You are here:
Data Model and Calculated Fields for Agent Analytics
The data model for Agent Analytics is based on Session Tracing, which is a collection of DLOs (Data Lake Objects) and DMOs (Data Model Objects) that contain detailed session trace logs of agent behavior. The data model also includes references to every LLM call the reasoning engine makes to support joins with feedback data or guardrails metrics. Extended Service Data Model DMOs such as GenAiFeedback, GenAIContentCategory, and TenantEnrichedUsageEvent support feedback, Trust Layer, and flex credit analytics.
Analytics Data Model
Analytics Calculated Fields
The analytics semantic layer is the infrastructure that represents the link between the different entities of session tracing and their connection with the Analytics data entities. To view the model, in Data 360, go to the semantic model tab and open Agentforce Analytics Foundations. The Analytics Semantic Layer provides comprehensive calculated fields for querying session and agent performance data. For example, understand the relationship between session duration and quality ratings by combining `Session_Count`, and `Average_Session_Duration_clc` measures with the `Quality_Score_clc` dimension, or track weekly or monthly performance trends by combining the `Unique_Sessions_clc`, and `Abandonment_Rate_clc` measures with `Session_Date dimension`.
Measures and Dimensions
Measures are calculated numerical values that provide quantitative insights into agent performance, including engagement rates, deflection rates, escalation rates, abandonment rates, timing metrics like session duration and response latency, and aggregate counts of interactions, sessions, and users. Dimensions are categorical fields used to group, filter, and segment this analytical data, providing status indicators and classifications such as abandonment status, engagement status, entity types (user vs. agent), and session states that enable analysts to slice and dice the quantitative measures across different categories for deeper performance analysis and targeted reporting.
Analytics also extends with intent-specific insights from Agent Optimization. These insights include intent-level metrics, such as their duration and quality scores that measure the relevance of agent responses. Tags generated by the LLM help cluster and categorize these intents for deeper analysis of user engagement patterns.
| Label | Field Name | Description |
|---|---|---|
| Abandonment Rate | Abandonment_Rate_clc | Abandonment rate percentage (abandoned sessions ÷ all sessions) |
| Abandoned Sessions | Abandoned_Sessions_clc | Number of sessions where users left due to error, browser crash, or timeout |
| Agent Messages | Agent_Messages_clc | The total number of messages sent by the agent |
| Agent Triggered Actions | Agent_Triggered_Actions_clc | The total number of agent-triggered actions across all sessions |
| Agent to User Message Ratio | Agent_User_Message_Ratio_clc | The ratio of agent messages to user messages across all sessions |
| Average Agent Interaction Latency | Average_Agent_Interaction_Latency_clc | Average agent response time in milliseconds |
| Average Answer Faithfulness Score | Average_Answer_Faithfulness_Score_clc | Average score (0–1) measuring how closely the agent's response adheres to grounded source data (such as knowledge base articles). Note To use this metric, in Setup, toggle on Audit and Feedback and Knowledge/RAG Quality Data and Metrics. |
| Average Answer Relevance Score | Average_Answer_Relevance_Score_clc | Average score (0–1) measuring the relevance of the agent's response to the user's request. Note To use this metric, in Setup, toggle on Audit and Feedback and Knowledge/RAG Quality Data and Metrics. |
| Average Context Relevance Score | Average_Context_Relevance_Score_clc | Average score (0–1) measuring whether the agent retrieved the correct data source to answer the user's question. Note To use this metric, in Setup, toggle on Audit and Feedback and Knowledge/RAG Quality Data and Metrics. |
