Defining Success Metrics and a North Star for LinkedIn Saved Posts

LinkedIn lets members save a post from their feed so they can come back to it later. How would you judge whether this save feature is successful? Define what success means for it, the metrics you would track, and the single metric you would treat as the primary one. ```hint Follow a saved post A save is a promise to return. Trace what happens after a member taps save, decide which step shows that the member actually got value, and build the metrics around that journey. ``` ### Clarifying Questions - Does "save" here cover feed posts and articles only, or also saved jobs, which have their own flow? - Are we judging a recent launch or the ongoing health of an established feature? - Is there a goal the feature should serve, such as member engagement, feed quality or revenue? - Should I focus on one member group, for example people who read the feed to learn versus job seekers? ### What a Strong Answer Covers - The member problem saving solves and how it ties to LinkedIn's goals - A metric funnel from finding and using save, through returning to saved posts, to acting on them - One primary metric with a clear rationale, plus guardrails against gaming and cannibalization - Segmentation, and a way to separate the feature's causal impact from the fact that heavy users save more - The trade-off between counts that are easy to move and metrics that reflect real value ### Follow-up Questions - After a redesign puts save one tap away, saves rise sharply but members return to saved posts no more often. How do you read that? - The team wants to remind members about saved posts they never reopened. How would you decide whether the reminders help or hurt? - How could saves be useful beyond the feature itself, for example as a signal for feed ranking, and how would you measure that?