Introduction
The 20% decline in average order value (AOV) for grocery items on Souq Now compared to last month is a significant issue that requires immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term and long-term implications for our product and business.
I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into our product, user journey, and relevant metrics. From there, I'll form data-driven 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: Seasonal trends can significantly impact grocery shopping behavior. Expected answer: No significant seasonal changes noted. Impact on approach: If seasonal, we'd focus on year-over-year comparisons instead of month-to-month.
Why it matters: Different segments may have different reasons for changing behavior. Expected answer: The decline is relatively uniform across segments. Impact on approach: If segment-specific, we'd tailor our solutions to those particular groups.
Why it matters: Internal changes could directly impact user behavior and AOV. Expected answer: No major changes implemented recently. Impact on approach: If recent changes occurred, we'd focus on analyzing their specific impact.
Why it matters: External market forces could be driving users to alternatives. Expected answer: No significant competitive shifts noted. Impact on approach: If competitive factors are at play, we'd need to consider market positioning and differentiation strategies.
Why it matters: Ensures we're dealing with a real issue, not a data anomaly. Expected answer: No changes to AOV calculation or tracking. Impact on approach: If data issues are present, we'd need to address those before diving into user behavior analysis.
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