Strategy question
Suppose 10 Google Cloud customers come to you and say they want you to customize your product for them. Your engineering team has the bandwidth to handle only one of the requests. Walk me through how you'd evaluate the customers and decide which ones to build for.
- Strategy
- Medium
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What this question tests
Tests structured prioritization under scarce engineering resources, requiring an evaluation framework rather than picking by gut feel or the loudest customer.
How to approach it
- Clarify what customize means for each request: confirm whether these are similar asks that could share a solution, or ten genuinely different one-off requests.
- Define evaluation criteria: revenue and growth potential of each customer, strategic fit, whether the customization solves a problem common to other prospects, and engineering effort required.
- Check for a shared underlying need: if several requests are variations on the same capability, prioritize building a general solution that satisfies multiple customers at once.
- Weigh long-term platform value against short-term relationship risk: a smaller customer's request that unlocks a broadly reusable feature may beat a large customer's narrow, one-off ask.
- Propose a decision process: score each request on revenue impact, reusability, and effort, pick the highest-scoring option, and document the reasoning to defend the decision.
- Address relationship management: communicate transparently with the nine not selected, offering a realistic timeline or interim workaround rather than silence.
What a strong answer includes
- Checks for a shared underlying need across the ten requests first, since one reusable solution may satisfy several customers at once.
- Proposes a concrete, multi-factor scoring framework, revenue, reusability, effort, rather than a single-dimension decision.
- Weighs reusability explicitly, showing platform-thinking beyond a single deal's revenue.
- Addresses the relationship side, communicating with the nine declined customers, not just the technical prioritization.
Common mistakes
- Picking simply the largest customer by revenue without checking whether a shared solution could serve multiple requests.
- Ignoring the relationship management needed with customers not selected, risking broader account damage.
Likely follow-up questions
- How would you handle it if the highest-scoring request is from your smallest customer?
- What would you say to the CEO of a large customer who wasn't selected?
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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