Banking — Automated Agent Performance KPI Reporting Pipeline

Free

This DAG automates the collection and reporting of agent performance KPIs. It integrates customer satisfaction, response times, and cost data to enhance operational insights.

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Overview

The purpose of this DAG is to streamline the reporting process for agent performance KPIs within the banking sector. It collects data from various sources, including customer satisfaction surveys, response time logs, and operational cost records. The ingestion pipeline initiates with data extraction from these sources, followed by data cleansing and transformation to ensure accuracy and consistency. The processing logic includes calculating key performance indicators such as average response tim

The purpose of this DAG is to streamline the reporting process for agent performance KPIs within the banking sector. It collects data from various sources, including customer satisfaction surveys, response time logs, and operational cost records. The ingestion pipeline initiates with data extraction from these sources, followed by data cleansing and transformation to ensure accuracy and consistency. The processing logic includes calculating key performance indicators such as average response time, customer satisfaction scores, and total operational costs. Quality controls are implemented to verify the precision of the data before generating reports. The outputs are comprehensive KPI reports, which are stored in a centralized dashboard for easy access and analysis by management. Monitoring KPIs, such as report generation time and data accuracy, are tracked to ensure the reliability of the reporting process. The business value of this DAG lies in its ability to provide actionable insights that drive performance improvements and enhance customer service efficiency.

Part of the AI Assistants & Contact Center solution for the Banking industry.

Use cases

  • Improved decision-making through timely performance insights
  • Enhanced customer satisfaction by identifying service gaps
  • Reduced manual reporting efforts and associated costs
  • Increased operational efficiency through data-driven strategies
  • Strengthened compliance with performance monitoring requirements

Technical Specifications

Inputs

  • Customer satisfaction survey results
  • Agent response time logs
  • Operational cost records
  • Call center transaction data
  • Agent performance metrics

Outputs

  • Comprehensive KPI performance reports
  • Dashboard visualizations of agent metrics
  • Historical performance trend analysis
  • Alerts for performance anomalies
  • Monthly performance summary reports

Processing Steps

  1. 1. Extract data from customer satisfaction surveys
  2. 2. Collect agent response time logs
  3. 3. Aggregate operational cost records
  4. 4. Perform data cleansing and validation
  5. 5. Calculate key performance indicators
  6. 6. Generate automated KPI reports
  7. 7. Store reports in centralized dashboard

Additional Information

DAG ID

WK-0095

Last Updated

2025-09-11

Downloads

85

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