Introduction
The sudden increase in appointment cancellation rates for specialist consultations in the Paris region on Doctolib is a critical 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 the platform and its users.
To tackle this problem, I'll follow a structured approach that covers issue identification, hypothesis generation, validation, and solution development. My response will be organized into distinct sections, each focusing on a crucial aspect of the analysis.
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 patterns could explain temporary spikes and inform our solution approach. Expected answer: The increase started in early summer. Impact on approach: If seasonal, we'd focus on temporary adjustments rather than systemic changes.
Why it matters: This could point to specific issues within certain medical fields or appointment types. Expected answer: Dermatologists and short consultations are most affected. Impact on approach: We'd tailor our solution to address the most impacted segments first.
Why it matters: Recent changes could have unintended consequences on user behavior. Expected answer: A new cancellation feature was implemented two months ago. Impact on approach: We'd focus on analyzing the impact of this specific feature change.
Why it matters: Policy changes could affect patient behavior across the board. Expected answer: No major policy changes have been reported. Impact on approach: We'd shift focus to internal factors and user behavior patterns.
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