Best practices for building a Customer Effort Score (CES) system with Amazon Connect Customer

This article provides best practices for building a Customer Effort Score (CES) system with Amazon Connect to measure and predict customer loyalty by capturing explicit surveys and detecting implicit effort signals from contact data.

• Capture explicit effort scores using post-contact surveys with a 1-7 scale question in disconnect flows, Tasks, or post-chat surveys
• Detect implicit effort signals from Contact Trace Records using Amazon Athena with weighted scoring based on transfers, repeat contacts, holds, and agent connection attempts
• Operationalize CES through effort-aware routing using Lambda and DynamoDB to prioritize high-effort customers to experienced agents
• Configure sentiment-based alerting with Amazon Connect analytics to flag negative interactions for real-time supervisor intervention
• Implement proactive outreach by triggering follow-up tasks for contacts exceeding effort thresholds within 24 hours
• Conduct quarterly process reviews to identify and prioritize the three highest-effort customer journeys for improvement

CES provides stronger churn prediction than CSAT by measuring interaction difficulty, enabling organizations to anticipate customer disloyalty and take preventive action.