Data Analysis
Last updated
Last updated
The Overview -- Data Analysis section displays metrics such as usage, active users, and LLM (Language Learning Model) invocation costs. This allows you to continuously improve the effectiveness, engagement, and cost-efficiency of your application operations. We will gradually provide more useful visualization capabilities, so please let us know what you need.
Total Messages
Reflects the total number of daily interactions between users and AI. Each time the AI answers a user's question, it counts as one message. Prompt orchestration and debugging sessions are not included.
Active Users
The number of unique users who have had effective interactions with the AI, defined as having more than one question-and-answer exchange. Prompt orchestration and debugging sessions are not included.
Average Session Interactions
Reflects the number of continuous interactions per session user. For example, if a user has a 10-round Q&A with the AI, it is counted as 10. This metric reflects user engagement. It is available only for conversational applications.
Token Output Speed
The number of tokens output per second, indirectly reflecting the model's generation rate and the application's usage frequency.
User Satisfaction Rate
The number of likes per 1,000 messages, reflecting the proportion of users who are very satisfied with the answers.
Token Usage
Reflects the daily token expenditure for language model requests by the application, useful for cost control.
Total Conversations
Daily AI conversation count; each new conversation session counts as one. A single conversation session may contain multiple message exchanges; messages related to prompt engineering and debugging are not included.
