Hinge · Metrics · Mid · 45 to 60 minutes

How should Hinge read retention and churn?

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

Metrics design
Product judgment
Analytical reasoning
Segmentation
User insight

The situation

Your manager, Hinge's Director of Product, asks you to prepare a recommendation for the leadership team on how the company should judge product health. Recent dashboard reviews have raised concern because common consumer app metrics are pointing in different directions. Some cohorts show strong early activity but softer medium term retention, and churn is hard to interpret across new, active, and returning users. At the same time, teams are debating priorities. Some want to optimize for more sessions and longer streaks, while others argue those metrics may not fully capture whether Hinge is doing its job for people. Leadership needs a clear measurement approach before setting quarterly goals and evaluating upcoming investments in onboarding, discovery, and matching. Assume you have access to standard in app behavioral data, survey tools, and basic cohort analysis, but not a perfect view of what happens after users stop using the app. Your task is to define how Hinge should interpret retention and churn, what metrics should anchor decisions, and what evidence would tell you the product is improving or failing.

What to produce

Write a 1 to 2 page product metrics memo for the leadership team.

Your answer must

State the product goal you would optimize for, and explain how that changes the meaning of retention and churn for Hinge.
Propose one primary metric and 3 to 5 supporting metrics, including at least one guardrail metric, and explain what decision each metric should inform.
Specify at least two user segments or cohorts that should be analyzed separately, and explain why aggregated metrics would be misleading.
Outline a plan to determine what different kinds of churn mean, using a mix of product analytics and direct user feedback.
Recommend how leadership should use your framework for quarterly planning, including what metric changes would trigger action.

Constraints

Work only from the write up summary and generally known facts about dating apps, do not present invented facts about Hinge as real.
Use only metrics and evidence Hinge could plausibly gather through product analytics and lightweight user research.
Do not assume raw retention, engagement, or churn each map cleanly to product value on their own.

Format

Use short sections with headings, and include one simple metric tree or table.

How Hinge actually played it

Hinge's data lead explains that success on a dating app is linked to losing users who found a match, so churn needs context. The post covers how the team interprets engagement, retention and churn. A strong metrics case for products where leaving can mean success.

Interpret churn in context of the product's goal
Success can look like churn for some products
Pair metrics with an understanding of user outcomes

Built from Hinge's good churn connects 50,000 dates a week by Mixpanel team.