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Why has One Medical (Clinics/Outpatient Services)'s same-day appointment booking feature seen a 30% decrease in utilization over the past month?

Prepared by NextSprints

15 mins
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Data Analysis Hypothesis Testing Problem-Solving Healthcare Digital Health SaaS Product Metrics Root Cause Analysis User Behavior Feature Adoption Healthcare Tech
Product Management Root Cause Analysis Question: Investigating One Medical's same-day appointment booking decline

Introduction

One Medical's same-day appointment booking feature has experienced a 30% decrease in utilization over the past month, raising concerns about user engagement and potential issues with the service. This analysis will systematically identify, validate, and address the root cause while considering both immediate and long-term implications for the product and business.

I'll approach this issue by first clarifying key details, ruling out external factors, understanding the product and user journey, breaking down the metric, gathering relevant data, forming hypotheses, conducting root cause analysis, and finally proposing validation methods and next steps.

Framework overview

This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.

Step 1

Clarifying Questions (3 minutes)

  • Looking at the timing, I'm thinking there might be seasonal factors at play. Has there been any change in overall appointment demand compared to the same period last year?

Why it matters: Seasonal trends could explain the decrease and inform our solution approach. Expected answer: No significant change in overall demand compared to last year. Impact on approach: If true, we'd focus more on internal factors rather than external seasonal influences.

  • Considering user segments, I'm curious about the distribution of the decrease. Is the 30% drop consistent across all user demographics, or is it more pronounced in specific groups?

Why it matters: Identifying affected segments could point to specific user needs or issues. Expected answer: The decrease is more significant among younger users aged 25-35. Impact on approach: We'd investigate factors specifically affecting this demographic, such as app usability or marketing changes.

  • Thinking about recent changes, have there been any updates to the booking interface or process in the last 1-2 months?

Why it matters: Recent changes could directly impact user behavior and feature utilization. Expected answer: A minor UI update was implemented six weeks ago. Impact on approach: We'd closely examine the impact of this update on user experience and booking flow.

  • Considering system performance, has there been any change in the app's uptime or response time for the booking feature?

Why it matters: Technical issues could be deterring users from using the feature. Expected answer: No significant changes in system performance metrics. Impact on approach: We'd shift focus from technical infrastructure to user experience and product design.

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Updated Mar 29, 2025