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Large companies can staff their call centers with far fewer people because of a new AI technology from
The latest private tests are currently running at six companies, including Pathé CZ, Wijnvoordeel and Yoursurprise, with a generative AI that combines company-specific data with the best-known language models, aka LLMs. Depending on the company and industry, a decision tree determines which AI is deployed for which purpose. Ultimately, it is always about answering consumer questions to a customer service department.
CEO
Companies can train CM' s new Generative AI Engine with their own data. "We learn a company's language in a few minutes by reading the site, old customer conversations and chatbot interactions and numerous files - think JSON and PDF." "Then you can query your own company information. ChatGPT can't do that, because it's too generic. It doesn't learn from internal company data."
The learning process is divided into two steps. A company feeds its data to the CM cloud. This then strips out any potentially personally identifiable information, because of privacy rules, and only then puts it through to Google PaLM,
The cleverness of this system's design,
"Customers have trouble finding budgets and staff for customer service. We say to them, just give us some of those HR budgets, and we'll provide the people work." In practical terms, that means fewer people can do more work. They become more productive because the AI machine listens in on customer conversations and suggests answers. "And so in multiple languages. So a Dutch speaker can speak to French customers of a French service provider or store ín Dutch." The AI does the translations.
In a few weeks, a large company will start using the new system. That will result in substantial savings in operating costs.
"You can also start using AI tools for sales purposes. Think of a scenario where someone visits a site and contacts the chatbot with a question. That could actually lead to a transaction, a purchase. Measurements show that chat has a conversion-enhancing effect. It looks like, that's about five percent with a human agent and up to 15 percent with an AI." Director: "We suspect AI bots stay friendly longer and give consistently better answers in terms of content. They are equally good at their work at the beginning and at the end of a workday. Humans, on the other hand, may be tired and therefore a bit short-tempered, for example."
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