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Nokia adds AI to its customer analytics software

Nokia has released a new version of its customer analytics solution that incorporates artificial intelligence algorithms, and the company says that the changes means getting faster results.

The new AI algorithms for Nokia’s customer analytics software were co-developed with Nokia Bell Labs.  Shelley Schleuter, head of analytics marketing at Nokia, said that they enable operator customers to get running and start seeing value from the solution faster.

Part of the customer analytics solution is Nokia’s Customer Experience Index. Schleuter explained that Nokia’s CEI is based on network, customer care and billing information across both fixed and mobile networks, combined with other sources such as social media and demographics, to correlate current customer satisfaction with their experience on a carrier’s network. She said that when operators implement the customer analytics solution, it takes some time before they can actually use it because it needs to be tuned to their specific customer base and customers’ needs — which can be very different. Schleuter noted that customer priorities for video streaming versus, say, reliability and speed of SMS delivery can vary by global geography and that the weighting of various KPIs has been a more manual process in the past, which is automated in the new release. 

When U.S. Cellular spoke to RCR Wireless News earlier this year about adopting Nokia’s customer satisfaction analytics to improve customer experience, the carrier described a start-up data collection period of about three to six months to accurately correlate customer sentiment with network information. The new software, Schleuter said, produces results about six times faster. Nokia says that the “algorithms optimize themselves over time, decreasing the time required for the initial tuning of the index from months to days, and delivering a far more accurate view of subscriber satisfaction.”

“It’s faster for [customers] to get started and achieve ROI, because they’re able to use it so much sooner,” Schleuter said, adding, “With the introduction of machine learning and deep learning algorithms, you get more accurate results.”

The new release also adds integration with Nokia’s Fastermind software, which uses machine learning to make automated recommendations on next-best-actions to take in real time to address customer issues.

The new software is slated to be available in the third quarter of this year.

Schleuter said operators are currently focused on the use of advanced analytics capabilities in improving customer experience, but that artificial intelligence in network insights will only become more important as the industry shifts to 5G.

“They way the technology is evolving, once we start hitting 5G, you have to automate to be able to keep up with the speed at which people are going to be able to spin up and spin down different slices of the network, and different technologies to accommodate people,” Schleuter said. “You’re going to have to automate, because I don’t think a human will be able to keep up otherwise.”

 

Image copyright: kentoh / 123RF Stock Photo

ABOUT AUTHOR

Kelly Hill
Kelly Hill
Kelly reports on network test and measurement, as well as the use of big data and analytics. She first covered the wireless industry for RCR Wireless News in 2005, focusing on carriers and mobile virtual network operators, then took a few years’ hiatus and returned to RCR Wireless News to write about heterogeneous networks and network infrastructure. Kelly is an Ohio native with a masters degree in journalism from the University of California, Berkeley, where she focused on science writing and multimedia. She has written for the San Francisco Chronicle, The Oregonian and The Canton Repository. Follow her on Twitter: @khillrcr

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