What caused the sudden 30% increase in customer support tickets for Rentomojo's appliance rentals over the past week?

Introduction

The sudden 30% increase in customer support tickets for Rentomojo's appliance rentals over the past week is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term fixes and long-term strategic implications.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a seasonal factor. Has there been any notable change in rental patterns or customer demographics recently?

Why it matters: Seasonal trends could explain the surge and inform our solution approach. Expected answer: No significant seasonal changes noted. Impact on approach: If confirmed, we'd focus more on internal factors.

• Considering the specificity of the increase, I'm wondering about recent product updates. Have there been any changes to the appliance lineup or rental terms in the past month?

Why it matters: Recent changes could directly correlate with the increase in support tickets. Expected answer: A new smart refrigerator was added to the lineup two weeks ago. Impact on approach: This would shift our focus to potential issues with the new product.

• Given the nature of support tickets, I'm curious about the types of issues being reported. Can you provide a breakdown of the most common categories of these new support tickets?

Why it matters: Understanding the nature of the issues helps pinpoint potential causes. Expected answer: Majority related to setup difficulties and connectivity problems. Impact on approach: We'd prioritize investigating product usability and technical issues.

• Thinking about operational changes, has there been any recent modification to the support ticket system or how tickets are categorized?

Why it matters: Changes in measurement or categorization could artificially inflate numbers. Expected answer: No recent changes to the support ticket system. Impact on approach: This would rule out data anomalies and focus on actual customer issues.