The capacity for data capture, storage and analysis has increased significantly in the last decade, and the mobile industry has a significant opportunity to evolve processes and methodologies to take advantage.
It’s 1959. A 5MB hard drive is being loaded onto a truck. This was the year that Elvis Presley was in the music charts with his famous song ‘A Big Hunk of Love’. At that time, Elvis did not have to worry about digitalised songs being distributed illegally: you would have needed a large removal truck full of hard drives to transport the digital version of just one of her albums, and a dozen men working for the whole day just to copy it. Today, it only costs USD600 to buy a device capable of storing all the music albums in the world, and you can easily copy anything on it with the click of a mouse.
This massive advance in device storage capacity and computing technology benefits many more people other than just the music pirates. The large-scale utilisation of internal data is becoming critical to successfully competing in many industries: the era of ‘big data’ has begun. We believe that, of all industries, mobile telecoms has the most to gain from this evolution, because of three assets:
Firstly, the mobile market has very high levels of penetration, even emerging economies have penetration rates of around 100%. Further, mobile is an oligopolistic industry, with typically just three or four mobile operators in each country. This means that most operators have access to data from a large number of customers, and multinational operator groups have access to customers’ data from several countries.
Secondly, mobile operators have access to a large amount of data per customer. Data is generated every time a customer makes a call, navigates the web or acquires a product using their phone. Simply by having the phone connected to the operator’s network data is being generated, such as location, speed of movement and even biometric data.
Lastly, the diversity of data availability allows mobile operators to achieve a depth of customer profiling beyond that of other industries. Operators have the potential to know a customer’s whereabouts, their network of contacts, content preferences, wealth and product preferences.
In the not-so-distant future, mobile operators will also be able to generate revenues from the packaging and selling of this data. With traditional revenues such as voice and SMS under pressure from web-based services and over-the-top (OTT) providers, and with mobile broadband now reaching its peak of profitability in developed economies, we expect big data to be the next source of enhanced profitability. But in order to move on to this stage, operators need to set up the basic processes, frameworks and technical infrastructures needed to capture and manipulate big data.
Before considering big data sales as a source of revenue, operators could use their data access to enhance internal processes, such as knowing customers’ value, what type of content they prefer and the type of device they carry. Similarly, decisions on the rolling out of networks and sales channels should consider the location and demographic data of potential customers. Customer care departments should use data to predict when a customer is at risk of churn and act upon it. Customer data will also allow operators to reduce their losses from customer or dealer commission fraud.
Large European operators, such as Orange, Telefónica and Vodafone have, for several years, leveraged the power of data analysis to improve their management decisions. In general, Middle East and African operators are still in the early stages of these processes. There is therefore enormous potential to increase revenues and margins by enhancing the customer experience using data analysis to improve internal processes.
The capacity for data capture, storage and analysis has increased significantly in the last decade, and the mobile industry has a significant opportunity to evolve processes and methodologies to take advantage.
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