Strategy question
Design a dashboard for the CEO of Google.
- Strategy
- Hard
Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.
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What this question tests
Executive-level metrics design skill, checking whether you can identify the small set of metrics that actually matter for company-wide decision-making at the CEO level.
How to approach it
- Clarify the CEO's actual decision-making needs: high-level company health and strategic bets, not granular product-level metrics any single team already tracks.
- Identify the top-level categories: financial health, like revenue and cloud segment growth, user and platform health, like active users across major products, and strategic bet progress, like AI product adoption.
- Prioritize trend and trajectory over static snapshots, since a CEO cares more about whether a metric is accelerating or decelerating than its absolute value on a given day.
- Propose a structure: a small set of 6 to 8 top-line metrics with clear trend lines, plus a drill-down layer for any metric showing a concerning inflection point.
- Address noise reduction: exclude vanity metrics like raw pageviews in favor of metrics tied to durable business outcomes, like paid conversion or retention.
- Define success as the dashboard's ability to surface an emerging problem early enough for leadership to act, validated by whether it would have caught a past real issue.
What a strong answer includes
- Limits the dashboard to a small number of metrics, 6 to 8, resisting the urge to include everything, which is the key discipline of executive-level design.
- Prioritizes trend and trajectory over static numbers, correctly identifying what actually drives executive decisions.
- Validates the design against a past real event, showing the dashboard is built to actually catch problems, not just look comprehensive.
Common mistakes
- Including too many metrics, creating a dashboard that overwhelms rather than informs executive decision-making.
- Choosing vanity metrics like raw traffic instead of metrics tied to durable business outcomes like retention or revenue.
Likely follow-up questions
- Which single metric would you cut first if you could only keep five?
- How would you validate this dashboard actually helps catch problems early?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 14: Get the job: the AI PM interview loop