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

Senior

May 2026

Summary

Meta PM interview with a product design question about building a cleaner-finding app. Pretty open-ended, which I wasn't fully prepared for.

Questions Asked (1)

Design a web app that helps users find a cleaner.

Product Sense & IdeationProduct StrategySystem Design

Author's notes

I went straight into features and the interviewer kind of just waited.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the scope and goals of the web app, then segment users and identify their pain points in finding a cleaner. Prioritize features based on impact and feasibility, and outline a high-level system design that supports the core user journey.

Pro tip: Anchor your design around trust and safety—these are the biggest barriers in hiring service providers. Show how your solution verifies cleaners, handles payments securely, and manages disputes to build user confidence.

1. Clarify Goals and Scope

Ask clarifying questions to understand the target users, platform (web app), and key success metrics. Define whether this is a marketplace, aggregator, or direct hiring tool.

2. User Segmentation and Pain Points

Identify primary user segments (e.g., busy professionals, elderly, families) and their specific needs and pain points when searching for a cleaner. Prioritize one segment to focus on.

3. Feature Prioritization

Brainstorm features that address pain points, then prioritize using a framework like RICE or MoSCoW. Focus on core features: search, booking, payment, reviews, and verification.

4. High-Level System Design

Outline the architecture: front-end (user interface), back-end (matching algorithm, database), and third-party integrations (payments, identity verification). Consider scalability and data flow.

5. Success Metrics and Iteration

Define key metrics (e.g., booking completion rate, user retention, cleaner utilization) and propose an MVP with a roadmap for future enhancements based on user feedback.

Key Points to Mention

Trust and safety mechanisms: background checks, insurance, secure payments, and dispute resolution.
Matching algorithm: factors like location, availability, skills, ratings, and price to ensure good matches.
User experience: simple search, transparent pricing, easy scheduling, and communication tools.
Monetization strategy: commission fees, subscription models, or featured listings.
Scalability considerations: handling growth in users and cleaners, geographic expansion, and performance.
Regulatory and compliance issues: licensing, tax, and employment classification of cleaners.

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