What metrics do you use to evaluate the ongoing performance and relevance of your AI models and tools?

Model Performance Metrics: Accuracy, Precision, Recall and some other measures here.

Operational Metrics: Latency (time taken for generating responses, the lower the latency the better), Uptime and Reliability:

Business Impact Metrics: Customer Retention Rate, NPS, CSAT

Customer Feedback and Sentiment Metrics:

• Feedback Scores: Collects customer feedback on AI interactions, providing qualitative insights into the effectiveness and user satisfaction.

• Sentiment Analysis: Analyzes customer sentiment from feedback and interactions, helping understand the emotional response to AI-driven services.

Economic Metrics:

• Return on Investment (ROI): Evaluates the financial impact of AI initiatives, comparing the benefits derived from AI tools against their costs.

• Cost Savings: Measures the reduction in operational costs due to the automation and efficiency gains provided by AI

Usage and Engagement Metrics:

• Adoption Rates: Tracks the adoption of AI-driven features by customers, indicating their perceived value and usability.

• Feature Utilization: Measures how frequently specific AI features are used, helping identify popular functionalities and areas for improvement