Written By Kiran Matty, Marketing Manager, and Ola Mabadeje, Marketing Manager
If “Big Data” is crude oil, then Analytics is its refinery. According to a Cisco IBSG report, “if ‘crude” data can be extracted, refined, and piped to where it can impact decisions, its value will soar”. The trends, patterns, and insights that can be gathered from the various sources of Big Data are virtually limitless. However, this blog shall primarily focus on the analytics that can be generated by refining i.e. analyzing the data that’s resident in a mobile network and is largely untapped.
According to Cisco VNI, the number of connected devices will be three times the global population by 2017 and the global IP traffic will also increase threefold in the same time frame. Mobile Networks have not only been primed to sustain this onslaught but have also transformed into a programmable platform that can collect, correlate, and contextualize data rapidly. Network data, Policy, and Analytics interplay in a multitude of ways and form the basis of Data in Motion that’s at the heart of network monetization.
Hidden opportunities exist in the market gaps
As you might be aware, CPM (Cost per Mille) for mobile Ads is lower than that of other advertising media such as online, television, etc. This is because mobile Ads are generally untargeted, which leads to ineffective Ad campaigns, and could be attributed to a large extent to the lack of contextual awareness vis-à-vis location, demographics, browsing history, network conditions, screen size, etc. Although market researchers have perfected the measurements for other advertising media, they haven’t yet cracked the nut for mobile and the mobile metrics remain fuzzy at best which is impeding the flow of advertising dollars to mobile. On the other hand, as much as we love applications like Apple Siri and FaceTime, Angry Birds, etc., and devices like the Apple iPhone, they have turned out to be an operational nightmare in certain cases for the mobile operators around the world because of the data and signaling Tsunami that they can potentially bring about. This is due in part to lack of network analytics that can predict such surges in the network traffic with reasonable accuracy to allow for timely management of the network in terms of network capacity and bandwidth. This would eventually lead to operational efficiency and hence cost savings. Further, think about Internet of Everything and the 50 billion devices that would come online by 2020!
Mobile network operators are well positioned to address the above pain-points. With access to millions of subscribers, they can predict network and consumer behavior with high degree of accuracy quite simply because of the law of large numbers. Unlike many pure-play analytics vendors, network operators have direct access to data from a variety of sources such as CDN (Content Delivery Network), devices, applications, network billing and charging systems, not to mention the various mobile network elements. Some may even have access to subscriber Wi-Fi data. Lastly, many have the cloud infrastructure that’s needed for analyzing data at a bigger scale.
Translating opportunities to $$$ Continue reading “Unlocking the Value of Data in Motion Through Analytics”
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