Virtual Assistant Performance Metrics
These quantifiable measures evaluate how effectively and efficiently SUVA resolves customer queries.
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Business Metrics
These metrics assess the return on investment (ROI) associated with SUVA implementation.
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LLM Usage Metrics
These metrics encompass key aspects of user interactions with large language models (LLMs)
Total Requests
Usually assessed through post-interaction surveys or feedback mechanisms, providing invaluable insights into user satisfaction levels and overall service quality.
Input Tokens
Measure the total number of tokens used by the LLM to process user queries, offering insight into the complexity and depth of interactions with the LLM.
Output Tokens
Assess the total number of tokens utilized by the LLM to generate contextual chat responses, reflecting the richness and detail of the generated content.
Average Response Time(s)
Calculate the average duration taken by the LLM to process and respond to queries, aiding in understanding the efficiency and responsiveness of LLM-driven interactions.
Average Error Rate(%)
Evaluate the average percentage of queries where the LLM fails to respond, offering insights into areas for improvement and fine-tuning of LLM capabilities.
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