Usage Analytics

Provides backend monitoring data to understand user information.

How to View

Go to "AI Assistant" in the left menu and select "Usage Analytics" to view the AI Assistant conversation dashboard.

• Word count

• Conversation count

• Message count

• Average messages per conversation

• User satisfaction

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

These metrics allow you to understand AI Assistant usage from multiple perspectives.

Detailed Metric Descriptions

1. Word Count (Words Count)

Calculation Method:

• Text word count: Counts the number of characters in message content

• Image cost: Each image is calculated based on the configured image word cost

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

Scope: Includes both user input messages and AI Assistant reply messages. Supports daily and monthly granularity.

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2. Conversation Count (Conversations Count)

Calculation Method:

• Each time a new conversation is created, the counter increments by 1

• When the first message in a conversation is created, it triggers a conversation statistics update

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

Scope: Supports hourly, daily, and monthly granularity.

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3. Message Count (Messages Count)

Calculation Method:

• Each time a new message is created, the counter increments by 1

• Includes both user input messages and AI Assistant reply messages

Update Trigger: Each message creation triggers a statistics update

Scope: Supports hourly, daily, and monthly granularity.

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4. Average Messages per Conversation (Average Messages per Conversation)

Formula:

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

Description:

• Represents the average number of messages per conversation

• Reflects the depth of interaction between users and the AI Assistant

• Higher values indicate deeper and more frequent interactions

Scope: Supports hourly, daily, and monthly granularity.

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5. User Satisfaction (User Satisfaction Rate)

Formula:

User satisfaction = Likes ÷ Total feedback (displays 0 if total feedback is 0)
Total feedback = Likes + Dislikes

Description:

• Represents the percentage of positive feedback (like rate)

• Value range: 0% to 100%

• Higher values indicate greater user satisfaction with AI Assistant responses

Feedback Mechanism:

• Users can give a "like" or "dislike" to AI Assistant responses

• Statistics are updated in real time

Update Trigger: When users provide feedback (create, update, or delete)

Scope: Supports hourly, daily, and monthly granularity.

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Statistics Update Mechanism

Real-time updates: Statistics are immediately updated when relevant events occur (new message, new conversation, feedback change)

Time granularity support:

• Hourly: Suitable for real-time monitoring

• Daily: Suitable for daily report analysis

• Monthly: Suitable for monthly reports and trend analysis

Use Case: Effectiveness Assessment

Observe trends in "User Satisfaction" and interaction counts to evaluate whether the AI Assistant's response quality meets expectations, serving as a basis for optimization.