Instagram is one of Meta’s largest consumer products, serving billions of users globally across feed, Stories, Reels, and messaging. Direct messaging is a critical engagement surface because it supports private sharing, relationship-building, and content distribution beyond public posting.
Instagram is preparing to launch a new direct messaging feature inside Instagram DMs. The product team believes the feature could increase private sharing and deepen retention, but there is disagreement on how to define success. Some leaders want to optimize for raw usage, while others worry that more messaging volume could come from spam, accidental sends, or low-quality interactions that hurt trust.
You are the data analyst embedded with the Instagram Messaging team. Your task is to define the right metric framework for this launch so the team can evaluate whether the feature creates meaningful user value, not just activity.
Assume the feature will launch first to a subset of Instagram users in a few major markets, with limited engineering bandwidth for instrumentation changes in the first release.