What factors are contributing to the recent 20% increase in cancellation rates for GLG's scheduled phone consultations?

Introduction

The recent 20% increase in cancellation rates for GLG's scheduled phone consultations 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 GLG's business model and customer satisfaction.

I'll approach this problem by first clarifying the context, then ruling out external factors before diving deep into the product ecosystem, user journey, and potential internal causes. My analysis will culminate in a set of actionable recommendations and a decision framework for moving forward.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a seasonal component. Has this increase occurred during a specific time of year or is it consistent across all seasons?

Why it matters: Seasonal patterns could indicate external factors rather than product issues. Expected answer: The increase is not tied to any particular season. Impact on approach: If seasonal, we'd focus on cyclical factors; if not, we'd prioritize internal product and user experience issues.

• Considering user segments, I'm wondering if this affects all user types equally. Are we seeing higher cancellation rates in specific user groups (e.g., experts, clients) or industries?

Why it matters: Segmentation could reveal targeted issues rather than system-wide problems. Expected answer: The increase is more pronounced among client-side users. Impact on approach: If segmented, we'd focus on specific user journeys; if universal, we'd look at broader system issues.

• Thinking about recent changes, have there been any significant updates to the scheduling system or user interface in the past 3-6 months?

Why it matters: Recent changes could directly correlate with the increase in cancellations. Expected answer: A new scheduling interface was implemented 4 months ago. Impact on approach: If changes occurred, we'd scrutinize those specific updates; if not, we'd look at gradual shifts in user behavior or external factors.

• Considering data integrity, has there been any change in how cancellations are tracked or defined in the system?

Why it matters: Ensures we're comparing apples to apples and not seeing a false increase due to measurement changes. Expected answer: No changes in cancellation tracking or definition. Impact on approach: If changed, we'd need to recalibrate our analysis; if not, we can proceed with confidence in the data's consistency.