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Design Instagram Reels Recommendations

Hard
Product Sense
Asked at 1 company1User NeedsUse CasesProduct Vision
Also asked at
Meta

Problem

Company Context

Meta operates one of the largest consumer social platforms globally, and Instagram Reels is a core short-form video surface competing for user attention against TikTok, YouTube Shorts, and other entertainment products. Reels already has massive scale, but continued growth depends on showing users videos that feel immediately relevant while also helping creators reach the right audiences.

Problem

Instagram leadership believes Reels can increase session depth and creator satisfaction, but users currently report mixed feed quality: some feel Reels becomes repetitive, some say it over-indexes on viral content instead of personal interests, and new creators struggle to get distribution. Internal analysis shows that users who find 5+ highly relevant Reels in their first week are significantly more likely to return, while excessive repetition and low-quality recommendations correlate with lower satisfaction and more negative feedback actions (e.g., “Not Interested,” skips, hides).

You are the product manager responsible for defining the product strategy for the Instagram Reels recommendation system. This is a product-sense question: focus on user needs, product goals, prioritization, trade-offs, and how you would decide what the system should optimize for. You do not need to design the full ML architecture.

Deliverables

  1. Define the primary user problems the Instagram Reels recommendation system should solve and identify the most important user segments.
  2. Propose a product vision for what a great Reels recommendation experience should look like for viewers and creators.
  3. Prioritize the recommendation system goals and product features you would launch first, including what signals or user behaviors matter most.
  4. Define success metrics and explain how you would balance engagement, satisfaction, creator ecosystem health, and content quality.
  5. Discuss key trade-offs and risks, including repetition, filter bubbles, cold start, and potentially harmful or low-quality content.

Constraints

  • You have one half-year planning cycle for the first major product iteration.
  • You cannot materially increase app latency or degrade the Instagram home feed experience.
  • Any approach must work across new users, casual viewers, heavy Reels consumers, and emerging creators.
  • Recommendations must align with Meta’s integrity, safety, and policy requirements.

Problem

Company Context

Meta operates one of the largest consumer social platforms globally, and Instagram Reels is a core short-form video surface competing for user attention against TikTok, YouTube Shorts, and other entertainment products. Reels already has massive scale, but continued growth depends on showing users videos that feel immediately relevant while also helping creators reach the right audiences.

Problem

Instagram leadership believes Reels can increase session depth and creator satisfaction, but users currently report mixed feed quality: some feel Reels becomes repetitive, some say it over-indexes on viral content instead of personal interests, and new creators struggle to get distribution. Internal analysis shows that users who find 5+ highly relevant Reels in their first week are significantly more likely to return, while excessive repetition and low-quality recommendations correlate with lower satisfaction and more negative feedback actions (e.g., “Not Interested,” skips, hides).

You are the product manager responsible for defining the product strategy for the Instagram Reels recommendation system. This is a product-sense question: focus on user needs, product goals, prioritization, trade-offs, and how you would decide what the system should optimize for. You do not need to design the full ML architecture.

Deliverables

  1. Define the primary user problems the Instagram Reels recommendation system should solve and identify the most important user segments.
  2. Propose a product vision for what a great Reels recommendation experience should look like for viewers and creators.
  3. Prioritize the recommendation system goals and product features you would launch first, including what signals or user behaviors matter most.
  4. Define success metrics and explain how you would balance engagement, satisfaction, creator ecosystem health, and content quality.
  5. Discuss key trade-offs and risks, including repetition, filter bubbles, cold start, and potentially harmful or low-quality content.

Constraints

  • You have one half-year planning cycle for the first major product iteration.
  • You cannot materially increase app latency or degrade the Instagram home feed experience.
  • Any approach must work across new users, casual viewers, heavy Reels consumers, and emerging creators.
  • Recommendations must align with Meta’s integrity, safety, and policy requirements.
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