Calendly Scheduling Analytics

Task

Analyze my Calendly scheduling data for the past 30 days. Give me a breakdown of meeting volume, cancellation rates, most popular event types, busiest days, and whether my availability schedule matches my actual booking patterns.

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 Event TypesName it "Calendly/List Event Types" and call it with @Calendly/List Event Types to get all event types with durations and active status
3. Use @Calendly/List EventsName it "Calendly/List Events" and call it with @Calendly/List Events for the past 30 days (both active and canceled) -- paginate to get all results
4. Use @Calendly/List Availability SchedulesName it "Calendly/List Availability Schedules" and call it with @Calendly/List Availability Schedules to see configured availability windows

What to Analyze

• Total meetings held vs. canceled
• Cancellation rate as a percentage
• Breakdown by event type (which meeting types are most popular?)
• Busiest day of the week
• Average meetings per day
• Peak booking hours
• Whether availability windows are well-utilized or have dead spots
• Comparison of active event types vs. those that never get booked

Output

Overview: Total meetings, cancellation rate, average per day.

By Event Type: Name, count, percentage of total, average duration.

Scheduling Patterns:

• Busiest days of the week
• Peak hours for bookings
• Trends (are meetings increasing or decreasing week over week?)

Availability Analysis:

• Which availability windows get the most bookings
• Suggested adjustments to availability based on booking patterns
• Event types that could be consolidated or retired

Recommendations: 2-3 actionable suggestions to optimize scheduling.