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)
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.
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.
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.
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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