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Google·Product Manager·Onsite - Product Sense / Strategy·Intermediate

IntermediatePrefer not to say
Apr 2026

Summary

Product management case question at Google, the burger shop sales decline scenario. Pretty classic root cause analysis framing but I fumbled the structure more than I expected.

Questions Asked (1)

Q1

You own a burger shop and sales have been declining. How do you investigate what's going wrong?

Root Cause AnalysisProduct Analytics & MetricsProduct Strategy
Author's notes

I went straight to external factors first, which in hindsight was backwards.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the goal and defining what 'declining sales' means (e.g., revenue, units, or market share) and over what period. Then structure your investigation by breaking down the problem into internal and external factors, using data to isolate the root cause before proposing solutions.

Pro tip: Demonstrate a hypothesis-driven approach: form 2-3 hypotheses early and prioritize them based on impact and ease of validation. This shows you can navigate ambiguity efficiently, a key trait for Google PMs.

1. Clarify the problem

Ask clarifying questions to understand the scope: Is the decline in revenue, units, or profit? Over what time period? Is it specific to certain locations or the entire chain? This ensures you're solving the right problem.

2. Break down the metrics

Decompose sales into drivers: number of customers, average order value, frequency, and retention. Analyze trends in each to identify which component is declining and by how much.

3. Form hypotheses

Based on the data, generate hypotheses for the decline, such as increased competition, changing customer preferences, operational issues, or pricing problems. Prioritize hypotheses by likelihood and impact.

4. Gather data to validate

Collect both quantitative data (sales trends, customer surveys, competitor analysis) and qualitative data (customer feedback, employee insights) to test each hypothesis. Use tools like cohort analysis, funnel analysis, and A/B tests if applicable.

5. Synthesize and recommend

Identify the root cause(s) and propose actionable solutions. Prioritize solutions based on impact and feasibility, and outline how you would measure success.

Key Points to Mention

  • Segment the data by customer demographics, time, location, and product mix to uncover patterns.
  • Consider external factors like market trends, competitor actions, and economic conditions.
  • Use both quantitative (e.g., sales data, web analytics) and qualitative (e.g., customer interviews) methods.
  • Apply the '5 Whys' or fishbone diagram to dig deeper into root causes.
  • Prioritize hypotheses using an impact/effort matrix to focus on high-impact areas first.
  • Define success metrics and a plan to monitor the effectiveness of implemented solutions.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.