How can we explain the sudden 25% increase in customer support tickets related to Korn Ferry's Talent Hub platform in the last month?

Introduction

The sudden 25% increase in customer support tickets related to Korn Ferry's Talent Hub platform in the last month is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term fixes and long-term strategic implications.

I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into the product, user journey, and relevant metrics. From there, I'll generate data-driven hypotheses, conduct root cause analysis, and propose validation methods and solutions.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a recent product update. Has there been any significant change to the Talent Hub platform in the past 1-2 months?

Why it matters: Recent changes often correlate with support ticket spikes. Expected answer: Yes, there was a major update. Impact on approach: If yes, I'd focus on change-related issues; if no, I'd look at external factors or gradual degradation.

• Considering user segments, I'm curious about the distribution of these tickets. Are they coming from a specific user group or spread across all users?

Why it matters: Helps identify if it's a localized or system-wide issue. Expected answer: Concentrated in a specific user group. Impact on approach: If concentrated, I'd focus on that group's unique characteristics or usage patterns.

• Thinking about the nature of the tickets, I'm wondering about their content. What are the top 3 issues being reported in these support tickets?

Why it matters: Reveals potential patterns or common pain points. Expected answer: Specific feature failures, login issues, data inconsistencies. Impact on approach: Would guide my technical and user experience investigations.

• Considering system health, I'm curious about our monitoring. Have there been any unusual patterns in system performance or error logs coinciding with this increase?

Why it matters: Could indicate technical issues not immediately visible to users. Expected answer: Some anomalies in error logs but no major outages. Impact on approach: If yes, I'd prioritize technical investigations; if no, I'd focus more on user behavior or external factors.