Why has customer satisfaction with Mashgin's visual AI technology for food recognition declined by 10 points in university cafeterias over the last 60 days?

Introduction

The recent 10-point decline in customer satisfaction with Mashgin's visual AI technology for food recognition in university cafeterias is a critical issue that demands immediate attention. To address this problem, 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.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a seasonal factor. Has there been any change in the student population or cafeteria offerings in the last 60 days?

Why it matters: Seasonal changes could explain the satisfaction drop. Expected answer: No significant changes in student population or menu. Impact on approach: If true, we'd focus more on internal factors.

• Considering the specificity of the decline, I'm curious about our measurement methodology. Has there been any change in how we collect or calculate customer satisfaction data?

Why it matters: Ensures we're comparing apples to apples. Expected answer: No changes in measurement methodology. Impact on approach: If changed, we'd need to reassess the validity of the decline.

• Given the technology focus, I'm wondering about recent updates. Have there been any software updates or changes to the AI model in the past 60-90 days?

Why it matters: Recent changes could directly impact performance. Expected answer: A minor update was pushed 75 days ago. Impact on approach: If true, we'd prioritize investigating that update.

• Thinking about user segments, I'm curious if this decline is uniform. Are we seeing differences in satisfaction across different types of foods or meal times?

Why it matters: Helps pinpoint if the issue is general or specific. Expected answer: The decline is more pronounced for certain food types. Impact on approach: If true, we'd focus on those specific categories.