What factors are contributing to the sudden increase in customer support tickets related to OneStudyTeam's TrialSite product in the last two weeks?

Introduction

The sudden increase in customer support tickets related to OneStudyTeam's TrialSite product over the past two weeks is a critical issue that demands immediate attention. As we delve into this problem, we'll employ a systematic approach to identify, validate, and address the root cause while considering both short-term fixes and long-term strategic implications.

Our analysis will follow a structured framework, beginning with clarifying questions to establish context, followed by a thorough examination of potential external factors. We'll then dissect the product's user journey, break down relevant metrics, gather and prioritize data, form hypotheses, conduct root cause analysis, and finally propose validation methods and next steps.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might have been a recent product update. Has there been any significant change to TrialSite in the last month?

Why it matters: Recent changes often correlate with support ticket spikes. Expected answer: Yes, a new feature was rolled out three weeks ago. Impact on approach: If confirmed, we'd focus on the new feature's implementation and user onboarding.

• Given the nature of TrialSite, I'm wondering about seasonal patterns. Are we in a period where clinical trial activity typically increases?

Why it matters: Seasonal fluctuations could explain increased usage and, consequently, more support tickets. Expected answer: There's a slight increase in trial activity, but not significantly different from previous years. Impact on approach: If confirmed, we'd need to investigate why this year's increase is causing more issues than usual.

• Considering the support ticket increase, I'm curious about the specific types of issues being reported. What are the top three categories of complaints in these tickets?

Why it matters: Understanding the nature of the issues helps narrow down potential root causes. Expected answer: Login problems, data synchronization issues, and difficulties in scheduling patient visits. Impact on approach: This would guide our technical investigation and help prioritize areas of focus.

• Thinking about user segments, I'm wondering if this issue is affecting all users equally. Are we seeing a disproportionate increase in tickets from any particular user group or role?

Why it matters: Identifying affected user segments can point to specific product areas or use cases causing problems. Expected answer: There's a higher proportion of tickets from clinical research coordinators compared to other roles. Impact on approach: We'd focus on the specific workflows and features used by this user group.