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Google·Product Manager·Onsite - Product Sense / Strategy·Senior

Senior
May 2026

Summary

Google PM interview with a single open-ended product design question. Pretty classic format but the question itself had a lot of room to go sideways.

Questions Asked (1)

Q1

How would you design a next-generation elevator?

Product Sense & IdeationProduct StrategySystem Design
Author's notes

I went straight to user pain points which felt right, but I spent way too long on the obvious stuff like wait times and button interfaces.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the goals and constraints of a 'next-generation' elevator, then segment users and use cases to identify key pain points. Propose a prioritized set of features that leverage Google's strengths in AI, cloud, and data, and define success metrics and a rollout plan.

Pro tip: Anchor your design in user needs and business value, not just technology; show how you'd validate assumptions with experiments and iterate based on data.

1. Clarify Goals and Constraints

Ask questions to understand the scope: Is this for new buildings or retrofits? What are the budget, timeline, and regulatory constraints? What does 'next-generation' mean to stakeholders?

2. Identify Users and Pain Points

Segment users (e.g., passengers, building managers, maintenance crews) and map their pain points such as wait times, crowding, energy efficiency, and accessibility.

3. Brainstorm and Prioritize Features

Generate ideas like AI-based predictive dispatching, personalized experiences via Google Assistant, IoT sensors for predictive maintenance, and energy recovery systems. Prioritize using impact vs. effort or RICE.

4. Define Success Metrics and Validation

Establish metrics like average wait time, energy consumption, user satisfaction, and uptime. Outline how to test assumptions via prototypes, simulations, or pilot deployments.

5. Plan Rollout and Iteration

Propose a phased rollout starting with a pilot building, gather data, iterate, and scale. Consider partnerships with elevator manufacturers and integration with Google's ecosystem.

Key Points to Mention

  • Leverage AI and machine learning for predictive dispatching and demand forecasting to reduce wait times.
  • Integrate with Google Assistant for voice control and personalized user experiences (e.g., destination dispatch).
  • Use IoT sensors and cloud analytics for predictive maintenance and real-time monitoring.
  • Incorporate energy-efficient technologies like regenerative drives and smart scheduling.
  • Ensure accessibility and safety compliance, and address privacy concerns with data collection.
  • Define clear success metrics and a phased rollout strategy with pilot testing.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.