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

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2 Answers
  1. Twinkle Bandla
    Twinkle Bandla

    Gainsight Associate Director, Client outcomes • 10mo

    Thanks for the interesting question. Performance assessment on any new rollout of AI models plays a crucial role. Think from the perspective of a new agent/AI feature that is launched in your product. It's important to assess it from three areas: Accuracy: How accurate are the responses? Get instant feedback from users (based on thumbs up and thumbs down). Let me give you a simple example: if you have launched an AI feature that scans and reads all the feedback from customers and categorizes it ...Read More

    1,118 Views
  2. Meenal Shukla
    Meenal Shukla

    Zoom Head of Scaled Customer Success, Onboarding, Learning and Adoption • 1y

    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 ...Read More

    656 Views

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