Introduction
The sudden 50% decrease in agent matches on HomeLight's agent finder platform last week is a critical issue that demands 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's success.
I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into the product's 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: Recent changes often correlate with sudden metric shifts. Expected answer: Yes, there was a minor UI update. Impact on approach: If yes, I'd focus on the update's impact on user behavior.
Why it matters: Segmentation helps isolate the problem and target solutions. Expected answer: The decrease is more significant among first-time users. Impact on approach: If segmented, I'd analyze the most affected group's journey.
Why it matters: Metric definition changes can cause apparent performance shifts. Expected answer: No changes to the metric definition. Impact on approach: If changed, I'd focus on reconciling old and new measurements.
Why it matters: External events can dramatically impact user behavior and platform performance. Expected answer: No major market shifts, but a competitor launched a new feature. Impact on approach: If external factors are present, I'd analyze their potential influence.
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