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AI-Powered Customer Service: Use-Cases and Real-World Examples

Cognitive/AI technologies for customer engagement are white hot. No wonder professionals, who had removed AI from their resumes, are scrambling to add it back in!

As a pioneer in cognitive/AI solutions for customer service and engagement, eGain has not only developed cutting-edge technology but also proven use-cases and best practices over the last two decades. In this article, we discuss four use-cases that have already enabled blue-chip companies to transform—not just improve—customer service and engagement.

  1. Understand and answer

Virtual assistants (VAs) help businesses wow customers with natural language understanding and distinctive self-service, while helping them cut costs and build brand equity. The best VAs are also multilingual and communicate in multiple modes—text-to-text, text-to-speech, speech-to-text, and speech-to-speech. Importantly, they know what they don’t know. When unable to answer the customer’s question, they escalate to human-assisted customer service with full context from the self-service interaction. For the VA to be able to do this out of the box without integration work, it needs to be an integral part of an omnichannel customer engagement hub which consolidates omnichannel interactions, knowledge, AI, analytics, and administration into one platform.

eGain AI clients understand and answer:

A large government organization in the UK uses the natural language capabilities of eGain Virtual Assistant™ to understand and answer questions from taxpayers, with intelligent and seamless escalation to live chat when necessary. Deployed in time to support the critical tax returns period, eGain Virtual Assistant and eGain Chat™ helped deflect 77% of their phone calls within the first six weeks of the deployment!

  1. Guide search and processes

While VAs are good at answering questions of low-to-medium complexity, AI reasoning technologies can guide customers and contact center advisors through interactions of higher complexity. Reasoning can guide users to the next best steps in their search for the correct answer or in-service processes such as troubleshooting and advice. This conversational, dialog-driven guidance is based on intelligent understanding of the problems faced by the customers as well as customer service expertise drawn from the best agents.

AI reasoning applies learnings from past cases to find solutions for new ones. Learning should be derived through a curated model rather than a fully automatic one, especially when the stakes are high, to ensure the best outcomes and process adherence. Watch out for pretenders like rigid scripting and rule-based systems—they tend to put agents and customers in conversation cul-de-sacs and dead ends, especially when the customer goes off-script (which is quite common). Moreover, such legacy systems are difficult and expensive to maintain.

eGain AI clients guide:

♦ A global bank uses eGain’s patented AI reasoning technology to guide a largely novice agent pool through best-practice interactions across 11 countries, while reducing training requirements by half.

♦ A leading telco guides 10,000 contact center advisors and associates in 550 retail stores with eGain AI for a 37% improvement in First-Contact Resolution (FCR), 50% improvement in advisor speed to competency, and a 20% boost to their NPS (Net Promoter Score).

♦ A multi-play CSP reduces unwarranted “No Fault Found” handset returns and exchanges by 38% with AI-guided problem resolution in the contact center.

♦ A white goods giant saved $50M per year by reducing unnecessary truck rolls through AI-guided problem resolution in the contact center.

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