Transforming customer support while reducing costs using AWS with ResultsCX

Since 1990, ResultsCX has helped clients across a wide range of industries to provide exceptional customer experiences through innovative, custom-built solutions. Its track record of driving efficiency while improving the customer experience made ResultsCX the ideal partner for the MVNO as its call volumes increased tremendously after the Affordable Connectivity Program ended.

Before working with ResultsCX, the MVNO had a customer support model that depended on human agents to manage customer inquiries. Over time, it became clear that the company needed a new approach to reduce wait times, decrease operational costs, and improve customer satisfaction.

ResultsCX and its client worked closely together to define the goals for the project. These included drastically reducing response times, offering more personalized customer interactions, boosting operational efficiency without expanding the company’s workforce, and implementing a cost-effective solution that was capable of handling fluctuating inquiry volumes.

ResultsCX worked with the MVNO to develop a state-of-the-art, AI-powered self-service solution built on QnABot on AWS, a versatile AWS Solution that helps organizations improve their customer service. At the heart of the ResultsCX solution is an advanced interactive voice response that serves as the initial point of contact. From there, the solution guides callers to the self-service channels that match their needs. At the same time, an AI-driven chatbot connects to the company’s backend systems through robust APIs, offering near real-time information on account balances, application progress, and device replacement procedures.

QnABot allowed ResultsCX to seamlessly integrate several AWS services and products into the use case. Amazon Lex powers the natural language understanding capabilities, while Amazon Kendra provides intelligent search functionality across the client’s knowledge base. The solution stores question-and-answer pairs in Amazon DynamoDB and uses Amazon OpenSearch Service to enable semantic search capabilities. Amazon Lambda functions handle the business logic and API integrations with the MVNO backend systems, while Amazon CloudFront ensures low-latency content delivery across different geographical regions.

QnABot relies on Amazon Simple Storage Service (Amazon S3) for content management and Amazon EventBridge to coordinate various system components. Additionally, AWS Identity and Access Management (IAM) provides fine-grained access control and security, while Amazon CloudWatch enables comprehensive monitoring and logging of the entire system. This architecture ensures high availability and scalability while maintaining strict security standards required in the telecommunications industry.

Underpinning these customer-facing interfaces is SupportPredict, a ResultsCX suite of AI-powered CX solutions designed to simplify access to knowledge, reduce handling time, and elevate every customer interaction. It is anchored by an AI-powered knowledge base serving as a comprehensive information repository. This system not only supports the chatbot but also provides human agents with quick access to accurate, up-to-date information. The seamless integration through sophisticated API connections makes it possible for the ResultsCX solution to deliver highly personalized, near real-time responses to diverse customer inquiries.

This implementation created an intuitive and frictionless customer journey, in which callers get clear self-service options as soon as they’re connected. What’s more, by automating routine inquiries, the ResultsCX solution freed the company’s human agents to focus on complex, high-value interactions, leading to marked improvements in both operational efficiency and staff satisfaction. This reallocation of resources enhanced the service quality for complex customer issues while optimizing the workforce.

The success of this collaboration underscores how AI-powered self-service solutions can transform the telecommunications industry. By strategically implementing AI, ResultsCX helped the MVNO achieve significant cost savings while enhancing the customer experience, positioning the MVNO for sustained growth in an increasingly competitive market.

ResultsCX deployed the solution and yielded impressive results across key performance metrics. The MVNO achieved a 20 percent reduction in annual operational expenses, with the cost dropping to 0.31 cents per self-service interaction. The system demonstrated a 45 percent containment rate, indicating nearly half of all customer contacts were resolved through self-service channels without escalation to human agents. 
 
The solution also increased time and cost efficiencies. With an average handling time of just 79.7 seconds, the MVNO dramatically improved its issue resolution speed. Over six months, the company saw a 37 percent reduction in overall call volume, demonstrating how effective the self-service tool is with reducing the need for live agent support. “QnABot on AWS has empowered our SupportPredict platform to deliver fast, intuitive self-service experiences that reduce support costs and boost customer satisfaction,” says Ganesh Iyer, chief solutions officer at ResultsCX. “Its seamless integration with the broader AWS ecosystem positions us to scale effortlessly and innovate continuously as customer needs evolve.”

Looking ahead, ResultsCX will assist the MVNO in continuous refinement through regular updates and monitoring of customer feedback to improve user satisfaction. The companies plan to expand the solution’s self-service capabilities, including the integration of more advanced generative AI technologies for enhanced personalization and context-aware support. They will also expand the self-service options across additional customer touchpoints, such as mobile applications and social media platforms.

By embracing innovation and prioritizing customer needs, ResultsCX has established a new benchmark for efficient, effective customer service. As the telecommunications industry continues to evolve, AI-driven solutions like this one will play an increasingly important role in shaping the future of customer experience.