Introduction
The recent 15% drop in average order value (AOV) for GrabFood across major Southeast Asian cities is a significant concern 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 factors could explain temporary changes in user behavior. Expected answer: No significant seasonal events during this period. Impact on approach: If confirmed, we'd focus more on internal factors or market changes.
Why it matters: Identifying specific affected segments could narrow down potential causes. Expected answer: The drop is more pronounced among frequent users. Impact on approach: We'd investigate factors specifically affecting loyal customers.
Why it matters: Recent changes could directly impact user behavior and order values. Expected answer: A new UI was rolled out two weeks ago. Impact on approach: We'd examine how the UI change might have affected ordering patterns.
Why it matters: Competitive pressures could be driving users to adjust their ordering habits. Expected answer: A major competitor launched an aggressive discount campaign. Impact on approach: We'd analyze our pricing strategy and value proposition relative to competitors.
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