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LinkedIn·Product Designer·Onsite - Product Sense / Strategy·Senior

SeniorPrefer not to say
Apr 2026

Summary

LinkedIn product design interview, one question about building a full onboarding flow from scratch. Pretty open-ended and I wasn't totally sure how deep they wanted me to go.

Questions Asked (1)

Q1

Design the end-to-end user onboarding experience for a mobile or web app.

Product Sense & IdeationProduct StrategyProduct Analytics & Metrics
Author's notes

I jumped straight into screens and flows without anchoring on what kind of app or what success looks like for a new user.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the product context and target user, then define what successful onboarding means for both the user and the business. Structure your answer around a user journey framework, covering discovery, activation, and retention, and tie each design decision to measurable metrics.

Pro tip: Anchor your design in a specific user segment and their core job-to-be-done, then show how you would validate assumptions with data and iterate. This demonstrates product sense and analytical rigor, which LinkedIn values.

1. Clarify Context and Goals

Ask clarifying questions to understand the product, target audience, and business objectives. Define success metrics such as activation rate, time-to-value, and retention.

2. Map the User Journey

Identify key stages from first touch to habitual use, including pre-signup, signup, first key action, and return visits. Highlight potential friction points at each stage.

3. Design the Onboarding Flow

Propose specific screens and interactions that guide users to their 'aha moment' quickly. Prioritize progressive disclosure, personalization, and clear value propositions.

4. Define Metrics and Iterate

Select quantitative and qualitative metrics to measure onboarding effectiveness. Outline an A/B testing plan and feedback loops to continuously improve the experience.

Key Points to Mention

  • Activation metrics (e.g., % of users completing key action within first session)
  • Time-to-value and reducing friction in signup/login
  • Personalization based on user goals or referral source
  • Progressive disclosure to avoid overwhelming users
  • A/B testing and experimentation for continuous improvement
  • Alignment with LinkedIn's professional context and network effects

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