Amazon Connect Puts Generative AI to Work Improving End to End Customer Experiences

New capabilities include proactive, personalized customer outreach, improved self-service, generative AI safeguards, and manager tools for agent coaching

LAS VEGAS--(BUSINESS WIRE)-- At AWS re:Invent, Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), today announced new generative AI enhancements for Amazon Connect, AWS's cloud contact center solution. These new features will further improve customer experiences by enabling more personalized, efficient, and proactive customer service. As a result, organizations can help significantly improve customer satisfaction through faster issue resolution and continuous contact center optimization, while simultaneously reducing operational costs.

Amazon Q in Connect for customer self-service (Graphic: Amazon)

• Amazon Connect now offers automated segmentation for proactive outreach, delivering personalized and timely interactions across communication channels for a single person or groups with similar characteristics.
• Amazon Q in Connect, a generative AI-powered assistant for customer service, now enables organizations to create relevant, automated, and dynamic self-service experiences.
• Amazon Q in Connect features new customizable AI guardrails with robust controls over AI-generated content, enabling organizations to confidently deploy generative AI in contact centers while adhering to their specific policies and safeguarding customer interactions.
• New AI-powered agent evaluations and intelligent contact categorization tools enable customer service managers to easily spot performance trends, enhance training, and help improve overall service quality.
• Tens of thousands of AWS customers use Amazon Connect to support more than 10 million contact center interactions every day. Frontdoor, Fujitsu, GoStudent, Priceline, Pronetx, and University of Auckland are among customers and partners using the new generative AI enhancements for Amazon Connect to deliver superior customer service at a lower cost.

"With Amazon Connect, in addition to evolving customer service, we're also fundamentally reimagining how organizations build, nurture, and sustain customer relationships," said Pasquale DeMaio, vice president and general manager of Amazon Connect at AWS. "By using generative AI to improve the customer experience, Amazon Connect is paving the way for a future where every customer interaction is an opportunity to delight and foster long-term loyalty. The continuous evolution of Amazon Q in Connect is giving organizations the power and flexibility needed to handle sophisticated customer service scenarios without requiring programming expertise."

Strengthen customer loyalty with more personalized experiences powered by generative AI

Organizations often struggle to deliver relevant customer experiences due to fragmented data across disparate systems, including separate databases for purchases, support tickets, and online interactions. This fragmentation prevents them from gaining a holistic view of their customers' journey, while also limiting their ability to launch specialized campaigns and initiate proactive outbound communications based on real-time customer events. As a result, organizations miss crucial opportunities to engage customers at just the right moments in their journey, whether through timely support, relevant offers, or proactive communication. This leads to diminished customer satisfaction and reduced loyalty, as organizations find themselves unable to meet the growing expectations of customers who anticipate seamless, relevant interactions.

Amazon Connect helps solve these problems by bridging data silos, creating a unified view of each customer that organizations can use for proactively addressing needs before issues arise and conducting outbound campaigns. Now, Amazon Connect's generative AI-powered segmentation capabilities can analyze data to provide smart recommendations on engaging different groups of customers based on both real-time and historical interactions, offering a comprehensive view of customer interactions and preferences. For example, an airline might use Amazon Connect to identify frequent flyers experiencing a significant delay, then automatically offer them priority rebooking options, lounge access, or personalized compensation based on their loyalty status and past travel patterns. Amazon Connect simplifies the process of defining meaningful customer segments and delivering relevant outbound campaigns by consolidating customer journey insights from various touchpoints. Campaign managers can then use simple, conversational commands to define segments based on this rich data. This approach enables organizations to craft precisely timed incoming and outgoing communications that respond to real-time interests and events, resulting in more personalized experiences that improve customer satisfaction and loyalty.

GoStudent, a leading tutorial and education technology provider, uses Amazon Connect to ensure customer call-backs are routed to the right sales representative based on previous contact history. By leveraging Amazon Connect's enhanced unified customer profiles and outbound campaign capabilities, GoStudent will expand its sales strategy to include proactive outreach alongside existing inbound operations. This combined approach is expected to increase sales representatives' daily contacts by 20% and accelerate lead-to-customer conversions.

Create generative AI-powered self-service experiences with Amazon Q in Connect

Consumers expect increasingly personalized, faster, and capable self-service support. Generative AI offers a promising solution to meet these expectations; however, integrating it into a contact center environment requires significant investment in multiple third-party services, infrastructure, and specialized talent. During implementation, organizations must develop custom safeguards to regulate AI-generated responses. Without proper controls, generative AI may provide inappropriate information to customers, surface information that does not resolve customer issues, or frustrate customers by asking them for the same information multiple times. Consequently, many organizations hesitate to fully embrace generative AI, missing out on potential improvements in customer experience and contact center efficiency gains.

Amazon Q in Connect now features generative AI-powered capabilities to enhance self-service customer service, offering customers the same personalized responses, proactive actions, and contextual understanding it provides to agents. Organizations can quickly create, test, and improve AI-powered self-service experiences across chat and voice channels that provide tailored responses and take proactive actions. For example, when a customer asks what rebooking options are available for their flight, Amazon Connect accesses and analyzes the customer's specific information before formulating a response. This includes checking the customer's airline status (e.g., frequent flyer level), reviewing the current ticket class, and examining eligibility based on the airline's policies. Amazon Connect then uses this data to provide a tailored response, offering rebooking options that align with the customer's status, preferences, and eligibility. If appropriate and within policy guidelines, it can proceed to book a new ticket. Amazon Connect also ensures smooth handoffs to a customer service agent, when needed, by automatically transferring the conversation, providing a comprehensive summary of the interaction, sharing all relevant customer data and context gathered, and enabling the agent to continue the conversation seamlessly without requiring the customer to repeat information.

