Strategy question
Gemini and Search both answer questions. How do you avoid cannibalizing Search ad revenue?
- Google DeepMind
- Strategy
- Hard
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What this question tests
Strategic tension between two products in the same portfolio competing for the same query intent and ad revenue.
How to approach it
- State the core tension: a direct AI answer in Gemini can resolve a user's need without any ad-supported search results page.
- Segment query intent: informational queries (facts, explanations) are most at risk of cannibalization, while commercial and navigational queries (shopping, brand lookups) still need Search's ad-driven results.
- Propose differentiated experiences by intent: Gemini answers informational queries directly, while Search keeps its results page and ads for commercial intent.
- Introduce new ad formats within AI answers themselves, such as clearly labeled sponsored suggestions or product placements within a Gemini answer, similar to how AI Overviews are evolving.
- Reframe the metric that matters: total advertiser value across both surfaces combined, rather than protecting Search's legacy click-through model in isolation.
- Define success as stable or growing total ad revenue across Search and Gemini combined, even if Search's standalone click volume declines.
What a strong answer includes
- Segments by query intent rather than treating all cannibalization risk as uniform.
- Proposes a concrete new ad model (sponsored placements within AI answers) instead of just protecting the old model.
- Reframes the success metric to combined advertiser value, showing awareness that individual channel metrics can be a false signal.
- Acknowledges that some standalone Search volume decline is an acceptable trade-off if total value holds.
- Grounds the answer in commonly known Google product structure (Search ads, AI Overviews) rather than speculation.
Common mistakes
- Assuming cannibalization simply must be blocked, without considering that combined revenue framing may matter more.
- Not segmenting by query intent, treating all searches as equally at risk.
Likely follow-up questions
- How would you design sponsored placements without undermining answer trust?
- How would you measure combined advertiser value across both products?
- What would you do if advertisers pushed back on reduced click volume?
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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