Strategy question
How would you set a 12-month acquisition strategy for Figma across traditional search and emerging generative discovery surfaces? Outline where you'd pursue quick wins, where you'd place longer-term bets, and what tradeoffs would guide resource allocation across SEO, product surfaces, and content or community assets.
- Figma
- Strategy
- Hard
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What this question tests
Cross-channel growth strategy: can you allocate resources across a mature channel and an emerging one under real uncertainty about how AI answer engines will drive traffic.
How to approach it
- Split the strategy into quick wins and long bets explicitly: traditional SEO is measurable and mature, generative discovery, being surfaced in AI answers, is emerging and harder to measure directly.
- Quick wins in traditional search: strengthen high-intent pages, like template and tutorial content, where Figma already ranks near the top and incremental gains are cheap.
- Longer bets in generative discovery: structure content and product surfaces, like public file links and community templates, to be citable and well-attributed in AI answer engines, even without clear attribution data yet.
- Allocate resources roughly by certainty of return: heavier near-term investment in proven SEO, a smaller experimental budget for generative discovery with its own success criteria.
- Set a tradeoff principle: don't sacrifice core SEO fundamentals chasing an unproven channel, but treat generative visibility as a hedge against search behavior shifting over the next 12 months.
What a strong answer includes
- Explicitly separates measurable SEO wins from harder-to-measure generative discovery bets instead of treating them as the same channel.
- Gives concrete product-content assets, like public file links, that plausibly help generative visibility, not just abstract SEO tactics.
- States a resourcing principle, protect the proven channel, hedge on the emerging one, rather than an even split by default.
Common mistakes
- Treats AI answer visibility as measurable the same way as search rankings, when attribution data is often unavailable.
- Allocates resources evenly with no rationale tied to certainty of return.
Likely follow-up questions
- How would you measure success in generative discovery given limited attribution data.
- What would make you pull the budget back from generative discovery bets.
More strategy questions
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- Figma’s Roundtripping area spans Code Context, Design to Code, Code to Design, and the underlying Code Platform. What 12-month strategy would you propose for this area? Define the north star, the sequence of bets across the four surfaces, and the key tradeoffs you’d make between platform investments, workflow quality, and near-term adoption.Figma · Strategy · Hard
- Figma’s internal pattern library is used across multiple products, but product teams want to ship differentiated experiences quickly. How would you decide which UI patterns and interaction models must be standardized versus left flexible, and how would you roll changes out across products without regressing craft, velocity, or stability?Figma · Strategy · Hard
- Figma’s products are increasingly part of one suite, but each product team still optimizes locally. As the PM leader for Platform Experience, how would you define a 12-18 month strategy for shared workflows and interoperability, what principles would you set, how would you prioritize which cross-product inconsistencies to fix first, and how would you avoid turning the platform team into a bottleneck?Figma · Strategy · Hard
- Figma’s AI features could support multiple workflows, including brainstorming, prototyping, and design-to-code. How would you decide which user segments and workflows to prioritize first for growth, and what tradeoffs would you use to justify where to focus?Figma · Strategy · Hard
- Figma wants better connectivity to enterprise codebases, but customer stacks, component systems, and developer workflows vary widely. How would you work with enterprise customers to identify the highest-value integration problems, segment the opportunity, and convert those findings into a prioritized roadmap for Roundtripping?Figma · Strategy · Hard
More questions from Figma
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