Describe

• The recommendation algorithm curates a personalized list of videos for each user based on their watch history, likes, and search patterns.
• Its goal is to increase user engagement by suggesting relevant content that the user might be interested in.

Feature Goals

• Increase user engagement.
• Increase the diversity of content consumed.
• Increase session length.
• Drive discovery of new content creators.

Success Metrics

Is the feature discoverable and are users using the feature as intended?

• % of users interacting with the recommendations.
• Click-through rate of recommended videos.

Is usage of the feature growing?

• Growth in the number of recommended videos watched per user.

What is driving usage of the feature?

• Correlation between user behavior (like, share, subscribe) and recommendation algorithm.
• Watch time per recommended video category or type.

Does the feature increase engagement?

• Increase in average watch time per session.
• Increase in frequency of user visits.

Does the feature lead to the discovery of new content?

• Number of new channels discovered per user via recommendation.
• Subscriptions to new channels per user based on recommendations.