Introduction
The recent 30% drop in completed virtual consultations for Babylon Health's GP at Hand service 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 the service.
I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into the product, user journey, and metrics. From there, I'll form data-driven hypotheses, conduct root cause analysis, and propose validation methods and solutions.
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 patterns could explain fluctuations and inform our approach. Expected answer: No significant seasonal correlation. Impact on approach: If seasonal, we'd focus on year-over-year comparisons and cyclical strategies.
Why it matters: Identifying affected segments helps pinpoint potential causes and tailor solutions. Expected answer: The drop is more pronounced in younger users. Impact on approach: We'd investigate factors specifically affecting younger users' engagement.
Why it matters: Recent changes could directly impact user behavior and consultation completion rates. Expected answer: A minor UI update was implemented two weeks ago. Impact on approach: We'd scrutinize the UI changes and their potential impact on user experience.
Why it matters: Technical issues could directly affect users' ability to complete consultations. Expected answer: No significant technical issues reported. Impact on approach: If technical issues are present, we'd prioritize resolving them before exploring other factors.
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