Agent Skill & Profile Mapping Extract
Updated
Agent Skill Extract provide detailed information about the agent unique details and agent skills configured within the platform and how these skills are assigned to agents, teams, queues, and routing workflows. These datasets help supervisors, administrators, and workforce managers understand team capabilities, such as which agents possess specific skills, their proficiency levels, and how skills impact routing decisions. This visibility supports better staffing, more accurate routing, identification of skill gaps, and improved training and upskilling efforts.
Purpose
Understand details of agent profile mapping and skills distributed across teams.
Identify skill gaps that may affect service levels or routing accuracy.
Support workforce planning and resource allocation based on skill availability.
Assist training and upskilling initiatives by revealing proficiency gaps.
Extract Configuration and Availability
The extract configuration and availability details are listed below:
Extract Attribute | Details |
Channel Split | Not channel-specific; platform-level agent profile and skill level data |
Agent Split | Agent ID provides the list of all agents in the system |
Granularity | Agent Level Information about their profile and skills assigned |
Date Filter | Extract depicts data based on login activity of the agent - aggregated at lifetime |
Custom Field Behavior | Custom Fields by default are not added in this extract but feasibility of custom field exists in the particular extract based on below:
Default Behavior: User Custom Field: Current Value |
Data Schema
The schema details are listed below:
Metrics / Dimension | Definition | Unique Key | Data Type | Is Null |
Date | Date on which the event occured. | Timestamp | N | |
Agent | The sprinklr user for whom the report is being generated. | Varchar | N | |
Agent ID | The sprinklr user ID for whom the report is being generated. | Y | Number | N |
Agent Email ID | Email ID of the user. | Y | Varchar | N |
Agent Federation ID | Federation ID of the user for whom report is been generated. | Y | Varchar | "-" if Null |
Agent Manager | Agent Manager Assigned to the user. | Y | Varchar | "N/A" if Null |
Agent Skills(Comma Separated) | Agent Skills assigned to the agent, if multiple skills are assigned, it will come comma seperated. | Array | N | |
Agent Skills VS Proficiciency(Comma Separated) | Agent Skills assigned to the agent, if multiple skills are assigned, it will come comma seperated. | Array | N | |
Agent Count | Number of agents that has been in a particular status in the selected time range. Note: This metric shouldn't be used to get hourly trend of available or logged in agent, as it works on Status Assign Time (Default), which means if user doesn't change status from 10am - 2PM, then in hourly trend we will only get one count against 10 am interval, since status was assigned in that interval. | Number | N |
Data Settings
Reporting Preferences allow users to customize the default formats for specific metric types. These preferences are applied at the user level. If no changes are made, the system will continue to honor the following defaults:
Default Timestamp Format: MM DD, YYYY, HH:MM AM/PM - Eg: Jan 15, 2026, 12:36 AM
Default Time Duration Format: HH (h) MM (min) SS (s) - Eg: 3h 02m 35s
For more details, refer to this article.
When Custom Fields are added in an Extract, they must be treated as Unique Key during calculations to ensure accuracy and consistency.
Note:
The data is aggregated at a lifetime filter to indicate valid details of all the agent registered in the system (logged in even once)
Each row represents a unique Agent ID with profile details.
Logout Cause identifies the reason for session termination (e.g., user logout, forced logout, session expiry).
The Agent ID field can be mapped with other agent-performance extracts to understand efficiency and performance(e.g., Agent Performance or Agent Login Logout) for enriched reporting.