Why Are My Class Sign-Ups Dropping?
The backdrop of our story — meet Aisha, and understand the problem before the data storytelling begins.
Situation — The World of Aisha’s Training Class
Aisha is a customer service supervisor in a regional contact center. Every month, she runs an internal class called “Handling Difficult Customers” for frontline agents.
Her manager Ben loves that complaints drop in the weeks after each session. HR, represented by Mei, manages the learning calendar and room bookings.
For most of the year, classes ran at 10:00 am. Agents attended during quieter call-volume blocks, and team leaders planned rosters around the sessions. Attendance was strong, feedback was high, and the class was considered a must-have in the onboarding journey.
“Three months ago, HR asked Aisha to move her class to 4:00 pm to reduce disruption during the day. The change seemed minor, so everyone agreed. No one checked the data afterward.”
Complication — The Hidden Drop in Sign-ups
Over the last three months, sign-ups for Aisha’s class have quietly fallen. She notices smaller groups, more empty chairs, and more last-minute cancellations.
Team leaders say afternoons are tough — call volumes spike, and agents are tired after a full day of escalations. Ben is worried. Complaints related to agent attitude are up. Mei is juggling many courses and needs evidence before changing time slots again.
Aisha feels caught in the middle — she senses the problem but lacks confidence with data. If she simply says “attendance feels lower,” she may not get a decision. If she pulls a complex report, she risks overwhelming Ben and Mei.
Resolution — A Clear Story and a Small Test
Aisha decides to build a small, focused data story using one simple dataset. Her goal is to show Ben and Mei how sign-ups changed when the class moved to 4:00 pm. She also wants to propose a practical test. This involves moving the class back to 10:00 am for at least some sessions.
Using the 10-step Curious Beginner path, she will work through her data one step at a time.
By the end, she wants Ben to say: “Yes, let’s try moving the class back to 10 am for the next two months.”
📊 Aisha’s Dataset
| Session | Date | Time Slot | Seats Available | Sign-ups | Show-ups | Avg Feedback |
|---|---|---|---|---|---|---|
| 1 | 14 Sep | 10:00 am | 24 | 22 | 21 | 4.7 |
| 2 | 12 Oct | 10:00 am | 24 | 23 | 22 | 4.6 |
| 3 | 9 Nov | 10:00 am | 24 | 21 | 20 | 4.7 |
| 4 | 14 Dec | 10:00 am | 24 | 22 | 21 | 4.5 |
| 5 | 11 Jan | 10:00 am | 24 | 23 | 22 | 4.6 |
| 6 | 14 Mar ▲ | 4:00 pm | 24 | 17 | 15 | 4.6 |
| 7 | 11 Apr | 4:00 pm | 24 | 150 | 13 | 4.5 |
| 8 | 9 May | 4:00 pm | 24 | 13 | 11 | 4.7 |
| 9 | 13 Jun | 4:00 pm | 24 | 14 | 12 | 4.6 |
| 10 | 11 Jul | 4:00 pm | 24 | 11 | 10 | 4.5 |
💡 Before you move to Step 1: Look at the sign-ups column. What changes after Session 5? Does anything not change? Hold that thought — you’ll use it in Step 5.
