Modern Customer Engagement with AWS

Improving customer experience with HCLTech and AWS

Modern customer engagement platform for US-based biopharma company.

5 min 所要時間

Overview

A leading US-based biopharmaceutical company specializing in therapies for neurological disorders and rare diseases required a modern, scalable and secure customer engagement platform to support patients, caregivers and healthcare professionals across multiple support channels.

The Challenge

As the organization's patient support services continued to expand, the existing operational model faced challenges in efficiently handling growing inquiry volumes while maintaining high-quality service experiences.

The organization sought to improve customer experience through intelligent self-service capabilities, automated workflows and enhanced agent productivity. At the same time, it needed to simplify support operations, reduce manual effort and establish a cloud-based platform capable of supporting future growth and evolving business requirements.

The existing support model relied heavily on agent-assisted interactions and manual workflows, resulting in increased operational effort and limitations in scalability. The organization required a solution that could automate routine inquiries while ensuring complex cases were routed efficiently to specialized support teams.

Increasing customer support demand placed pressure on existing service operations
Manual processes limited scalability and increased operational costs
Routine customer inquiries consumed significant agent capacity
Existing support model lacked intelligent self-service and automation capabilities
Longer customer wait times impacted service efficiency and customer experience
Agents spent valuable time handling repetitive interactions that could potentially be automated
Limited automation constrained the organization's ability to scale support operations efficiently
Need for a consistent and seamless experience across patients, caregivers and healthcare providers

Failure to address these challenges would have resulted in increasing operational costs, longer customer wait times, reduced service efficiency, higher agent workloads and difficulties maintaining a consistent customer experience as demand for support services continued to grow.

The Objective

The objective was to modernize customer engagement operations by implementing a cloud native contact center solution capable of automating routine interactions, increasing self-service adoption, improving service quality and enhancing agent productivity.

Modernize patient and healthcare provider support operations
Increase adoption of intelligent self-service capabilities
Automate routine customer inquiries and workflows
Improve service quality and customer experience
Enhance agent productivity and operational efficiency
Reduce customer wait times and improve response times
Simplify support operations across multiple customer groups
Establish a scalable customer engagement platform capable of supporting future growth
Improve visibility into operational performance through centralized reporting and analytics

The Solution

HCLTech designed and implemented a Contact Center Transformation solution leveraging Amazon Connect to provide intelligent self-service, workflow automation and scalable customer engagement capabilities. The solution streamlined patient, caregiver and healthcare provider interactions while enabling support teams to focus on more complex customer needs.

The cloud native architecture utilized Amazon Connect contact flows, automated workflows and backend integrations to improve operational efficiency while delivering a more personalized and seamless customer experience.

The solution was enhanced with a custom Contact Trace Record (CTR) analytics pipeline that moves data from Amazon Connect to Amazon S3 and Amazon Athena, enabling structured querying of contact events, call metadata, queue activity, routing details and operational KPIs. The platform also integrated Single Sign-On (SSO) with Azure Active Directory (Microsoft Entra ID) using SAML 2.0, supporting centralized authentication, enterprise identity governance and controlled access for agents and administrators.

Assessment

Conducted a comprehensive assessment of existing patient and provider support operations
Analyzed customer service workflows, inquiry volumes, escalation patterns and operational challenges
Identified opportunities for automation and self-service adoption
Evaluated customer interaction journeys across patients, caregivers and healthcare professionals
Assessed integration requirements, security considerations and scalability objectives
Developed a modernization roadmap aligned with the organization's customer experience strategy

Build

Implemented Amazon Connect as the enterprise cloud contact center platform
Designed and configured intelligent IVR experiences and customer contact flows
Enabled self-service capabilities to automate routine customer inquiries and requests
Implemented automated workflow processing using AWS Lambda
Integrated Amazon Connect with support systems and backend business applications
Implemented SAML 2.0-based SSO integration between Amazon Connect and Azure Active Directory (Microsoft Entra ID) for secure agent and administrator access
Aligned Amazon Connect access with enterprise identity controls, role-based access and centralized user lifecycle management
Configured intelligent routing capabilities to direct complex interactions to specialized support teams
Established omnichannel engagement capabilities supporting evolving customer communication requirements
Implemented call recording and operational data management using Amazon S3
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 operational reporting and audit analysis
Enabled Amazon QuickSight dashboards for AWS-native visibility into customer interactions, queue performance, routing behavior and service-level trends
Developed centralized reporting and analytics dashboards using Power BI
Created operational monitoring capabilities for customer interactions, service levels and agent performance
Established automation frameworks supporting future enhancement and expansion initiatives

Operate

Established ongoing operational management and monitoring of the Amazon Connect environment
Continuously monitored customer interaction volumes, service quality metrics and operational performance
Optimized customer journeys and IVR experiences based on customer behavior and service analytics
Monitored self-service adoption rates and customer resolution outcomes
Maintained workflow automation processes and backend integrations
Utilized Power BI dashboards to track operational performance, service efficiency and customer experience metrics
Used Athena-based CTR analytics to monitor interaction trends, routing outcomes, wait-time patterns, queue performance and operational KPIs
Maintained SSO governance through Azure AD identity policies, access controls and controlled provisioning for Amazon Connect users
Supported continuous improvement initiatives focused on increasing automation and enhancing customer satisfaction

The Impact

The Amazon Connect-powered transformation enabled the organization to modernize patient and provider support operations while improving customer experience, increasing automation and enhancing operational efficiency. Routine inquiries were successfully automated through self-service capabilities, allowing support teams to focus on more specialized and complex interactions.

Increased self-service adoption through intelligent IVR and automated customer journeys
Improved customer experience through faster and more efficient support interactions.
Reduced dependency on manual inquiry handling processes
Increased agent productivity by automating repetitive and routine customer requests.
Improved service quality and operational efficiency
Reduced customer wait times and improved responsiveness
Enabled scalable support operations capable of accommodating future growth
Enhanced visibility into operational performance through centralized reporting and analytics
Improved data-driven decision-making through a custom CTR analytics pipeline using Amazon S3, AWS Glue Data Catalog and Amazon Athena
Strengthened access security and operational control through Azure AD-integrated SSO for Amazon Connect
Simplified customer engagement operations across patients, caregivers and healthcare providers
Established a future-ready cloud-based customer engagement platform