| Average Interactions Per Session | Average_Interactions_Per_Session_clc | Average number of interactions per session |
| Average Moment Duration | Average_Moment_Duration_clc | Average duration of an intent in seconds |
| Average Quality Score | Average_Quality_Score_clc | Average relevance score (1-5) of agent responses across sessions |
| Average Session Duration | Average_Session_Duration_clc | Average session duration in seconds |
| Average User Interactions | Average_User_Interactions_clc | Average number of user interactions across all sessions |
| Deflected Sessions | Deflected_Sessions_clc | Sessions ended by user (not by escalation or abandonment) |
| Deflection Rate | Deflection_Rate_clc | Deflection rate percentage (deflected sessions ÷ all sessions) |
| Engaged Sessions | Engaged_Sessions_clc | Sessions where user received reply based on agent-triggered action |
| Engagement Rate | Engagement_Rate_clc | Engagement rate percentage (engaged sessions ÷ all sessions) |
| Interaction Error Rate | Error_Rate_clc | The interaction error rate across all sessions. Errors are only recorded for interactions that contain at least one action or LLM step. |
| Escalated Sessions | Escalated_Sessions_clc | Number of sessions escalated to human or different agent |
| Escalation Rate | Escalation_Rate_clc | Escalation rate percentage (escalated sessions ÷ all sessions) |
| Interruption Count | Interruption_Count_clc | Number of voice interactions interrupted by the user |
| Interruption Rate | Interruption_Rate_clc | Percentage of voice interactions interrupted by the user relative to total session interactions |
| Quality Score Reasoning | Quality_Score_Reasoning_clc | Explanation for assigned quality score |
| Stickiness Rate | Stickiness_Rate_clc | Ratio of daily active users to monthly active users; the percentage of monthly users who are also active daily |
| Success Rate | Success_Rate_clc | The percentage of agent interactions that included action steps and completed without errors |
| Unique Interactions | Unique_Interactions_clc | Number of distinct user and agent interactions recorded |
| Unique Moments | Unique_Moments_clc | Number of distinct intents recorded within defined time frame |
| Unique Sessions | Unique_Sessions_clc | Number of distinct sessions recorded within a time frame |
| Unique Tags | Unique_Tags_clc | Number of unique tags created within defined time frame |
| Unique Users | Unique_Users_clc | The number of unique users interacting with the agent. For Service Agents, this includes messaging end users; for other agent types, this counts users by session participant role. |
| User Messages | User_Messages_clc | The total number of messages sent by the user |
| Adherence Response Rate | Adherence_Response_Rate_clc | Percentage of agent responses for which instruction adherence meets the defined threshold (high adherence), derived from Trust Layer instruction adherence evaluation |
| Average Agent Toxicity Score | Average_Agent_Toxicity_Score_clc | Average toxicity detector score (0–1) for agent output, aggregated from Trust Layer category scores. Note To use this metric, in Setup, toggle on Audit and Feedback and related Trust Layer data. |
| Average User Prompt Injection | Average_User_Prompt_Injection_clc | Average likelihood of prompt injection detected in user prompts (prompt defense), derived from Trust Layer evaluation. Note To use this metric, in Setup, toggle on Audit and Feedback and related Trust Layer data. |
| Negative User Feedback | Negative_User_Feedback_clc | Count of negative user feedback events on agent responses (for example, thumbs down), from Gen AI feedback data joined to session trace |
| Positive User Feedback | Positive_User_Feedback_clc | Count of positive user feedback events on agent responses (for example, thumbs up), from Gen AI feedback data joined to session trace |
| Task Resolution Rate | Task_Resolution_Rate_clc | Percentage of sessions or interactions evaluated as fully resolved by the Task Resolution detector (Trust Layer). Note Task Resolution evaluation is available as a beta detector; see Trust Layer documentation for availability. |
