Next Generation Communications Blog

May 2013

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Facebook's Signaling Chatter Grows Louder

By Lindsay Newell, VP, Marketing Networks & Platforms Group, Alcatel-Lucent

Our last few blog posts on mobile intelligence focused on how changes to devices and their operating systems can affect both the user experience and the network in positive and negative ways as detected using the 9900 Wireless Network Guardian. Today we will explore the impact of changes introduced by a new version of a popular application.

Last year, Facebook released new versions of their mobile app for Android and iOS. Prior to the new release, Facebook signaling and airtime already accounted for 10% and 15% of the overall load on 2G/3G networks, respectively.  As users around the world updated and started to use this new version, we quickly noticed a dramatic increase of almost 60% in the signaling load and 25% in the airtime consumed by the Facebook application.  During the same period, the number of Facebook users increased by only 4%.   Clearly, it is not the swelling of Facebook’s community that intensified the load, but rather the introduction of new Facebook features for mobile users and underlying platform changes.

Proactive Care Puts Operators One Step Ahead

By Thomas Fuerst, Senior Director, Multimedia Solutions MarketingAlcatel-Lucent

Monitoring and analyzing network data proactively saves operators time, money, and customers.

When a network service fails, it makes headlines, ticks off customers, and costs that network operator money. When a failure is headed off in advance, on the other hand, there might not be praise-laden headlines, but it's newsworthy nonetheless.

The traditional approach to customer care has typically been: a disgruntled customer calls customer service and complains of a service interruption or problem; the rep, learning of it for the first time, sends out a technician the next day, and eventually finds a resolution. Often, customers are left feeling put out, and the operator has spent significant time and money resolving the problem. Even worse is the customer who doesn’t call and just feels this is ‘typical’ of their network experience.  That is a customer at risk of leaving.

Proactive care flips this dynamic on its head by using predictive analytics to identify potential outages or errors in the network and stop them before they occur. It consists of three main parts: one, constantly monitoring and measuring data on the network; two, real-time analysis of the data; and three, the most important, acting on that analysis to fix the problem.

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