Aprende Product Metrics Case Study Project | Product Strategy and Real-World Metrics

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Definition

A product metrics case study is a practical exercise where learners analyze a real or hypothetical product's metrics to identify challenges and recommend improvements.

You are about to apply your understanding of product KPIs and growth metrics to a real-world scenario. Imagine a hypothetical product: TaskFlow, a productivity app designed to help remote teams manage projects and daily tasks. TaskFlow has received positive initial feedback, but recent data shows slowing user growth, declining engagement, and higher churn rates among new users. The product team suspects that users are not finding enough value in the onboarding experience and are not adopting key features that drive long-term retention. Your challenge is to analyze the available metrics, identify the main issues, and recommend actionable improvements that could help TaskFlow grow more sustainably.

Step 1: Review the current metrics.

TaskFlow's dashboard highlights the following:

DAU/MAU ratio has dropped from 32% to 18% over three months;
New user activation rate is 25%, down from 40% at launch;
Feature adoption for "Automated Reminders" is only 10% among active users;
Churn rate for users in their first month is 35%.

Step 2: Identify the main challenges.

The steep drop in DAU/MAU and activation rate suggests users try the app but do not continue using it. Low adoption of "Automated Reminders", a core differentiator, points to poor onboarding or unclear value communication. High first-month churn confirms that users are not converting to long-term customers.

Step 3: Decide on potential improvements.

The team considers several options:

Redesign onboarding to highlight "Automated Reminders";
Implement contextual tooltips and in-app messages to guide new users;
Set up a new KPI: "Feature Adoption Rate within 7 Days" to measure early engagement with key features;
Launch A/B tests on onboarding flows and track resulting changes in activation and retention.

Step 4: Recommend metrics improvements.

Focusing on actionable metrics is key. The team recommends:

Prioritizing "Feature Adoption Rate within 7 Days" as a leading indicator;
Closely tracking activation and retention cohorts after onboarding changes;
Using funnel analysis to spot drop-off points in the first-week experience;
Regularly reviewing DAU/MAU and churn to measure long-term impact.

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