cotera

Calendly Booking Conversion Tracker

Not every booking becomes a meeting. Track which event types, days, and time slots actually convert and stop wasting availability on low-show patterns.

Booking conversionLead scoringSales analyticsMeeting intelligence

The Challenge

Your Calendly shows total bookings but not which ones actually happen. A 15-minute intro call booked for Friday at 4pm has a very different show rate than one booked for Tuesday at 10am. Without tracking completions against bookings, you are blind to which slots and event types actually convert into real meetings.

What This Prompt Does

Pull All Bookings

Fetches 90 days of events including completed and canceled

Calculate Conversion

Computes booking-to-completion rates across dimensions

Find Patterns

Identifies best and worst day, time, and type combinations

Optimize Schedule

Recommends where to focus availability for higher conversions

The Prompt

The Prompt

Task

Track how my Calendly bookings convert from scheduled to completed meetings over the past 90 days. Break down conversion rates by event type, day of the week, and time of day to identify which booking patterns actually result in real meetings.

Input

The user provides a time range (default: past 90 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 names and durations
  3. Use @Calendly/List Events With InviteesName it "Calendly/List Events With Invitees" and call it with @Calendly/List Events With Invitees for the past 90 days — pull both active and canceled events, paginate to get all results

What to Analyze

  • Total bookings vs. total completed meetings vs. total canceled
  • Booking-to-completion rate (conversion rate) overall
  • Conversion rate by event type: which meeting types actually happen?
  • Conversion rate by day of week: are Friday bookings less likely to happen than Tuesday?
  • Conversion rate by time of day: do morning meetings convert better than afternoon?
  • Invitee analysis: do events with multiple invitees cancel more or less?
  • Trend analysis: is the conversion rate improving or declining week over week?
  • Identify the highest-conversion and lowest-conversion combinations (e.g., "30-min call on Tuesday at 10am" vs. "60-min call on Friday at 4pm")

Output

Overall Conversion:

  • Total bookings, completed, canceled
  • Overall booking-to-completion rate
  • Week-over-week trend

By Event Type: For each event type:

  • Total booked, completed, canceled
  • Conversion rate
  • Rank from highest to lowest conversion

By Day of Week:

  • Conversion rate per day (Monday through Friday)
  • Best day and worst day for completed meetings

By Time of Day:

  • Conversion rate by time block (morning, midday, afternoon, late afternoon)
  • Best and worst time slots

High-Conversion Patterns:

  • Top 3 event type + day + time combinations with highest completion rates
  • What they have in common

Low-Conversion Patterns:

  • Bottom 3 combinations with lowest completion rates
  • Possible reasons and suggested fixes

Recommendations:

  • Which event types to prioritize or promote
  • Optimal days and times for booking high-value meetings
  • Suggested changes to reduce cancellation rates
  • Whether to limit availability in low-conversion slots

Example Usage

Try asking:

  • →"What percentage of my Calendly bookings actually happen? Break it down by event type."
  • →"Which days and times have the best show rates for my meetings?"
  • →"Track my booking-to-completion rate over the past 3 months and show me the trend"