Hinge · Metrics · Senior · 45 to 60 minutes

What Should Hinge Optimize For?

Hinge is a dating app that helps people meet romantic partners. Answer this product management case and get it graded line by line against a weighted rubric.

metric design
strategic thinking
product sense
systems thinking
executive communication

The situation

The CEO asks you, a senior PM on Hinge, to recommend the company level product metric for the next planning cycle. Hinge operates in a category where many teams naturally optimize for repeat use, time spent, and other engagement signals. At the same time, Hinge's brand promise is about helping people form meaningful connections, and leadership worries the current metrics may be steering design choices in ways that are not fully aligned with that promise. The decision matters because the chosen metric will shape roadmap priorities, team incentives, experimentation, and how Hinge balances user value with revenue. A metric focused on activity may support near term growth, but could bias the product toward more browsing and messaging. A metric focused on user outcomes may better reflect the promise, but could be harder to define, measure, and connect to business performance. You need to recommend what Hinge should optimize, how to measure it, and what tradeoffs the company should accept.

What to produce

A 1 to 2 page decision memo.

Your answer must

Frame the decision with 2 to 3 plausible north star metric options, including one engagement centered option and one user outcome centered option.
Recommend one primary metric and define it precisely, including numerator, denominator, time window, and who is counted.
Propose 2 to 4 guardrail metrics that protect user experience and business health, and explain how they reduce gaming.
Explain how your metric choice would change product design and roadmap priorities over the next two phases.
Address second order effects on retention, revenue, trust, and team incentives, and describe how you would validate the metric before fully scaling it.

Constraints

Work only from the summary and takeaways above, and state any assumptions clearly.
Do not assume Hinge can directly observe every successful relationship with perfect accuracy.
Keep the recommendation at the company or business line level, not a single feature experiment.

Format

Use headings for decision, options considered, metric definition, guardrails, roadmap implications, and risks and validation.

How Hinge actually played it

Tells how Hinge rebuilt around the success metric of users leaving because they found a relationship, replacing swipes with prompts. It covers why this contradicted the usual dating app incentive and the revenue that followed.

Pick a success metric that matches the user's real goal
Break from engagement-maximizing business logic when the product promise says otherwise
Metric choice drives product design

Built from Justin McLeod Bet Hinge’s Growth on Users Deleting the App. Revenue Grew 69× to $691 Million by James Bickerton (Your Product Sucks).