Introduction
LivePerson's Intent Manager accuracy decline of 8% for retail clients in the past quarter is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term fixes and long-term strategic implications.
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Seasonal patterns could explain temporary fluctuations in accuracy. Expected answer: No significant correlation with seasonal events. Impact on approach: If seasonal, we'd focus on adapting the model for cyclical changes.
Why it matters: Changes in customer behavior could affect the model's ability to accurately interpret intents. Expected answer: Some shifts in online shopping trends and customer service expectations. Impact on approach: We'd need to update our training data and potentially adjust our model architecture.
Why it matters: Context is crucial for understanding the severity of the issue and setting appropriate goals. Expected answer: Previous accuracy was around 90%, which is above industry average. Impact on approach: This would help us set realistic improvement targets and prioritize our efforts.
Why it matters: Internal changes could directly impact the model's performance. Expected answer: A minor update was pushed two months ago. Impact on approach: We'd need to investigate the impact of this update and potentially rollback or refine it.
Why it matters: Ensures we're comparing apples to apples and not dealing with a measurement artifact. Expected answer: No changes in measurement methodology or tools. Impact on approach: If there were changes, we'd need to re-evaluate our historical data for consistency.
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