view helps you answer
Use this view when you need to know:
- Which slots or days had the strongest real attendance?
- Where are you losing people between booking and arrival?
- Are cancellations happening early enough, or are you still carrying too many no-shows?
- Should you change reminders, staffing, capacity, or slot timing next time?
No-show is something you calculate
OmniLab shows Confirmed, Cancelled, Check-ins, and Check-in Rate. To get a no-show rate, subtract check-ins from confirmed bookings, then divide by confirmed bookings, for the period you are reviewing.
The metrics that matter after launch
| Metric | What it helps you answer | Practical reading |
|---|---|---|
| Confirmed | How many attendees were expected? | This is your attendance plan before people start arriving. |
| Cancelled | How much confirmed demand dropped out? | Read this separately from no-shows. A cancellation is not the same as a missed arrival. |
| Check-ins | How many people actually arrived? | This is your real attendance number. |
| Check-in Rate | What share of confirmed bookings turned into arrivals? | Use it to compare attendance quality across slots, dates, events, and ticket types. |
Work an example
Imagine a workshop shows 40 confirmed bookings, 6 cancelled, 32 check-ins, and an 80% check-in rate. From that row, you can say:
- Attendance was strong, because 32 of 40 confirmed bookings arrived.
- The no-show rate was 20%, because 8 of the 40 confirmed bookings did not arrive.
- Cancellations still matter, but they answer a different question: how many people dropped out before arrival.
Use grouping to spot the right pattern
- Slot: best for staffing, host allocation, and finding the exact session with the weakest attendance.
- Daily: best for day-of operations, because it rolls multiple slots into one attendance picture.
- Weekly: best for recurring formats such as classes, demos, or tours that run over several weeks.
- Monthly: best for high-level reporting when the event program runs across a longer campaign.
Use filters when you need a narrower answer
- If the campaign contains more than one event, start with the Event filter.
- After you narrow to one event, use Ticket Type to compare attendance quality inside that event.
How to act on what you learn
- When bookings are strong but the check-in rate is weak, review reminders, arrival instructions, and check-in timing.
- When one ticket type consistently underperforms, filter down and compare it against the rest of the event mix.
- When one daypart always shows lower attendance, adjust slot times, staffing, or capacity before repeating the format.
- When cancellations spike shortly before the event, review reminder timing and make the cancellation path easier to understand.
Use your own baselines
OmniLab does not apply a built-in no-show benchmark in this view. Compare similar event types, venues, dayparts, and ticket mixes inside your own reporting history.
Related
Booking analytics
Read slot fill, booking demand, and event or ticket-type performance before you focus on attendance.
Exports for events
Download the current event view or find the full export documentation.
Early/late window issues
Troubleshoot check-in timing problems when attendees arrive too early or too late.