TikTok's ForYou Page Recommendation System

Requirements Clarification & Assessment

Before diving into designing the recommendation system, it's crucial to clarify the requirements and assess what needs to be achieved:

• Objective:

  • Increase user engagement by maximizing average retention time and time spent on the platform.
  • Enhance user satisfaction by suggesting relevant and interesting content.

• Target Audience:

  • Diverse user base with varying interests, age groups, and geographical locations.

• Key Performance Indicators (KPIs):

  • User retention rate
  • Average session duration
  • Click-through rate on recommended videos
  • User satisfaction scores (e.g., through feedback surveys)

• Constraints and Considerations:

  • Data privacy and compliance with regulations such as GDPR.
  • Scalability to handle millions of users and videos.
  • Real-time processing to deliver instant recommendations.

• Data Availability:

  • User interaction data (likes, shares, comments)
  • Video metadata (tags, categories, creator info)
  • User profile data (age, location, preferences)

• Potential Challenges:

  • Cold start problem for new users and videos.
  • Balancing between popular and niche content.
  • Avoiding echo chambers and promoting content diversity.