Introduction
New Engen's automated bidding algorithm has experienced a 15% decrease in conversion rates over the past month, signaling 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 strategic implications.
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: Seasonal fluctuations could explain the change without indicating a problem in the algorithm. Expected answer: No significant seasonal trend observed in previous years. Impact on approach: If seasonal, we'd focus on adjusting for cyclical patterns rather than algorithm issues.
Why it matters: Identifying affected segments could pinpoint specific issues or user behaviors. Expected answer: The decrease is more pronounced in certain user segments. Impact on approach: We'd investigate those segments' unique characteristics or recent changes affecting them.
Why it matters: Recent changes could directly impact performance and provide a clear starting point for investigation. Expected answer: A minor update was implemented three weeks ago. Impact on approach: We'd focus on analyzing the impact of that specific update.
Why it matters: External shifts could affect conversion rates independently of the algorithm's performance. Expected answer: No major market shifts, but some competitors have adjusted their strategies. Impact on approach: We'd analyze competitor actions and their potential impact on our performance.
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