Why has Morningstar's Advisor Workstation seen a 15% drop in daily active users over the past month?

Introduction

The 15% drop in daily active users for Morningstar's Advisor Workstation over the past month is a significant issue that requires immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term and long-term implications for the product and its users.

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.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be seasonality at play. Has this 15% drop been compared to the same period last year?

Why it matters: Seasonal fluctuations could explain the drop and impact our solution approach. Expected answer: Yes, it has been compared, and this drop is unusual for this time of year. Impact on approach: If seasonal, we'd focus on why this year is different; if not, we'd look at recent changes or issues.

• Considering user segments, I'm curious about the distribution of the drop. Is the 15% decrease uniform across all user types, or are certain segments more affected?

Why it matters: Identifying affected segments helps narrow down potential causes and tailor solutions. Expected answer: The drop is more pronounced among financial advisors managing smaller portfolios. Impact on approach: We'd focus on features or changes that disproportionately affect this user segment.

• Thinking about recent changes, have there been any significant updates to the Advisor Workstation in the past 1-2 months?

Why it matters: Recent changes often correlate with shifts in user behavior and could be the root cause. Expected answer: A new portfolio analysis tool was launched six weeks ago. Impact on approach: We'd investigate the new tool's adoption rate and any issues related to its implementation.

• Considering data integrity, has there been any change in how daily active users are measured or in the systems tracking this metric?

Why it matters: Ensures we're not chasing a phantom problem due to measurement errors. Expected answer: No changes in measurement or tracking systems. Impact on approach: Confirms the issue is real and not a data anomaly, focusing our efforts on actual usage patterns.