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Product Management Improvement Question: Enhancing iQiyi's personalized content recommendations for increased user engagement

Asked at iQiyi

15 mins

How can we enhance iQiyi's personalized content recommendations to increase user engagement?

Product Improvement Medium Member-only
Product Strategy Data Analysis User Segmentation Streaming Media Entertainment Technology
User Engagement Data Analytics Machine Learning Content Personalization Streaming Platforms

Introduction

To enhance iQiyi's personalized content recommendations and increase user engagement, we need to dive deep into our user segments, their pain points, and potential solutions. I'll walk you through my approach to this challenge, focusing on data-driven insights and innovative strategies.

Step 1

Clarifying Questions (5 mins)

  • Looking at iQiyi's position in the streaming market, I'm thinking about the competitive landscape. Could you share insights on how our recommendation system currently performs compared to major competitors like Tencent Video or Youku?

Why it matters: Helps identify gaps and opportunities in our recommendation algorithm. Expected answer: We're slightly behind in terms of user satisfaction with recommendations. Impact on approach: Would focus on rapid iteration and innovative features to leapfrog competitors.

  • Considering the diverse content library on iQiyi, I'm curious about user behavior across different genres. Can you provide data on how users typically navigate between content categories and how this impacts their engagement?

Why it matters: Informs how we structure and present recommendations across genres. Expected answer: Users tend to stick within 2-3 preferred genres but occasionally explore new categories. Impact on approach: Would design a recommendation system that balances familiarity with discovery.

  • Given the importance of user data in personalization, I'm wondering about our current data collection and analysis capabilities. What types of user data are we currently leveraging for recommendations, and are there any limitations or privacy concerns we need to consider?

Why it matters: Determines the scope and depth of personalization we can achieve. Expected answer: We use viewing history, ratings, and basic demographics, but lack deeper behavioral insights. Impact on approach: Would explore ways to ethically gather more nuanced user data to improve recommendations.

  • Thinking about iQiyi's broader business goals, how does improving personalized recommendations align with other strategic initiatives? Are there specific KPIs we're aiming to impact beyond user engagement?

Why it matters: Ensures our solution aligns with overall company objectives. Expected answer: We're looking to increase subscription conversions and reduce churn rates. Impact on approach: Would focus on recommendations that drive both engagement and monetization.

Tip

Let's take a quick minute to organize our thoughts before moving on to user segmentation.

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