Strategy question
Pretend Google Next wants to acquire iRobot. What do you look for/how do you position your decision?
- Strategy
- Hard
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What this question tests
M&A style strategic thinking: evaluating market fit, synergy, and risk for an acquisition rather than just liking the target's product.
How to approach it
- Clarify the strategic goal behind the acquisition, for example entering home robotics hardware versus acquiring mapping and navigation technology.
- Assess the market: home robotics (led historically by iRobot's Roomba) is growing but hardware heavy and low margin compared with Google's core software business.
- Evaluate competitors already in the space, such as Roborock and Ecovacs, and whether Google can differentiate post-acquisition.
- Identify Google's advantage: Google Home ecosystem, mapping expertise from Maps, and Assistant integration could make iRobot's home mapping data more valuable.
- Weigh the options: full acquisition, licensing the mapping technology, or building in-house, and compare cost and speed to market.
- Recommend a position with explicit risks, such as antitrust scrutiny on data collection from in-home mapping.
What a strong answer includes
- Names the real strategic asset, indoor mapping data from vacuuming robots, not just the product line, as the reason to acquire.
- Flags a concrete risk: regulators scrutinizing a large tech company collecting detailed floor plans of people's homes.
- Considers a lighter alternative to full acquisition, such as a data partnership, and explains why acquisition still wins on integration speed.
Common mistakes
- Evaluating the deal only on product fit and ignoring antitrust and privacy risk.
- Failing to state what specific asset justifies the price versus building in-house.
Likely follow-up questions
- What would you be willing to pay and how would you justify that valuation?
- What integration risks would concern you most in the first year?
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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