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MWC2015: Nokia unleashes predictive marketing for cellcos

02 Mar 2015
00:00
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Amid the blitz of press releases Nokia Networks has been unleashing ahead of this year’s Mobile World Congress, the biggest news could well be Nokia’s push into the big data analytics field with a new solution that helps cellcos create marketing campaigns in minutes instead of days.

The analytics solution, dubbed predictive marketing, combines two existing Nokia solutions – CEM on Demand and Mobile Marketing Suite – and uses network data from a variety of sources to give cellcos a broader view of mobile users’ service experiences to the point of being able to predict future behaviors.

That capability will help cellcos automatically target the right personalized message to the right customer, says Nils Kleeman, head of Mobile Broadband APAC at Nokia Networks.

“There’s a lot of information in the network, but think about where that’s coming from. It’s coming from CEM, network data, device data, OSS, and iSON,” Kleeman told telecomasia.net. “What we can do is leverage that network insight and device behavior data and CEM, etc, to help the operator come up with new marketing campaigns – what areas of marketing, and locations they should run their campaigns in, in a predictive way.”

The predictive marketing solution captures contextual customer data in close to real-time that can be used to dynamically segment and target marketing messages. The result automates and simplifies what is usually a time consuming and labor-intensive process, and enables cellcos to monitor customer experience, campaign success rate and resulting benefits as it happens.

Nokia claims its predictive marketing solution can improve campaign click-through rates from 4% to potentially 25% (though that figure comes from T-Mobile using Nokia’s existing Mobile Marketing Suite).

The predictive marketing solution is just one angle of Nokia’s Predictive Services Suite, which also introduced a new service called Predictive Care, which is based on a machine-learning concept to detect network elements' behavior anomalies in order to predict and resolve issues before they impact customers.

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