Should we build collaborative editing?
Last updated: October 22, 2025
Quick Overview
Your team is considering building push notifications. How would you evaluate this decision?
OpenAI
October 22, 20257
5
1,314 solved
Your team is considering building push notifications. How would you evaluate this decision?
This product question from OpenAI's Onsite goes beyond feature brainstorming. The interviewer expects a framework-driven approach that considers market dynamics, user segmentation, and data-informed decision making.
What the Interviewer Expects
- Apply a structured framework for product thinking (user, problem, solution, metrics)
- Segment users and identify differentiated needs
- Prioritize features using a clear framework (RICE, ICE, impact vs effort)
- Define comprehensive success metrics across the user funnel
- Consider competitive dynamics and market positioning
Key Topics to Cover
How to Approach This
- Start with the user. Who are they, what problem do they have, and what is their current workaround?
- Use a prioritization framework: impact vs effort, RICE scoring, or ICE scoring.
- Define success metrics using the AARRR framework: Acquisition, Activation, Retention, Revenue, Referral.
- Consider second-order effects. A feature might boost short-term engagement but hurt long-term retention.
Possible Follow-up Questions
- How would you handle pushback from engineering on feasibility?
- How would you validate this idea before committing engineering resources?
- What would you do if usage data contradicts user feedback?
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Browse Product QuestionsSample Answer
Problem Framing
To evaluate whether OpenAI should build collaborative editing functionality, we need to frame the problem around enhancing user engagement and productivity. The specific goal is to determine how colla...
User & Market Context
The primary users for a collaborative editing feature would be professionals and teams who utilize OpenAI's tools for brainstorming, drafting content, or technical writing. These users value efficienc...
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