Why has Douyin's average watch time per user decreased by 20% over the last month? What factors might be contributing to this reduction?

Introduction

Douyin's 20% decrease in average watch time per user over the last month is a significant issue that demands immediate attention. This metric is crucial for Douyin's success as it directly correlates with user engagement, content quality, and ultimately, the platform's revenue. I'll approach this problem systematically, starting with clarifying questions, then moving through hypothesis generation, root cause analysis, and finally, proposing solutions and next steps.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a seasonal effect. Has this decrease coincided with any major holidays or events in China?

Why it matters: Seasonal trends can significantly impact user behavior. Expected answer: No major holidays during this period. Impact on approach: If confirmed, we'd focus more on internal factors.

• Considering user segments, I'm curious if this decrease is uniform across all user groups. Have you noticed any particular demographics or user types more affected than others?

Why it matters: Identifying specific affected groups can narrow down potential causes. Expected answer: Younger users (18-25) show a more significant decrease. Impact on approach: We'd investigate factors specifically affecting this age group.

• Regarding recent changes, have there been any major updates to the app or algorithm in the past 1-2 months?

Why it matters: Product changes often have unintended consequences on user behavior. Expected answer: A recommendation algorithm update was implemented 6 weeks ago. Impact on approach: We'd closely examine the impact of this algorithm change.

• Thinking about content, has there been any shift in the type or quality of content being produced or promoted on the platform recently?

Why it matters: Content is the core of Douyin's offering and directly impacts watch time. Expected answer: No significant changes noted in content trends. Impact on approach: We'd look more closely at how content is being served to users.