To enhance the safety and reliability of generative AI deployments in contact centers, Amazon Q in Connect now includes customizable AI guardrails. These safeguards provide organizations with robust controls over AI-generated responses without the need for extensive prompt engineering. Organizations can block undesirable topics for self-service, filter harmful and inappropriate content based on their responsible AI policies, redact sensitive information to protect customer privacy, and verify model responses using contextual grounding checks. These safeguards can be selectively applied based on contact type, offering flexible control over AI interactions. By integrating these features into Amazon Q in Connect, Amazon reduces the complexity and cost associated with building custom generative AI virtual agents, while empowering organizations to confidently leverage AI in their contact centers in alignment with their unique requirements.

Frontdoor, a leading provider of home warranties and digital on-demand services, is piloting Amazon Q in Connect with the intent of reducing agent training and on-boarding time. This pilot is already reducing an agent's path to proficiency by delivering agents' next best responses and actions, based on policy documents stored in Amazon S3 within the Amazon Connect agent workspace. As they learn from how agents use this technology, Frontdoor expects to expand this same support to consumer-facing, self-service interactions.

Pronetx, a professional services partner for customer experience transformation, is implementing Amazon Q in Connect for a number of public sector, federal, and financial technology organizations. With Amazon Q in Connect, they have the ability to use a single engine to drive both customer-facing conversational self-service experiences and context-aware suggestions and automations for representatives. Pronetx expects Amazon Q in Connect will allow the public sector, federal, and financial technology organizations they support to focus on creating the experiences that matter most to their customers while empowering their representatives with the best decision-making information and guidance at the right time in every customer touchpoint.

Empower contact center managers with generative AI-driven insights

Contact center managers face significant challenges in managing customer journeys and engagement across digital and agent interactions at scale. Traditional methods of evaluating agent performance are often time-consuming and limited in scope, typically allowing managers to assess only 1%-2% of all customer interactions. This limitation makes it difficult to provide timely and comprehensive feedback, potentially introducing bias and reducing visibility into overall performance. Managers also struggle to efficiently categorize and analyze customer contacts, hindering their ability to identify trends, spot areas for improvement, and make data-driven decisions to enhance customer experiences. Without effective tools to automatically flag critical issues such as customer discontent or requests for escalation, managers often miss opportunities to address emerging problems promptly. These limitations impede an organization's ability to be more agile and adaptive in getting ahead of external and business condition changes that impact the customer experience.

To address these challenges, Amazon Connect has new enhancements that help contact center managers quickly spot important trends in customer feedback and identify agent coaching insights. Managers now have tools to automatically complete 100% of agent performance evaluations against defined quality standards, aided by conversational analytics and screen recording capabilities. Managers can automatically perform and complete evaluations, access aggregated agent performance data, identify specific coaching opportunities, and help their teams develop and grow. These improvements collectively contribute to the continuous enhancement of the customer journey. For example, managers will automatically be able to identify behavioral coaching opportunities on all customer interactions, like "interaction lacked empathy while delivering bad news to the customer." Amazon Connect also uses generative AI to enable managers to easily categorize contacts. Through natural language prompts, managers can automatically categorize contacts to understand call trends over time, flag calls indicating customer discontent, learn about communication breakdowns during calls, discover agent performance improvement opportunities, and more. As a result, organizations can train their staff more effectively, identify and address common customer issues faster, and improve overall customer experiences.

Fujitsu, a global digital transformation partner based in Japan, has collaborated with AWS to develop a generative AI-powered approach to quality assurance (QA). Traditionally, Fujitsu's QA process could only review 4% of voice interactions and 0.5% of chat interactions. However, with Amazon Connect, Fujitsu's service desks can now auto-score 100% of interactions across both voice and chat channels without increasing human effort. This advancement allows managers to focus on higher-level strategic initiatives and enhances QA efficiency by 60%, transforming Fujitsu's QA process into a real-time, high-sample, and unbiased approach without requiring additional QA resources.

Priceline, an online travel agency offering a wide range of travel-related services, uses Amazon Connect to analyze customer interactions quickly, zeroing in on problems and areas to improve the customer experience. With Amazon Connect's generative AI-powered agent performance evaluations and call summary, Priceline expects to reduce the time managers spend evaluating customer interactions. Priceline's managers have expressed enthusiasm for the system's ability to provide rich context in review notes.

University of Auckland, a public research university in New Zealand, uses generative AI-powered automated evaluations to improve the efficiency and effectiveness of their quality assurance process. Since implementing this feature of Amazon Connect, the university's team of 50 staff were able to focus more on targeted feedback and coaching rather than manual reviews. This shift is significantly improving their student support services while reducing staff training time and enhancing overall service delivery. Importantly, the new system is saving the university up to 10 hours per week on the QA process, time which can now be redirected towards other pressing tasks, further boosting productivity and service quality.

All of these features are generally available today. To learn more, visit:

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Peter Lo, AWS PR
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