Mobile Data Means Business

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Recently Analysys Mason reported that global mobile data traffic is growing at a rate of 67 percent a year. Conversely revenue per gigabyte is estimated to fall 82 percent by 2015. Lyn Cantor, president of Tektronix Communications, believes that the huge surge in data traffic has meant that operators face a double headed challenge in both optimizing, and monetizing this traffic.

Operators are now transitioning to deploy networks that service the growing demand for mobile broadband. Today, carriers have deployed diverse technologies in their networks to serve the delivery of voice and data. Operators began with 2.5G, then moved to EDGE, 3G, HSPA and are now focusing on LTE.

With the network efficiencies that LTE provides, operators can reduce the delivery costs of mobile data and launch personalized services, and applications. Carriers are now shifting their focus to see quality from the customer’s perspective first, then from the services point of view and then, ultimately, the network; in an end-to-end manner. In order to achieve this, carriers require integrated solutions that have the ability to analyse customer usage and quality within, and between, each technology domain.

Lyn Cantor, president, Tektronix Communications, explained: “Network monitoring, assurance and optimization tools have always helped operators to manage their networks cost-effectively. However, a new generation of traffic management tools now exist that enable operators to better leverage the data from their network, which directly ties back to customer usage and preferences. This high value data allows operators to develop new, revenue generating value propositions that target individual users; or groups of users.

“As LTE will remarkably drive down the cost of delivery of mobile broadband; the ability to monetize all that new traffic is what will make, or break, an operator’s 4G business model. Operators that are able to collect and correlate high-value, and cross-domain, data will have the ability to see real-time quality and usage KPI’s, and statistics, at the end-user level. Moreover, data collected from across the network will help operators to perform predictive analytics to identify prospective churners proactively; or detect other usage patterns that may impact the bottom-line. Using this focused data, operators can develop new services and strategies that are perfectly targeted at the end-user.”