GENERATIVE AI IN THE CONTACT CENTER: ARTIFICIAL INTELLIGENCE IN PRACTICE

Everyone is talking about generative AI, but few companies have implemented it in their contact centers so far. Here, we present five concrete use cases that are ready for practical application.

Marketing Content Writer | Cognigy

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CUSTOMER SELF-SERVICE: MORE EFFICIENT CUSTOMER INTERACTIONS WITH KNOWLEDGE AI

People who contact a company with a concern—whether it's a question about a bill or a refund—are not happy recipients of pre-fabricated copy-and-paste answers. Often, they have already done extensive research and have taken the step to contact the contact center. Generic FAQ answers to personal concerns, therefore, tend to breed mistrust and lead to customer frustration. It's like, after 20 minutes on hold, being told what you already know. However, with artificial intelligence, this can end. With the help of Natural Language Processing (NLU) and conversational AI, complex human language is understood. Knowledge AI accesses internal company information relevant to the inquiry and systematically queries it. Finally, generative AI presents personalized and context-based answers—all without employee intervention.

POST CALL WORK AND WRAP-UP ASSIST

If an interaction cannot be automated, the work of a contact center employee does not end with the conclusion of the conversation or chat. Rather, employees often have to manually enter data from each interaction into a CRM tool—a process that is repetitive and prone to errors and takes a few minutes. With hundreds of inquiries per day, this represents a significant time investment. There is no reason to make such an effort, as automatically created transcripts of each customer interaction are already available. Taking into account the customer's previous history and relevant context, generative AI can enter this data into company systems, saving time. This approach brings another significant benefit: the drastic improvement in data quality by considering all information and avoiding human errors. This is relevant since high-quality data can later be used for analytical purposes and to sustainably improve the customer experience.

REAL-TIME TRANSLATION AND COMMUNICATION OPTIMIZATION

Another obvious use case for generative AI in customer service is real-time translation of text and speech in human-to-human interactions. The advantages are not limited to optimized human resource management; customers also appreciate this feature due to the increased level of personalization. Real-time translation is particularly interesting for global companies or those operating in multilingual regions such as Switzerland. By allowing both parties to use their native language, misunderstandings are avoided, and the service is localized in real-time by generative AI. The result: bilingual employees become global problem solvers.

CROSS-SELLING AND UPSELLING

When effective communication is ensured, it also opens the door to seamless cross-selling and upselling. Opportunities for this often arise within a support conversation, and there are just as many reasons why these opportunities are not seized. One reason might be that opportunities are simply overlooked due to the high volume of inquiries—potential revenue remains unrealized. In an example available to us, a customer asks questions about her bill, through which the AI recognizes the chance to offer her a more comprehensive internet contract. The contact center employee receives a notification on his screen presenting all the information about the new internet contract and can discuss the details with the customer. The customer feels well advised and gratefully signs the new contract.

HYPER-PERSONALIZATION WITH LARGE LANGUAGE MODELS (LLM)

Lastly, good advice also means personalization, which can undoubtedly be achieved through large language models. Personalization using AI leverages collected data and uses it to tailor service experiences even more closely to customer needs. Important in this aspect is not just mentioning the customer's name when giving a response but incorporating the entirety of all customer events into each interaction. The implementation of empathy also benefits from the knowledge of the entire customer history. Generative AI recognizes intentions, moods, and considers these in every interaction to conduct empathetic dialogues and find solutions best suited to the interest of each customer. This fosters trust in a company and increases customer satisfaction.

Overall, these five use cases illustrate the transformative power of generative AI in the contact center. From more efficient customer service and automated follow-up to hyper-personalization, the integration of artificial intelligence enables service optimization that goes far beyond traditional approaches. The targeted use of generative AI not only increases efficiency but also elevates the customer experience to a new level, ultimately leading to sustainable improvement in customer retention

Want to learn more about the potential of Cognigy’s AI agents—powered by Generative and Conversational AI? Then secure your personal appointment with us at booth 3H10!

Cognigy brings AI to the contact center. The market-leading solution Cognigy.AI enables excellent customer service without waiting times, in natural language, on any channel. This enables companies to increase customer satisfaction and actively support employees in live support. The award-winning Conversational AI platform, enhanced with Generative AI, offers turnkey solutions for outstanding services and is used by customers such as Lufthansa, Toyota, ARAG and others worldwide.

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