Introduction
The recent 20% decrease in average order value (AOV) for Klarna's one-time card feature 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 trends could explain temporary fluctuations in AOV. Expected answer: No significant seasonal correlation observed. Impact on approach: If seasonal, we'd focus on year-over-year comparisons and cyclical patterns.
Why it matters: Identifying specific affected segments could pinpoint targeted issues. Expected answer: The decrease is more pronounced among newer users. Impact on approach: We'd investigate onboarding processes and new user experience if this is the case.
Why it matters: Recent changes could directly impact user behavior and AOV. Expected answer: A minor UI update was implemented last month. Impact on approach: We'd closely examine the impact of this update on user interaction and purchase behavior.
Why it matters: External market forces could be driving changes in user behavior. Expected answer: No major competitive shifts, but general economic uncertainty has increased. Impact on approach: We'd consider broader economic factors and their impact on consumer confidence.
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