Metrics question
Assume you are the product owner for Airbnb’s Mobile app and that there is a data point that indicates that there are more mobile web than mobile app users of Airbnb. Please describe why this could be the case, and describe what you would do within the product to change that. Lower fidelity mockups, where applicable, would be helpful.
Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.
Start a mock interview on this question · Mock interview from a job description
What this question tests
Tests diagnosing why a channel underperforms and proposing product changes with a testable, hypothesis-driven approach.
How to approach it
- Hypothesize causes: install friction for casual browsers, the app requiring login sooner than web, or web simply serving top-of-funnel SEO traffic.
- Segment the data by new versus returning users and by funnel stage, browsing versus booking, to see where mobile web actually dominates.
- If browsing-stage users dominate mobile web, recognize the app doesn't need to win there and shouldn't force an early install.
- Propose smart app-install prompts timed to high-intent moments, like saving a listing or starting a booking, plus lightweight mobile-web checkout parity.
- Define success as mobile-web-to-app conversion at high-intent moments and booking completion rate by channel, not raw install count.
What a strong answer includes
- Does not assume the app must win everywhere; instead separates funnel stage to correctly interpret the data.
- Proposes a smarter, delayed install prompt rather than an early interstitial, addressing the mockup-worthy design ask.
- Notes that SEO traffic naturally lands on mobile web, which is expected and not automatically a problem.
Common mistakes
- Assuming this gap is automatically a problem and forcing app installs everywhere with an interstitial.
- Not segmenting by funnel stage before proposing a fix.
Likely follow-up questions
- How would you validate your hypothesis about why users stay on mobile web?
- What would make you decide not to push app installs at all for some segments?
More metrics questions
- Late deliveries lead to customer churn. What data we should look at to prove this hypothesis for a food delivery app?PayPal · Metrics · Medium
- How would reduce cancellations for Uber?Shopify · Metrics · Medium
- There is a data point that indicates that there are more Uber drop-offs at the airport than pick-ups from the airport. Why is this the case and what would you do within the product to change that?PayPal · Metrics · Hard
- How would you measure the success of Uber Ride?Lyft · Metrics · Easy
- If a large number of drivers are dropping out of a particular city, why would it be?Lyft · Metrics · Medium
- Drivers are dropping out of a city on Lyft. How do you figure out what's going on?PayPal · Metrics · Medium
More questions from these companies
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