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Bot performance metrics for indept insights on Flows

The Bot Performance Metrics dashboard provides detailed insights into the effectiveness and usage of your bot. To access this dashboard, navigate to Dashboard > Bot Performance Metrics. All data in this dashboard can be filtered for specific dates or time ranges to provide tailored analytics.

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This guide explains the various metrics available in the dashboard, how to interpret them, and when to use them to optimize your bot's performance.

Bot performance metrics KPIs​

Following are the Bot Performance Metrics Key performance indicators(KPIs):

1. Flow Visits​

Tracks the number of times users enter a specific flow within the bot. This metric helps measure the popularity and usage of different bot flows.

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Data Details:

  • Data Source: Number of visits completed through flows.
  • Table: User Engagement Events.
  • Filter: Event is "journey-completed."
  • Summarize By: Sum of count.
  • Group By: Journey.

When to Use:

  • To understand which flows are most frequently accessed.
  • To identify less-used flows that may require improvements or better promotion.

2. Bot Accuracy​

Measures the bot's ability to accurately understand and respond to user queries. High accuracy indicates effective natural language processing (NLP) and a well-trained bot.

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Data Details:

  • Data Source: Accuracy of bot identification in messages.
  • Table: Message Events.
  • Filter: IDENTIFICATIONSTATUS not empty.
  • Summarize By: Count.
  • Group By: IdentificationStatus.
  • Visualization: Pivot.
  • Custom Formula: Identified / (Identified + Unidentified).

When to Use:

  • To evaluate the quality of the bot's NLP.
  • To identify areas where training data or intents need refinement.

3. Bot Feedback​

Collects user feedback on their interactions with the bot, providing insights into user satisfaction and areas for improvement.

Data Details:

  • Data Source: Feedback provided for bot performance.
  • Table: User Feedback Table.
  • Summarize By: Average on rating.

When to Use:

  • To gauge user satisfaction and identify trends in user sentiment.
  • To prioritize improvements based on feedback ratings.

4. Flow Completion Rate​

Calculates the percentage of users who successfully complete a flow from start to finish. Indicates how effectively the bot guides users through processes.

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Data Details:

  • Data Source: Completion rate of initiated journeys.
  • Table: User Engagement Events.
  • Filter: Event is "journey-started" and "journey-completed."
  • Summarize By: Sum of count.
  • Group By: Event.
  • Visualization: Pivot.
  • Custom Formula: (journey-completed / journey-started) * 100.

When to Use:

  • To assess the usability and clarity of specific flows.
  • To identify points where users abandon flows and improve them.

Flow Completion Rate for Each flow​

This displays the flow completion rate for each flow.

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5. Deflection Rate​

Measures the percentage of user inquiries resolved by the bot without escalation to a human agent. A higher deflection rate indicates effective issue resolution by the bot.

Data Details:

  • Data Source: Deflection rate in user-agent sessions.
  • Table: User Engagement Events.
  • Filter: Event is "user-session" and "agent-session."
  • Summarize By: Count.
  • Group By: Event.
  • Visualization: Pivot.
  • Custom Formula: (User-Agent / User) * 100.

When to Use:

  • To monitor the bot's success in reducing workload for human agents.
  • To identify areas where bot responses can be improved for higher deflection.

6. Utterance Status Split​

Categorizes user utterances based on their status (e.g., recognized, unrecognized, ambiguous). Helps in understanding how well the bot processes user inputs.

Data Details:

  • Data Source: Number of messages with an "unidentified" status.
  • Table: Message Events.
  • Filter: IdentificationStatus is "unidentified."

When to Use:

  • To identify intents that are not recognized or are ambiguous.
  • To refine training data and improve recognition rates.

7. API Usage by Status Code​

Tracks the status codes returned by API requests made by the bot. Provides insights into the performance and reliability of APIs.

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Data Details:

  • Data Source: Usage of API services categorized by status.
  • Table: API Events.
  • Filter: API name.
  • Summarize By: Sum of count.
  • Group By: Status code.

When to Use:

  • To monitor API reliability and identify potential issues with integrations.
  • To troubleshoot failed API requests based on status codes.

8. API Requests by Day​

Displays the number of API requests made by the bot daily. Useful for tracking bot activity levels and identifying trends or spikes in API usage.

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Data Details:

  • Data Source: Usage of API services categorized by status.
  • Table: API Events.
  • Filter: API name.
  • Summarize By: Sum of count.
  • Group By: Day.

When to Use:

  • To track daily API activity and identify usage patterns.
  • To ensure API request volumes align with expected bot activity.