Metrics question
How would you go about deploying Google Fiber to a new city, assuming you were part of the original roll-out team?
- Metrics
- Hard
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What this question tests
Metrics for a capital intensive infrastructure rollout, balancing build speed, cost efficiency, and long term subscriber adoption.
How to approach it
- Confirm the goal: fastest coverage expansion, cost efficiency, or subscriber adoption within a new city.
- Split metrics into build phase, such as homes passed per month, and adoption phase, such as subscriber conversion rate.
- Add a cost metric, cost per home passed, since infrastructure builds are capital intensive.
- Add a satisfaction and reliability metric, such as uptime and support ticket rate, since fiber competes on quality.
- Define a north star, such as subscribers per dollar invested, tying build efficiency to adoption success.
- Set a guardrail on construction related complaints, since fiber rollouts involve digging in public spaces.
What a strong answer includes
- Separates build phase metrics from adoption phase metrics, reflecting the real two stage nature of infrastructure rollout.
- Includes cost per home passed, a metric specific to capital intensive infrastructure projects.
- Adds a community facing guardrail, construction complaints, relevant to digging up streets and yards.
- Ties everything to one north star, subscribers per dollar invested, useful for comparing cities.
Common mistakes
- Tracks only subscriber growth and ignores the capital cost side of the rollout.
- Ignores community impact from construction, a real and common complaint with fiber rollouts.
Likely follow-up questions
- How would you decide which neighborhoods to prioritize first within a city?
- How would you measure success differently in a competitive market versus one with no fiber competitor?
- What would make you pull out of a city mid rollout?
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More questions from Google
Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 2: Data fluency: SQL, logs, and reading the truth yourself
- Chapter 14: Get the job: the AI PM interview loop