Verizon uses GenAI to improve customer loyalty

The Verizon logo is seen on the 375 Pearl Street building in Manhattan, New York City, U.S., November 22, 2021. REUTERS/Andrew Kelly/File Photo

STOCKHOLM (Reuters) - U.S. telecom company Verizon is using generative AI to stop 100,000 customers from leaving its service this year by predicting why a customer is calling, connecting them with a suitable agent and reducing store visit time, CEO Hans Vestberg said on Tuesday.

The company receives around 170 million calls every year and with GenAI it can now determine 80% of the time why a customer is calling, he said. "I have 60,000 call agents and I know what they are really good at so I can match your call with the right agent," he added, saying this would mean 100,000 customers staying with Verizon.

Earlier this year, Verizon launched several GenAI-backed initiatives focused on customer service. Other companies such as Swedish fintech Klarna have been using GenAI to cut response time in handling customers and save costs.

"We already have four generative AI products in commercial use," Vestberg said at the Future Talent Summit in Stockholm.

"We have 1,500 data points on each telephone number," he said. "We don't expose the data for anybody else. We run all our data, large language models inside our network, not outside."

Verizon has about 70 million store visits every year, and the company can personalize any offer as soon as a customer visits, cutting roughly seven minutes per store visit, he said.

It had reported about 145 million wireless retail connections in 2023. Its churn rate, percentage of customers who stopped using the company's services, hovered around 1%.

"We believe this year we can have less churn ... it's an experience for you, for my employee, and ultimately I'll make some more money," Vestberg said. (This story has been refiled to add the missing word 'AI' in paragraph 1)

(Reporting by Supantha Mukherjee, European Technology & Telecoms Correspondent, based in Stockholm, Editing by Louise Heavens)

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