Modernizing customer support operations with HCLTech and AWS

5 min 所要時間

A leading US-based nonprofit consumer advocacy organization serving millions of consumers through product testing, research, ratings and consumer protection services sought to modernize its customer support operations

The Challenge

The existing support model relied heavily on agents manually searching extensive knowledge repositories to answer customer questions, creating inefficiencies across customer service operations.

As inquiry volumes continued to grow, agents spent significant time locating relevant information before responding to customers. This increased Average Handle Time (AHT), reduced agent productivity and created inconsistencies in customer responses. The organization required a scalable solution that could provide intelligent self-service capabilities while simultaneously empowering agents with AI-driven knowledge recommendations.

Agents manually searched large knowledge repositories to answer customer inquiries
High dependency on agent-assisted interactions increased operational costs
Manual information retrieval processes impacted customer response times
Existing support model lacked intelligent self-service capabilities
Inconsistent responses could occur due to varying agent knowledge and experience levels
Growing customer demand created scalability challenges for support operations
Limited automation increased agent effort and reduced overall operational efficiency

Failure to modernize would have resulted in continued dependence on manual knowledge searches, longer Average Handle Times, increased call volumes requiring agent intervention, higher operational costs, reduced productivity and limitations in scaling customer support operations effectively

The Objective

The objective was to transform the customer support experience through AI-powered self-service and intelligent agent assistance while leveraging Amazon Connect as the cloud contact center platform.

Enable AI-powered self-service using the enterprise Knowledge Base
Provide customers with automated answers through IVR channels
Reduce agent effort through real-time Agent Assist capabilities
Improve customer response times and first-contact resolution
Reduce Average Handle Time (AHT)
Improve consistency and accuracy of customer responses
Increase operational efficiency and scalability
Establish a modern cloud native contact center platform supporting future AI-driven innovation

The Solution

HCLTech designed and implemented a cloud native Contact Center Transformation solution leveraging Amazon Connect, Amazon Q, enterprise Knowledge Base integrations and Agent Assist capabilities. The solution enabled customers to receive automated responses through intelligent self-service experiences while providing agents with contextual knowledge recommendations during live customer interactions.

The solution was further enhanced with a custom Contact Trace Record (CTR) analytics pipeline from Amazon Connect to Amazon S3, enabling structured post-call analytics using AWS Glue Data Catalog, Amazon Athena and Amazon QuickSight. In addition, SAML 2.0-based SSO integration with Azure Active Directory (Microsoft Entra ID) was implemented to support centralized authentication, enterprise identity governance and controlled access for agents and administrators.

Assessment

Conducted a comprehensive assessment of the existing customer support model, contact center workflows and knowledge management processes
Analyzed customer interaction patterns and frequently asked questions to identify self-service opportunities
Evaluated enterprise knowledge repositories and content readiness for AI-powered retrieval
Assessed agent workflows to identify opportunities for automation and productivity improvements
Defined a modernization roadmap focused on self-service adoption, agent enablement and operational efficiency

Build

Implemented Amazon Connect as the enterprise cloud contact center platform
Configured intelligent IVR experiences and customer contact flows
Integrated Amazon Connect with the organization's enterprise Knowledge Base to enable AI-powered self-service capabilities
Enabled customers to receive automated answers to common inquiries directly through IVR interactions
Implemented Amazon Q and Agent Assist capabilities to deliver real-time knowledge recommendations to agents during customer conversations
Leveraged AWS Lambda to orchestrate knowledge retrieval processes and backend API integrations
Implemented SAML 2.0-based Single Sign-On (SSO) integration between Amazon Connect and Azure Active Directory (Microsoft Entra ID) for secure user access
Aligned Amazon Connect access with enterprise identity controls, role-based permissions and centralized user lifecycle management
Configured dynamic content retrieval mechanisms to provide relevant and contextual responses
Implemented Amazon S3 for storage of customer interaction data, recordings, reporting datasets and operational information
Built a custom CTR pipeline to capture Amazon Connect Contact Trace Records in Amazon S3 for centralized analytics and governance
Cataloged CTR datasets using AWS Glue Data Catalog and queried interaction data through Amazon Athena for analytics, audit review and operational reporting
Enabled Amazon QuickSight dashboards for AWS-native visibility into interaction trends, self-service performance, Agent Assist outcomes and service-level metrics
Integrated Contact Lens for Amazon Connect to provide conversation analytics, agent performance insights and customer interaction intelligence
Developed operational dashboards and reporting capabilities to monitor customer interactions, self-service adoption, call volumes and agent productivity
Established analytics capabilities to continuously optimize self-service performance and knowledge recommendations

Operate

Established ongoing monitoring and management of the Amazon Connect environment and AI-powered support capabilities
Continuously monitored self-service adoption, call deflection rates and customer interaction trends
Utilized Contact Lens insights to improve customer service quality and agent performance
Reviewed AI-generated recommendations and knowledge retrieval performance to optimize accuracy and relevance
Maintained Knowledge Base content and continuously expanded content coverage based on customer interaction patterns
Leveraged operational dashboards to track contact center performance, service quality and productivity metrics
Used Athena-based CTR analytics to monitor call patterns, self-service adoption, routing outcomes, queue behavior and operational KPIs
Maintained SSO governance through Azure AD identity policies, access reviews and controlled provisioning for Amazon Connect users
Supported continuous improvement initiatives focused on enhancing customer experience and operational efficiency

The Impact

The Amazon Connect implementation enabled the organization to transform its support operations through AI-powered self-service and intelligent agent assistance. Customers gained faster access to information while agents benefited from contextual knowledge recommendations, resulting in improved service quality, reduced operational effort and greater efficiency.

Reduced Average Handle Time (AHT) through intelligent self-service and automated knowledge retrieval
Improved customer response times by providing immediate answers to common inquiries
Reduced agent effort by eliminating manual searches through extensive knowledge repositories
Increased consistency and accuracy of customer responses
Improved agent productivity through AI-powered Agent Assist recommendations
Increased self-service adoption and reduced dependency on agent-assisted interactions
Established a scalable cloud native contact center platform capable of supporting future growth
Enhanced visibility into customer interactions through advanced analytics and reporting
Improved data-driven decision-making through a custom CTR analytics pipeline using Amazon S3, AWS Glue Data Catalog, Amazon Athena and Amazon QuickSight
Strengthened access security and operational control through Azure AD-integrated SSO for Amazon Connect
Improved operational efficiency and support scalability