Introduction
The sudden drop in Google Pay's payment success rate to 85% is a critical issue that demands immediate attention and a thorough root cause analysis. This significant decrease in successful transactions not only impacts user experience but also poses potential risks to Google Pay's market position and revenue. I'll approach this problem systematically, examining both internal and external factors to identify the root cause and propose effective solutions.
Framework overview
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Pinpointing the timeframe helps narrow down potential causes. Expected answer: Within the last week or month. Impact on approach: A sudden drop suggests a specific trigger, while a gradual decline might indicate a systemic issue.
Why it matters: Identifying patterns in affected users can reveal underlying issues. Expected answer: Possibly higher impact on new users or specific transaction types. Impact on approach: Targeted investigation of affected segments vs. system-wide analysis.
Why it matters: Recent changes often correlate with performance issues. Expected answer: Yes, a recent update or No, no major changes. Impact on approach: Focus on recent changes or expand search to external factors.
Why it matters: Ensures we're comparing apples to apples in our analysis. Expected answer: No change in metric definition. Impact on approach: If changed, we'd need to reassess the actual impact.
Why it matters: External dependencies can significantly impact performance. Expected answer: Possible issues with specific banks or payment processors. Impact on approach: Investigate external partnerships and integrations.
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