cotera

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.

No-show trackingCancellation analysisMeeting analyticsSchedule optimization

The Challenge

You manually check your Calendly dashboard to see which meetings got canceled or no-showed. There is no easy way to see patterns — which days have the most cancellations, which event types get skipped most, or whether certain time slots are chronically problematic. You are guessing instead of knowing.

What This Prompt Does

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

The Prompt

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

  1. Use @Calendly/Get Current UserName it "Calendly/Get Current User" and call it with @Calendly/Get Current User to get the user URI
  2. 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
  3. 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.

Example Usage

Try asking:

  • →"Show me my no-show rate for the past month by event type"
  • →"Which days and times have the most cancellations on my Calendly?"
  • →"Track my Calendly no-shows and tell me what patterns you see"