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Company focus

Appfire

What factors are contributing to the sudden 50% increase in support tickets for Appfire's Confluence Reporting & Dashboards app in the last two weeks?

Prepared by NextSprints

15 mins
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Problem Solving Data Analysis Product Improvement SaaS Enterprise Software Productivity Tools Data Analytics Root Cause Analysis Product Troubleshooting Support Tickets Atlassian Ecosystem
Product Management Root Cause Analysis Question: Investigating sudden increase in support tickets for Confluence app

Introduction

The sudden 50% increase in support tickets for Appfire's Confluence Reporting & Dashboards app over the past two weeks 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 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.

Framework overview

This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.

Step 1

Clarifying Questions (3 minutes)

  • Looking at the timing, I'm thinking there might have been a recent update. Has there been any change to the app or Confluence itself in the last month?

Why it matters: Recent changes often correlate with support ticket spikes. Expected answer: Yes, there was an update to the app two weeks ago. Impact on approach: If confirmed, I'd focus on changes introduced in the update.

  • Given the specificity of the 50% increase, I'm curious about the baseline. What's the typical volume of support tickets for this app in a two-week period?

Why it matters: Understanding the scale helps prioritize the issue and resource allocation. Expected answer: Around 200 tickets per two weeks. Impact on approach: A higher baseline would indicate a more severe problem requiring immediate action.

  • Considering user segments, I'm wondering if this increase is uniform across all users. Are we seeing any patterns in terms of user types or specific features mentioned in these tickets?

Why it matters: Identifying affected segments can narrow down potential causes. Expected answer: Enterprise users are reporting more issues with custom dashboard creation. Impact on approach: I'd focus on enterprise-specific features and custom dashboard functionality.

  • Thinking about the app's ecosystem, have there been any changes to Confluence or related Atlassian products that might impact our app's functionality?

Why it matters: External changes could be causing compatibility issues. Expected answer: Confluence had a minor update three weeks ago. Impact on approach: I'd investigate potential compatibility issues with the recent Confluence update.

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Updated Jan 22, 2025