| Total Flex Credits | Total_Flex_Credits_clc | Sum of flex credits attributed to agent or generative AI usage, typically sourced from enriched usage events |
| Label | Field Name | Description |
|---|---|---|
| Abandonment Status | Abandonment_Status_clc | Indicates whether user left the session |
| Agent Adherence Status | Agent_Adherence_Status_clc | Instruction adherence level for the response (for example, high, low, uncertain), from Trust Layer InstructionAdherence evaluation on GenAIContentCategory |
| Agent Interaction Latency | Agent_Interaction_Latency_clc | Time for agent to respond to user request (milliseconds) |
| Deflection Status | Deflection_Status_clc | Indicates whether session ended at user's request |
| Engagement Status | Engagement_Status_clc | Indicates if user received reply based on agent action |
| Escalation Status | Escalation_Status_clc | Specifies if escalation moved session to different agent |
| Is Session Ended | Is_Session_Ended_clc | Indicates whether session has ended |
| Is Interaction With Errors | Is_Interaction_With_Errors_clc | Identifies interactions that encountered errors. Errors are only recorded for interactions that contain at least one action or LLM step. |
| Is User | Is_User_clc | Indicates whether entity is an agent or user |
| Moment Duration | Moment_Duration_clc | Duration of the intent in seconds |
| Quality Score | Quality_Score_clc | Relevance score (1-5) of agent response to user request |
| Session Ambiguous | Session_Ambiguous_clc | Indicates whether the session could not be classified clearly as deflected, escalated, abandoned, or cleanly ended |
| Session Duration | Session_Duration_clc | Session duration in seconds |
Calculated Field Formulas
The following formulas define how key calculated fields are computed from the underlying data model.
| Label | Field Name | Formula |
|---|---|---|
| Abandonment Rate | Abandonment_Rate_clc | |
| Abandoned Sessions | Abandoned_Sessions_clc | |
| Agent Messages | Agent_Messages_clc | |
| Agent Triggered Actions | Agent_Triggered_Actions_clc | |
| Agent to User Message Ratio | Agent_User_Message_Ratio_clc | |
| Average Agent Interaction Latency | Average_Agent_Interaction_Latency_clc | |
| Average Answer Faithfulness Score | Average_Answer_Faithfulness_Score_clc | |
| Average Answer Relevance Score | Average_Answer_Relevance_Score_clc | |
| Average Context Relevance Score | Average_Context_Relevance_Score_clc | |
| Average Interactions Per Session | Average_Interactions_Per_Session_clc | |
| Average Moment Duration | Average_Moment_Duration_clc | |
| Average Quality Score | Average_Quality_Score_clc | |
| Average Session Duration | Average_Session_Duration_clc | |
| Average User Interactions | Average_User_Interactions_clc | |
| Deflected Sessions | Deflected_Sessions_clc | |
| Deflection Rate | Deflection_Rate_clc | |
| Engaged Sessions | Engaged_Sessions_clc | |
| Engagement Rate | Engagement_Rate_clc | |
| Interaction Error Rate | Error_Rate_clc | |
| Escalated Sessions | Escalated_Sessions_clc | |
| Escalation Rate | Escalation_Rate_clc | |
| Interruption Count | Interruption_Count_clc | |
| Interruption Rate | Interruption_Rate_clc | |
| Success Rate | Success_Rate_clc | |
| Stickiness Rate | Stickiness_Rate_clc | |
| Unique Interactions | Unique_Interactions_clc | |
| Unique Moments | Unique_Moments_clc | |
| Unique Sessions | Unique_Sessions_clc | |
| Unique Tags | Unique_Tags_clc | |
| Unique Users | Unique_Users_clc | |
| User Messages | User_Messages_clc | |
| Label | Field Name | Formula |
|---|---|---|
| Abandonment Status | Abandonment_Status_clc | |
| Agent Interaction Latency | Agent_Interaction_Latency_clc | |
| Deflection Status | Deflection_Status_clc | |
| Engagement Status | Engagement_Status_clc | |
| Escalation Status | Escalation_Status_clc | |
| Is Interaction With Errors | Is_Interaction_With_Errors_clc | |
| Is Session Ended | Is_Session_Ended_clc | |
| Is User | Is_User_clc | |
| Moment Duration | Moment_Duration_clc | |
| Quality Score | Quality_Score_clc | |
| Session Duration | Session_Duration_clc | |

