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Product Management Root Cause Analysis Question: Investigating Airtable's Gantt view feature adoption decline

Why has the adoption rate of Airtable's new Gantt view feature dropped by 30% over the past month?

Data Analysis Problem Solving Product Strategy SaaS Project Management Productivity Tools
User Experience Data Analysis Root Cause Analysis Feature Adoption SaaS

Introduction

The recent 30% drop in adoption of Airtable's new Gantt view feature over the past month is a concerning trend that requires immediate attention. To address this issue, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term fixes and long-term strategic implications.

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 significant change to the Gantt view feature in the last 1-2 months?

Why it matters: Recent changes could directly impact adoption rates. Expected answer: Yes, there was an update to the UI/UX of the Gantt view. Impact on approach: If true, we'd focus on the changes made and user feedback.

  • Considering user segments, I'm curious about the adoption patterns. Are we seeing this drop across all user types, or is it more pronounced in specific segments?

Why it matters: Helps identify if the issue is universal or segment-specific. Expected answer: The drop is more significant among new users. Impact on approach: We'd investigate onboarding processes and first-time user experience.

  • Thinking about external factors, have there been any notable changes in the project management tool market recently?

Why it matters: Competitive pressures could influence user behavior. Expected answer: A major competitor launched a new Gantt feature last month. Impact on approach: We'd analyze our feature set against competitors and user needs.

  • Regarding data integrity, has there been any change in how we measure or define "adoption" for this feature?

Why it matters: Ensures we're comparing apples to apples in our metrics. Expected answer: No changes in measurement or definition. Impact on approach: If changed, we'd need to recalibrate our analysis based on the new definition.

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