Usage Analytics

Provides backend monitoring data content to understand user information.

How to View

Enter "Usage Analytics" under "AI Assistant" in the left function bar to see the dashboard of AI assistant conversation processing.

• Word Count

• Conversation Count

• Message Count

• Average Messages per Conversation

• User Satisfaction Rate

• Time Filter (by date, month, day, hour)

Through these metrics, you can understand the usage of AI assistant from multiple angles.

Detailed Statistics Explanation

1. Words Count

Calculation Method:

• Text Word Count: Calculates the number of characters in message content

• Image Cost: Calculated based on the set word cost per image

• Total Word Count = Message content word count + (Number of images × Image word cost)

Statistical Range: Includes user input messages and AI assistant reply messages, supports daily and monthly time granularity statistics

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2. Conversations Count

Calculation Method:

• Counter +1 when a new conversation is created

• Conversation statistics update is triggered when the first message in a conversation is created

Update Timing: When user starts a new conversation (first message)

Statistical Range: Supports hourly, daily, and monthly time granularity statistics

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3. Messages Count

Calculation Method:

• Counter +1 when a new message is created

• Includes both user input messages and AI assistant reply messages

Update Timing: Statistics update is triggered with each message creation

Statistical Range: Supports hourly, daily, and monthly time granularity statistics

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4. Average Messages per Conversation

Calculation Formula:

Average Messages per Conversation = Message Count ÷ Conversation Count (displays 0 if conversation count is 0)

Meaning:

• Shows average number of messages per conversation

• Reflects depth of interaction between users and AI assistant

• Higher values indicate deeper conversations and more frequent interactions

Statistical Range: Supports hourly, daily, and monthly time granularity statistics

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5. User Satisfaction Rate

Calculation Formula:

User Satisfaction Rate = Likes ÷ Total Feedback (displays 0 if total feedback is 0)
Total Feedback = Likes + Dislikes

Meaning:

• Represents proportion of positive feedback (like rate)

• Value range: 0% ~ 100%

• Higher values indicate greater user satisfaction with AI assistant responses

Feedback Mechanism:

• Users can give "like" or "dislike" to AI assistant replies

• Supports real-time statistics updates

Update Timing: When user provides feedback (create, update, delete)

Statistical Range: Supports hourly, daily, and monthly time granularity statistics

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Statistics Update Mechanism

Real-time Updates: Statistics are immediately updated when relevant events occur (new messages, new conversations, feedback changes)

Time Granularity Support:

• Hourly: Suitable for real-time monitoring

• Daily: Suitable for daily report analysis

• Monthly: Suitable for monthly reports and trend analysis

Application Scenario: Usage Effectiveness Evaluation

Observe trends in "User Satisfaction Rate" and interaction frequency to evaluate whether AI assistant response quality meets expectations, serving as a basis for optimization.