Several FB users have experienced shopping integrity issues, where the product they received is different and/or much lower quality than expected (i.e., misalignment between product advertised via FB ad and product received). How would you determine if this is a problem worth solving and what product enhancements would you make to address this issue?

Introduction

Shopping integrity issues on Facebook, where users receive products that differ significantly from what was advertised, present a critical challenge for the platform's e-commerce ecosystem. This misalignment between expectations and reality not only erodes user trust but also threatens the viability of Facebook as a reliable marketplace. To address this complex issue, I'll employ a systematic approach to identify the root cause, validate our hypotheses, and develop both immediate and long-term solutions.

Step 1

Clarifying Questions (3 minutes)

• What percentage of users are reporting this issue, and how has this trend changed over time?

• Are there specific product categories or price ranges where this problem is more prevalent?

• What is the current process for vetting advertisers and their products on the platform?

• Have there been any recent changes to Facebook's advertising policies or algorithms?

Why these questions matter: Understanding the scope and trends helps prioritize the issue. Identifying patterns in affected products can point to specific vulnerabilities. Knowing the current vetting process highlights potential gaps, while recent policy changes could explain sudden shifts in product quality.

Hypothetical answers:

• 5% of users report issues, up from 2% last quarter
• Problems are most common in electronics and fashion items priced $50-$200
• Advertisers undergo basic identity verification, but product quality isn't directly assessed
• A recent algorithm change prioritized engagement over advertiser history

Impact on approach: These answers would suggest a significant, growing problem that requires immediate attention. We'd focus on high-risk categories and price points, review the vetting process, and investigate the impact of recent algorithm changes.