New featureMedium

Amazon Connect Customer now automatically finds example agent evaluations for tailored coaching

Amazon Connect Customer now automatically surfaces relevant examples of agent evaluations when managers prepare coaching feedback, enabling actionable, evidence-backed coaching. This saves time previously spent manually searching for examples.

Amazon Connect Customer now automatically surfaces relevant examples of an agent's evaluations when managers prepare coaching feedback. Managers receive examples of recent evaluations where the agent scored high or low on the chosen coaching topic, along with human or AI evaluator notes explaining the agent behaviors that drove the result. For example, while preparing feedback for an agent on 'de-escalation,' a manager receives example calls where the agent successfully calmed a frustrated customer, alongside calls that were escalated, with insights into the agent behaviors that led to each outcome. This enables managers to deliver tailored coaching that accelerates agent performance improvement while saving time previously spent manually searching for examples. This feature is available in all regions where Amazon Connect Customer is offered.

Read the original AWS announcement

Related articles and terms

Building a Cloud Contact Center with Amazon Connect - The Decisive Difference from Legacy PBXCompare Amazon Connect's architecture with traditional on-premises PBX systems, and learn practical approaches to contact flow design, real-time analytics, CRM integration, and the pay-per-use pricing model.Amazon ConnectA cloud-based contact center service that enables building customer interaction infrastructure without physical telephony equipment, using contact flow design and pay-per-use pricingKiro Agent Hooks in Practice - Boosting Development Quality with Automated Processing on File SaveIntegrate linting, testing, and formatting into your AI agent workflow with hooks that auto-trigger on file save or command execution. This article explains hook definition structure and practical usage patterns.90% of AWS Is Born from Customer Feedback - Working Backwards and Customer-Driven InnovationWe explain how the Working Backwards process and the Customer Obsession principle shape AWS service development. Learn about the innovation mechanism that starts with PR/FAQ documents and the process for incorporating customer feedback.Generative AI Platform - Building an Enterprise AI Foundation with Amazon BedrockLearn how to build generative AI applications using Amazon Bedrock. This guide covers foundation model selection, RAG pattern implementation, safety guardrails, and SageMaker integration for designing enterprise-grade AI infrastructure.