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Google·Business Analyst·Onsite - Product Sense / Strategy·Intermediate

IntermediatePrefer not to say
Apr 2026

Summary

Got a market sizing question at Google, pretty standard case interview stuff but I fumbled the structure more than I'd like to admit.

Questions Asked (1)

Q1

Estimate the number of people who frequently visit bars.

Product Analytics & MetricsAdaptability & Ambiguity
Author's notes

I jumped straight into US population and started segmenting by age, which felt right, but then I got tangled up trying to define 'frequently' and wasted like two minutes debating whether that meant weekly or monthly.

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AI HintsAI Generated

Suggested Approach

Clarify the scope (e.g., geographic region, definition of 'frequently') and then use a top-down estimation approach. Segment the population by age and other relevant factors, apply reasonable frequency assumptions, and calculate the total number of frequent bar visitors.

Pro tip: State your assumptions explicitly and round numbers to make calculations easier. Show that you can iterate and adjust based on new information, demonstrating adaptability.

1. Clarify the question

Ask clarifying questions to define the target population, geographic scope, and what 'frequently' means (e.g., at least once a week).

2. Segment the population

Break down the total population into relevant segments, such as age groups, considering legal drinking age and typical bar-going demographics.

3. Estimate segment sizes

Estimate the number of people in each segment using known population data or reasonable assumptions (e.g., percentage of population in each age group).

4. Apply frequency assumptions

For each segment, estimate the proportion that frequently visits bars and the average frequency of visits, then calculate the number of frequent visitors.

5. Sum and sanity-check

Add up the estimates from all segments to get the total, and sanity-check the result against known benchmarks or logical bounds.

Key Points to Mention

  • Definition of 'frequently' (e.g., at least once a week)
  • Legal drinking age and its impact on eligible population
  • Age segmentation and typical bar-going behavior by age group
  • Geographic scope (e.g., United States, urban vs. rural)
  • Assumptions about frequency and proportion of frequent visitors
  • Sanity-checking the final estimate against known data or logical constraints

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