Business case study questions are a staple of data science interviews—especially at product- and business-focused companies like Meta, Airbnb, Amazon, and Uber. These questions test your ability to apply structured thinking, data reasoning, and product intuition to solve real-world business problems.
In this guide, we’ll break down how to approach these questions, common themes to expect, and strategies to stand out.
🧩 What Are Business Case Study Questions?
These are open-ended questions that simulate real product or business problems, such as:
- “Why is retention dropping?”
- “How would you evaluate the success of a new feature?”
- “Which countries should we expand into?”
Your job is not to calculate a specific number, but to demonstrate how you think through ambiguity, identify key metrics, and suggest actionable recommendations.
🛠️ A Structured Approach
Here’s a battle-tested structure you can use:
1. Clarify the Objective
Ask:
- What is the business trying to achieve?
- What is the time horizon and scope?
Example: “Are we optimizing for short-term revenue or long-term user engagement?”
2. Identify Key Metrics
Choose metrics that align with the business objective:
- Growth: MAU, sign-ups, referral rate
- Retention: N-day retention, churn, DAU/WAU ratio
- Revenue: ARPU, conversion rate, LTV
- Engagement: session frequency, feature usage
Tip: Explain why the metric matters—not just what it is.
3. Form Hypotheses
Use MECE (mutually exclusive, collectively exhaustive) reasoning to list possible causes or solutions.
Example: “If engagement dropped, is it due to:
- A recent UI change?
- App crashes or performance issues?
- External seasonality?
- Competition?”
4. Prioritize Analyses
Which hypothesis is most likely, most impactful, or easiest to test?
Explain how you’d:
- Segment users (e.g., by device, geography)
- Use historical trends
- Analyze event funnels or drop-offs
- Look for correlation between changes and metrics
5. Recommend Actions
End with a recommendation that’s tied to the data insights.
“If we find engagement dropped only on Android devices after a recent update, I’d suggest reverting that version or rolling out a fix immediately.”
💼 Common Case Themes
1. Retention Drop
“Instagram’s 7-day retention dropped by 5% last month. What would you investigate?”
Walk through:
- Cohort retention curves
- Segment by platform / geography / acquisition source
- Check for bugs or crashes
- Look for feature removals or policy changes
2. Feature Evaluation
“We launched a new personalized homepage. How would you evaluate its impact?”
Focus on:
- Designing an A/B test with clearly defined metrics
- Looking at click-through rate, dwell time, return rate
- Checking for unintended side effects (e.g., slower load time)
3. Revenue Optimization
“How would you increase revenue for Spotify without harming user experience?”
Brainstorm:
- Upsell premium at natural breakpoints
- Optimize ad load timing
- Target long-time free users with LTV modeling
🎯 What Interviewers Look For
- Clear structure: Can you break down a messy problem?
- Business judgment: Do you understand trade-offs?
- Metric intuition: Do you know what to measure and why?
- Actionable thinking: Can you translate analysis into recommendations?
🔥 Bonus Tips
- Use real-life analogies to communicate ideas (e.g., “like a store measuring foot traffic and purchases”).
- Speak in hypotheses, not assumptions.
- Bring in previous experience: “At my last role, we faced a similar drop and found…”
✅ Conclusion
Business case questions aren’t about finding the "right" answer—they’re about showing how you use data to make smart business decisions. By approaching these questions with structure and empathy for both users and the business, you’ll stand out as a thoughtful, product-savvy data scientist.