Metrics question
Instagram recently decided to hide like counts on posts. How would you measure the success of this new feature?
- Metrics
- Medium
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What this question tests
Tests defining success metrics for a well-being-motivated feature where the goal is reduced social comparison, not engagement growth.
How to approach it
- Clarify the goal: hiding like counts aims to reduce social comparison pressure and anxiety, particularly for younger users, not to boost raw engagement.
- Define a primary well-being metric: self-reported comparison or anxiety levels via periodic in-app surveys, hidden-count users versus a control group.
- Define a behavioral proxy: posting frequency and content diversity, willingness to post more authentic content, among users with hidden counts.
- Define a guardrail: overall engagement, likes given, comments, session time, shouldn't collapse, since the feature must not tank the core product.
- Segment by age group, since the well-being rationale is strongest for teens, and measure impact separately for that cohort.
- Define success: a measurable reduction in reported comparison pressure without a significant drop in posting frequency or core engagement.
What a strong answer includes
- Grounds success in the feature's actual motivation, well-being, rather than defaulting to a generic engagement metric.
- Proposes a direct well-being measurement method, periodic sentiment surveys, rather than only inferring it from behavior.
- Sets an explicit engagement guardrail, recognizing the feature could backfire if it collapses core usage.
- Segments by age, correctly identifying teens as the most relevant cohort for this feature's stated purpose.
Common mistakes
- Measuring only engagement metrics, missing the feature's actual well-being goal entirely.
- No guardrail against a usage collapse, risking a feature that succeeds on its stated goal but kills the product.
Likely follow-up questions
- How would you measure comparison pressure without relying purely on self-report?
- What would you do if posting frequency dropped for creators who relied on visible like counts for status?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 2: Data fluency: SQL, logs, and reading the truth yourself
- Chapter 14: Get the job: the AI PM interview loop