Why has SonderMind's therapist matching algorithm seen a 15% decrease in successful matches over the past month?

Introduction

SonderMind's therapist matching algorithm has experienced a 15% decrease in successful matches over the past month, indicating a significant disruption in the platform's core functionality. This analysis will systematically investigate potential root causes, generate data-driven hypotheses, and propose a strategic plan to address the issue while considering both immediate fixes and long-term improvements.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might have been a recent update to the matching algorithm. Has there been any significant change to the algorithm in the past 1-2 months?

Why it matters: Recent changes could directly impact matching performance. Expected answer: Yes, there was an update to improve match speed. Impact on approach: If confirmed, we'd focus on the algorithm change as a primary factor.

• Considering user behavior, I'm curious about any shifts in the therapist or patient demographics. Have you noticed any changes in the user base composition recently?

Why it matters: Changes in user demographics could affect match compatibility. Expected answer: There's been an increase in younger patients seeking therapy. Impact on approach: We'd need to assess if the algorithm is adapting to changing user needs.

• Thinking about external factors, has there been any significant change in the competitive landscape or market conditions affecting therapist availability?

Why it matters: External pressures could impact the pool of available therapists. Expected answer: No major changes, but there's been a slight increase in demand for therapy services. Impact on approach: We'd need to consider if the algorithm is adjusting for changes in supply and demand.

• Regarding data integrity, I'm wondering if there have been any changes in how successful matches are defined or measured. Has the definition or tracking of a "successful match" remained consistent?

Why it matters: Changes in measurement could artificially affect the reported success rate. Expected answer: The definition has remained consistent. Impact on approach: If confirmed, we can focus on actual performance issues rather than measurement discrepancies.