Estimation and Product Metrics Drill
Provide best-effort estimates using clear assumptions. Give a single-number answer and a justified range for estimation parts.
Questions:
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Estimate how many Starbucks stores exist in the United States.
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Estimate annual smart-TV units sold worldwide.
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For Google Docs, list the three most important product metrics and set a measurable goal for each.
Constraints & Assumptions
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Use Fermi estimation rather than trying to recall exact facts.
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State scope, assumptions, central estimate, and range.
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Sanity-check estimates with at least one alternative method when possible.
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For Google Docs metrics, define the metric precisely and include a measurable goal.
Clarifying Questions to Ask
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Should Starbucks include licensed stores and kiosks, or only standalone stores?
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Should smart-TV sales include all TVs with smart capabilities or only connected/activated TVs?
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Are Google Docs metrics for consumer users, education, enterprise, or all users?
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Should goals be quarterly, annual, or experiment-level targets?
Part 1 - Starbucks Store Estimate
Estimate U.S. Starbucks stores.
What This Part Should Cover
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Demand-side or per-capita decomposition.
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Assumptions for population, coffee buyers, Starbucks share, and orders per store.
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Central estimate and plausible range.
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Sanity check and pitfalls.
Part 2 - Smart-TV Sales Estimate
Estimate annual worldwide smart-TV unit sales.
What This Part Should Cover
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Household or replacement-cycle decomposition.
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Global household count, TV penetration, replacement cycle, and smart-TV share.
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Central estimate and plausible range.
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Sanity check against manufacturing or regional logic.
Part 3 - Google Docs Metrics
List the three most important product metrics and set measurable goals.
What This Part Should Cover
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Metrics tied to creation, collaboration, retention, and quality.
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Clear definitions, windows, and goals.
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Guardrails such as latency, sharing errors, spam/abuse, and satisfaction.
What a Strong Answer Covers
A strong answer shows estimation structure, not memorized trivia. It explains assumptions, computes cleanly, gives ranges, sanity-checks, and defines product metrics that reflect real Google Docs user value.
Follow-up Questions
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Which assumption drives the Starbucks estimate most?
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How would your smart-TV estimate change if replacement cycles lengthen?
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Why not use Google Docs DAU alone?
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What metric would capture collaboration quality?
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How would you validate your estimate after the interview?