Case Study 4 - Root Cause Analysis - Facebook Friend Requests Down by 10 %

You are a Product Manager at Facebook. Friend requests have suddenly dropped by 10% overnight, and the company wants to understand why and how to respond.

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Initial Clarification & Scoping:

The candidate starts by narrowing down the problem:

• The drop is sudden and happened overnight.

• It’s not seasonal, unexpected, and shows no variance in historical trends.

• The drop is happening in the US and across all platforms (iOS, Android, web).

• It is specific to friend requests, not other features.

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Root Cause Exploration Approach:

The candidate categorizes investigation into four buckets: internal, contextual, user behavior, and external factors.

1. Internal Checks:

• System issues: No known degradation or system outages.

• Product/UI changes: None that deprioritized or altered friend requests.

• Data quality: Trustworthy, no anomalies reported.

2. External Factors:

• User behavior: No sudden change observed.

• Competitive landscape: TikTok is evolving to become more social, which could pull user attention away from Facebook’s friend request flow.

• Regulatory changes: A new European privacy law went into effect overnight, blocking Facebook’s ability to operate in a European country—this indirectly impacts friend connections with/from the US.

• Marketing changes: Facebook has reduced marketing budget, possibly weakening user re-engagement or perception during a critical period.

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Hypothesis:

The candidate synthesizes the situation into three likely contributing factors:

1. Regulatory constraints in Europe limiting cross-border friend requests.

2. TikTok’s shift to social features potentially capturing user attention.

3. Reduced marketing efforts during a sensitive time, leading to reduced visibility and engagement.

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Next Steps as PM:

• Collaborate with privacy/legal teams to fully understand the new law and identify at what point in the user flow it breaks compliance.

• Ideate alternative solutions, such as UI changes or consent-based flows, to regain compliance and re-enable the friend request feature in the affected region.

• Test new designs to evaluate effectiveness.

• Monitor competitor features and user adoption trends to stay proactive.

• Evaluate the need to increase marketing efforts to offset user loss and rebuild trust or awareness.

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Conclusion:

The candidate demonstrates a structured, methodical approach: clarifying the scope, performing a segmented root cause analysis, forming hypotheses from internal and external signals, and proposing practical next steps for mitigation and product iteration.