Why has Cognite's Data Fusion adoption rate dropped by 15% among industrial customers over the past quarter?

Introduction

Cognite's Data Fusion adoption rate decline among industrial customers is a critical issue that demands immediate attention. This 15% drop over the past quarter could significantly impact our market position and revenue. I'll approach this problem systematically, focusing on identifying the root cause, validating hypotheses, and developing both short-term and long-term solutions.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be seasonal factors at play. Have we seen similar adoption rate fluctuations in previous quarters?

Why it matters: Helps distinguish between cyclical patterns and genuine problems. Expected answer: No significant seasonal patterns observed previously. Impact on approach: If seasonal, we'd focus on strategies to smooth out adoption rates across quarters.

• Considering the specificity of the drop, I'm wondering about our measurement accuracy. Has there been any change in how we calculate or track the adoption rate recently?

Why it matters: Ensures we're addressing a real issue, not a measurement artifact. Expected answer: No recent changes in measurement methodology. Impact on approach: If measurement issues are found, we'd prioritize data quality improvements.

• Given the industrial customer focus, I'm curious about recent market trends. Have there been any significant industry-wide changes or economic shifts affecting our target market?

Why it matters: Helps differentiate between internal issues and external market forces. Expected answer: Some economic uncertainty, but no major industry disruptions. Impact on approach: If market-driven, we'd need to adjust our value proposition or target new segments.

• Thinking about product changes, have we recently rolled out any major updates or alterations to Data Fusion?

Why it matters: Identifies potential internal triggers for the adoption rate drop. Expected answer: A few minor updates, but no significant overhauls. Impact on approach: If linked to recent changes, we'd focus on specific feature improvements or rollbacks.