From 6 Months of Declining Demos to KPI Clarity: 1 Field, 20% No-Shows, 30% Reschedules, 14-Day Lag Exposed

TL;DR

• Found a tracking gap: SDRs and Sales were measuring different dates

• Reality: 30% of meetings were rescheduled by around 2 weeks, extending the sales cycle, and 20% no-shows.

• Simple solution, implementing one date field of "Original Booking Date" to track when a meeting was booked.

Context

At Craft.io, the sales team reported a decline in meetings, and the quick fix suggested was to update the outbound sequence. I wanted to investigate the underlying cause, and what I discovered is:

1. The SDR (me) was tracking meetings using "Meeting Booked Date" - the day I scheduled the meeting

2. The sales team was tracking meetings using "Meeting Done Date" - when the demo actually occurred

This created three predictable problems:

1. If I booked for next month, I counted it now, they counted it next month.

2. If a demo got rescheduled, it created a gap between the booked and held dates

3. If a demo was canceled or a no-show, it remained on my meeting list but was not reported anywhere.

This, over a few months, led to a compounded data misalignment disaster.

Part 1 - The Solution

I created a third date field: "Original Booking Date" to capture the exact date I first scheduled the meeting.

With all 3 fields in place, we could now track:

• How many meetings I booked each month vs. when they actually occurred

• Whether meetings happened on the originally scheduled date

• How far out were rescheduled meetings being pushed

What the data revealed:

•  ~20% no-show rate that wasn't visible in either system

• ~30% reschedule rate with an average delay of 2+ weeks.

• The issue labeled as "decline" was not related to the pipeline itself, but rather a scheduling friction problem.

The impact:

•  Sales, marketing, and SDR teams are now aligned on the same KPIs.

• We could proactively address no-shows and reschedules.

• Leadership had visibility into the actual length of the sales cycle.

Part 2 - Simulated Analysis  - The Original Investigation (Recreated)

The Takeaway from the AI data generated