Calendly No-Show Tracker
Stop guessing which meetings get skipped. Track no-shows and cancellations across your Calendly events and find patterns you can fix.
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Setup time
~5 min
Time saved
1-2 hrs/week
Difficulty
Easy
Tools
1 connected
How it works
Pull Event History
Fetches all events including canceled and no-showed
Classify Outcomes
Separates completed, canceled, and no-show events
Find Patterns
Analyzes no-show rates by day, time, and event type
Recommend Fixes
Suggests schedule changes to reduce wasted slots
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View the agent prompt
See the full instructions this agent runs on — copy, edit, or customize it
The Prompt
Task
Track no-shows and cancellations across my Calendly events for a given date range. Identify patterns by day of the week, time of day, and event type so I can reduce wasted meeting slots.
Input
The user provides a time range (default: past 30 days).
Context
Data to Pull
- Use @Calendly/Get Current UserName it "Calendly/Get Current User" and call it with @Calendly/Get Current User to get the user URI
- Use @Calendly/List Events With InviteesName it "Calendly/List Events With Invitees" and call it with @Calendly/List Events With Invitees for the specified date range, including canceled events -- paginate to get all results
- For events that were canceled, use @Calendly/Get EventName it "Calendly/Get Event" and call it with @Calendly/Get Event to pull cancellation reasons and details
What to Analyze
- Total events scheduled vs. completed vs. canceled vs. no-showed
- No-show rate as a percentage
- Cancellation rate as a percentage
- Breakdown by event type: which meeting types get skipped most?
- Day-of-week patterns: are certain days worse for no-shows?
- Time-of-day patterns: are early morning or late afternoon slots more likely to be missed?
- Cancellation reasons: what reasons do people give when they cancel?
- Lead time: how far in advance do cancellations happen?
Output
Overview: Total events, completion rate, no-show rate, cancellation rate.
By Event Type: Name, total scheduled, completed, canceled, no-showed, no-show rate.
Day-of-Week Patterns:
- No-show rate by day (Monday through Friday)
- Cancellation rate by day
- Highlight the worst and best days
Time-of-Day Patterns:
- No-show rate by hour block (morning, midday, afternoon, evening)
- Which time slots have the highest completion rate
Cancellation Analysis:
- Most common cancellation reasons
- Average lead time before cancellation
- Last-minute cancellations (under 24 hours) vs. advance cancellations
Recommendations: 3-4 actionable suggestions to reduce no-shows and cancellations based on the data.
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