Reimagining Customer Experience with Generative AI

Customer experience is everything. A strong customer experience can cultivate loyalty for a lifetime, while one poor interaction can alienate a customer and cause irreparable harm to a brand. In an analysis of earnings call transcripts of S&P 500 companies between 2007 and 2019, researchers found that 92% of the 31,000+ transcripts mentioned the vital importance of customer experience and satisfaction to the company’s existential success. With the emergence of Generative AI, brands have a new and powerful tool to revolutionize their customer engagement strategies.

The contact center, the hub of most customer service operations, is a good case study of how customer experience has been shaped through technological revolutions. The internet turned telephone-based customer interactions to web-based support. Mobile made contact centers quicker and more convenient, bringing support into the hands of the customer. Cloud computing ushered in unprecedented scalability and flexibility, enabling call centers to handle surges in customer inquiries and integrate data from various channels to better equip customer success agents. The latest shift, Generative AI, is poised to elevate call center operations by substantially broadening the surface area of automation. McKinsey estimates a potential productivity lift in customer operations of over $400B due to Generative AI.

Generative AI Application in Customer Support

AI has become an indispensable element within call centers. According to a survey conducted by Boston Consulting Group in 2022, enterprise investment in call center technologies is expected to significantly increase over the period to 2025. In fact, 95% of customer service leaders surveyed anticipate integrating AI bots into the customer service journey. The allure of AI for customer support lies in the fact that the process possesses the ideal characteristics for automation: it is both data-driven and comprised of repetitive workflows. Generative AI could propel this disruption to new heights with a greater degree of automation, personalization, and overall support optimization.

Large Language Models (LLMs) have the power to meaningfully expand what can be automated in call centers. Trained on vast amounts of data, these models excel at handling complex customer inquiries, generating responses that were previously unattainable with traditional AI technologies or manual processes. A study by McKinsey demonstrated the practical benefits of Generative AI: for a company with 5,000 customer service agents, implementing LLMs led to a notable 14% increase in issue resolution per hour and a 9% reduction in issue handling time. Moreover, by automating responses to a wider range of customer inquiries, LLMs enable human agents to focus on addressing the most intricate cases. This advancement significantly improves agent productivity, reduces attrition rates, and provides enhanced support, particularly for unique customer inquiries that require personalized attention.

Generative AI also introduces a new era of personalization in customer support. By leveraging real-time customer sentiment analysis and existing customer data, AI algorithms can generate tailored responses and suggestions, catering uniquely to each individual’s needs. Furthermore, multi-lingual models bridge language barriers, allowing agents to translate and respond to customer queries in their preferred language. This seamless multilingual support not only enhances customer satisfaction but also unlocks immense business opportunities in global markets.

In the realm of contact centers, Generative AI emerges as a beacon of promise. As this technology evolves, automating more complex tasks and integrating vast amounts of data, the role of agents will shift from reactive responders to proactive and strategic supporters. Through handling more intricate customer inquiries, across various stages of the customer journey, Generative AI will provide tailored and personalized suggestions akin to a personal assistant, rather than a mere chatbot. While current limitations (i.e., model hallucination and occasional factual inaccuracies) impede full enterprise adoption, the emerging behaviors of generative models applied to customer support are promising. We anticipate that customer support and the customer experience as a whole will be reimagined. These hypotheses grounded our initial investment in ASAPP, and we are excited to continue supporting companies at the forefront of this transformation.

ASAPP, a Trailblazer in Contact Center Automation

We first invested in ASAPP in 2018, recognizing the company as the leader in research and development of artificial intelligence for the customer experience. With one of the largest and most well-respected research teams in the industry, ASAPP has spent years developing a comprehensive and incredibly impactful AI-native contact center platform. According to Priya Vijayarajendran, Chief Technology & Security Officer at ASAPP, their strength lies in “transitioning AI from a mere capability to an enterprise-ready service.” Renowned enterprises such as Dish, JetBlue, and American Airlines have already embraced ASAPP’s solutions, resulting in elevated customer satisfaction (CSAT) scores and enhanced operational efficiency. Put simply, the goal for ASAPP is twofold: leverage automation to give agents only high value activities and provide the tools to help agents excel in those activities.

While they first emerged in the general consciousness last year, LLMs have been embedded into ASAPP’s offerings for years. ASAPP trains LLMs on a vast corpus of customer experience and support-focused data and optimizes these models for specific key performance indicators (KPIs) and desired business outcomes. This is all done with a high degree of attention to data security and compliance. The results have been impactful, as exemplified by JetBlue’s collaboration with ASAPP to implement a robust Generative AI solution. This implementation has led to an average time reduction of 280 seconds per chat, saving a staggering 73,000 hours (over 8 years) of agent time in just one quarter.

While automation plays a large role in delivering call center optimization, ASAPP’s secret sauce is supporting the agent with a suite of tools for each step of their journey with the customer. AutoCompose enables agents to craft messages during conversations, AutoAssist generates real time customer assistance for every stage of the customer interaction, and AutoSummary automatically summarizes calls and chat interactions. Through these and other tools, ASAPP ensures every agent in the call center can perform like a top agent.

The future of call center customer experience extends beyond LLMs. Agents need to comprehend customer sentiment, execute actions on behalf of customers, and leverage information from various sources and tools. A significant portion of an agent’s work goes beyond the conversation itself. As a result, models need to become multimodal and leverage all available information. ASAPP has already invested in understanding the data stream of agent actions, enabling the development of multimodal models that enhance agent augmentation. This means that information gathered during the conversation can directly inform the actions the agent should take (i.e., automating booking of flights for the customer). ASAPP’s mission has always been to multiply agent productivity, and we are confident in their ability to continue spearheading innovation in the customer experience.

Generative AI: A New Path to Customer-Centricity

Generative AI is ushering in a new era of customer experience, and we are thrilled to witness a wave of innovative companies fundamentally transforming how brands connect with their customers.

Some enterprises have explored early conversational AI use cases with chatbots and autonomous agents to answer customer inquiries in real-time with human-like text and voice, provide personalized recommendations, summarize calls and reduce response time. Incumbents like Five9 and NICE have been fast to adopt LLMs for these use cases, and generative-native disruptors, like Birch AI, Aide, Siena and Ultimate AI have built complex platforms to instantly bring the functionality and ease of use of ChatGPT directly into the call center. We are also excited to see new categories created in customer experience, such as customer feedback analysis with upstarts like Viable, Enterpret, and Unwrap, delivering valuable insights from a company’s proprietary and public data channels.

Customer experience in 10 years will look much different than it does today. At March, we are excited for the companies that are leading the charge, and the enterprises that are embracing the change to gain a competitive edge.