Introduction
Zoopla's "Instant Valuation" feature experiencing a 40% increase in error rates during peak hours over the past two weeks is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term fixes and long-term implications for the product.
I'll approach this problem by first clarifying the context, then ruling out external factors before diving deep into the product mechanics, metric breakdown, and data analysis. From there, I'll form hypotheses, conduct root cause analysis, and propose validation methods and solutions.
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Recent changes often correlate with performance issues. Expected answer: Yes, there was a minor update to the valuation algorithm. Impact on approach: If yes, I'd focus on the changes made and their potential impact.
Why it matters: Peak hour issues often indicate capacity problems. Expected answer: Traffic has increased by 20% in the last month. Impact on approach: High traffic would lead me to investigate scalability solutions.
Why it matters: Different error types point to different root causes. Expected answer: Mostly timeout errors and incorrect valuations. Impact on approach: This would guide my technical investigation focus.
Why it matters: External factors can indirectly impact system performance. Expected answer: No major market shifts, but a competitor launched a similar feature. Impact on approach: This would influence whether I focus more on internal or external factors.
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