Company Context

Meta operates one of the largest consumer social ecosystems globally, with Instagram serving billions of sessions across Feed, Stories, Explore, DMs, and Reels. Instagram Reels is a strategic short-form video surface that competes for creator supply, user attention, and ad inventory while also affecting engagement on other Instagram surfaces.

Problem

The Head of Instagram asks you, as a Data Scientist partner to Product, to define how Meta should measure the success of Instagram Reels. Reels has grown quickly, but leadership is concerned that raw watch time may overstate value if Reels cannibalizes Feed or Stories, attracts low-intent consumption, or creates a short-term novelty effect. There is also pressure to understand whether Reels improves long-term user value, creator ecosystem health, and monetization quality.

You are not being asked to build a dashboard of every possible metric. Instead, define a product-sense measurement strategy that reflects user needs, Meta's AARRR funnel, and the trade-offs between engagement, retention, creator health, and ecosystem impact. Assume you have access to Meta-standard event logs for impressions, plays, watch time, likes, comments, shares, ig save, follows, session starts, ad impressions, and creator posting activity, plus experiment infrastructure that supports CUPED adjustment and SRM checks.

Deliverables

1. Define the core user and business goals of Instagram Reels, including which user segments matter most.
2. Propose a north-star metric and supporting metric hierarchy for Reels using Meta-specific product signals.
3. Explain how you would separate genuine product value from cannibalization, novelty effect, and low-quality engagement.
4. Recommend how you would validate your framework through experimentation, including key guardrails.
5. State the main trade-offs you would make if metrics conflict across users, creators, and monetization.

Constraints

• You must account for cross-surface effects on Feed, Stories, Explore, and creator posting behavior.
• Leadership wants a framework that can be used for both product reviews and A/B test readouts.
• You cannot rely only on short-term engagement metrics; long-term retention and ecosystem health must be addressed.
• Assume a 12-week decision window for evaluating whether a major Reels ranking investment is successful.