Why has the customer satisfaction rating for DiDi Food delivery declined from 4.5 to 3.8 stars in Guangzhou over the last two weeks?

Introduction

The recent decline in DiDi Food's customer satisfaction rating in Guangzhou from 4.5 to 3.8 stars over a two-week period is a critical issue that demands immediate attention. This significant drop could have far-reaching consequences for our market position and user retention. I'll approach this problem systematically, focusing on identifying the root cause, validating hypotheses, and developing both short-term and long-term solutions.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might have been a recent change in our service. Has there been any significant update to the DiDi Food app or backend systems in the past month?

Why it matters: Recent changes often correlate with sudden metric shifts. Expected answer: Yes, there was a major app update two weeks ago. Impact on approach: If confirmed, we'd focus on the update's features and potential bugs.

• Considering the localized nature, I'm wondering about Guangzhou-specific factors. Have there been any local events or changes in Guangzhou that could affect food delivery services?

Why it matters: Local factors could explain the geographically limited impact. Expected answer: No significant local events, but there's been an increase in food safety concerns. Impact on approach: We'd investigate our restaurant vetting process and user feedback mechanisms.

• Given the magnitude of the drop, I'm curious about the distribution. Is the rating decline uniform across all user segments, or are certain groups more affected?

Why it matters: Helps identify if the issue is universal or segment-specific. Expected answer: The decline is more pronounced among frequent users. Impact on approach: We'd focus on understanding changes in the experience of power users.

• Considering potential data anomalies, has there been any change in how we collect or calculate customer satisfaction ratings?

Why it matters: Ensures the metric itself isn't the source of the perceived problem. Expected answer: No changes in the rating system or calculation method. Impact on approach: We'd rule out measurement issues and focus on actual user experience factors.