Introduction
The recent 25% decline in click-through rates for Farfetch's product recommendation emails to UK customers is a concerning trend that requires immediate attention. This analysis will systematically investigate potential root causes, generate data-driven hypotheses, and propose actionable solutions to address the issue.
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 trends can significantly impact e-commerce behavior. Expected answer: No major holidays or events during this period. Impact on approach: If confirmed, we'll focus more on internal factors.
Why it matters: Recent changes often correlate with performance shifts. Expected answer: A minor update to the recommendation algorithm was implemented. Impact on approach: This would shift our focus to technical and product-related hypotheses.
Why it matters: Market dynamics can heavily influence consumer behavior. Expected answer: No major changes in the UK fashion retail market. Impact on approach: If confirmed, we'll prioritize internal factors over external market conditions.
Why it matters: Segmented analysis can reveal targeted issues. Expected answer: The decline is more pronounced among newer customers. Impact on approach: This would lead us to investigate onboarding and new user experience more closely.
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