Facebook Dating: Strategic Rationale, Impact Measurement and a North Star Metric

Facebook Dating is the opt-in dating feature Meta built inside the Facebook app. Answer two questions about it. ### Clarifying Questions - Should I reason about the decision as it looked when Dating launched, or about Dating as it exists today? - Does "overall impact" mean Dating's success for its own users, its effect on the wider Facebook app and business, or both? - Is Dating expected to make money directly, or should I treat its revenue contribution as indirect? ### Part 1 — Why Meta built a dating product Explain why you think Meta decided to build Dating into Facebook. ```hint Assets and gaps Compare what Facebook already had that standalone dating apps lack with what Facebook needed from its younger users, then weigh both against the risks Meta took on. ``` #### What This Part Should Cover - Fit with Meta's mission and with how people already met partners through Facebook - The advantages Facebook's identity, social graph, groups and events gave it, and where they were liabilities - The strategic upside for Facebook as a whole, not only for Dating - The risks Meta accepted and how the product design responded to them ### Part 2 — Measuring impact and setting the North Star How would you measure Dating's overall impact, and what would you choose as its North Star metric? ```hint Success can mean leaving A user whose dating worked may stop using the product, so test each candidate metric against that case, then think about how you would isolate Dating's effect on the rest of Facebook. ``` #### What This Part Should Cover - A North Star that reflects the outcome users come for, with a precise definition and the reasons other candidates were rejected - Supporting metrics across the funnel and the two-sided market, plus safety and privacy guardrails - How Dating's causal effect on Facebook engagement and retention would be estimated when users choose for themselves whether to join ### What a Strong Answer Covers - A consistent thread: the reasons given in Part 1 become the impact measured in Part 2 - Precise metric definitions (unit, time window, thresholds) rather than labels - Awareness that a dating market is two-sided and local, so its health differs by city, age band and gender balance - Safety, scams and privacy treated as first-class guardrails - Honest limits of measurement: rare real-world outcomes, survey bias and self-selection ### Follow-up Questions - Your North Star rises while the share of users reporting an in-person date falls. What do you investigate? - Leadership asks whether Dating should become its own app. Which metrics would inform that decision? - How would you detect that a small share of profiles receives most of the attention, and why does it matter?