“I feel like we’re back in the days of the gold rush, but we’re still building the picks and shovels and designing the next pair of Levi jeans for the miners – We’re not yet extracting the gold.”
Yifat Kafkafi Business Development Manager, Amdocs Big Data Analytics
Service providers today are sitting on a goldmine of customer data.
Data such as customer location, mobile app usage, social media activity, digital content consumption, customer demographics, care interactions, billing and machine-to-machine sensors all afford the service provider deep insight into their customers’ digital behavior and preferences, buying patterns and quality of experience.
Given the fact that service providers are an integral part of their customers’ lives ‒ 91% of smartphone users keep their phone within arm’s reach 24 hours a day according to research from Morgan Stanley ‒ just by analyzing geo-location data for example, service providers can understand their customers’ commuting patterns, what stores they go to and where they spend their leisure time.
But having this data is not enough without the tools to leverage it – which is where Big Data Analytics comes into play. The advent of new Big Data technologies enables the analysis of this wealth of data and the ability to produce meaningful insights in ways that were not possible with traditional BI and analytics capabilities.
The three V’s
Using the framework of the three V’s; Volume, Velocity and Variety, we can see how Big Data Analytics differs from the traditional analytics and business intelligence technologies service providers have been using in recent years:
Volume: Collecting, storing and analyzing huge volumes of data quickly and cheaply. Storing and analyzing two years of a customer’s data versus three months provides much deeper insight into a customer’s preferences and the ability to target them with more accurate content recommendations.
Velocity: Analyzing data and taking action in real or near-real time, for example by pushing targeted advertising in real time to a subscriber when they arrive at a specific geographic location. With batch mode processes, by the time this information is analyzed it would no longer be relevant.
Variety: The ability to analyze and gain insight from data sources that were not utilized in the past. Analyzing network data enables understanding a customer’s digital behavior and preferences – apps used, websites browsed, searches queried, videos viewed, purchases made – and at what times and which locations.
Time to mine
Encouraged by all this potential, service providers are beginning to implement Big Data technologies and to develop new business models to monetize their data assets. Grant Watts, head of global advertising at SingTel, gave an apt description when he recently stated, “I feel like we’re back in the days of the gold rush, but we’re still building the picks and shovels and designing the next pair of Levi jeans for the miners – We’re not yet extracting the gold.”
Service providers are starting to make use of Big Data Analytics to launch highly personalized marketing offers, provide proactive customer care, and optimize the customer’s network experience to list just a few use cases. SK Telecom, a service provider in South Korea, achieved a fourfold improvement in churn prediction by analyzing browsing behavior from network data. They identified that customers typically searched for specific phrases, such as “data plan” or “operator benefits” and browsed certain websites 3 to 7 days before they churned. By identifying customers at risk of churning, they can step in proactively to retain high value customers.
In addition, new revenue streams are being created by providing insights based on customer data to external partners. In the U.S., Verizon is analyzing customer location patterns to understand where and how they spend their time, offering enterprises the ability to send targeted advertising based on those insights in an anonymized and aggregated manner. In one statistic cited by Gartner Research, Verizon enabled a basketball team to increase season ticket sales by 35% through targeted advertising.
Big Data Analytics has also showed impressive results in improving the accuracy of fraud detection in a recent trial undertaken by Telefonica O2 UK in partnership with a leading UK bank. Telefonica’s JetSetMe solution sent location data updates in real time to the bank’s fraud system for customers who had opted in. When customers used their credit card while traveling abroad, the bank’s real-time fraud detection used the location data to predict that it was a legitimate use of the card and approved the purchase, which otherwise might have been blocked. The business value of the solution was forecast to be multi-millions of pounds annually for the bank, due to increased revenue from higher number of purchases made, reduced operational costs from less customer calls to the call center, and improved customer satisfaction.
The business potential is vast, but there are challenges that must be addressed – the most important of which is privacy. Service providers must abide by the laws and regulations concerning the use of customer data, while also carefully protecting their brand image which could be damaged by even the perception that data is being misused.
Given the uncertain climate around privacy regulation, the current best practice is to use an opt-in policy. Service providers should clearly communicate to consumers what personal data will be analyzed, how it will be used and receive their consent before using it, all while explaining exactly what value consumers will receive in return; whether it be a more personalized experience, access to additional content or better pricing options. Check out this video Channel 4 in the UK produced with comedian Alan Carr which, in my opinion, sets the bar for explaining an opt-in policy in a simple, user-friendly and engaging manner.
Of course, Internet and e-commerce companies such as Google, eBay and Apple are not resting on their laurels when it comes to Big Data either. They were the pioneers in using Big Data Analytics and they also have access to lots of customer data which they are working to monetize. Google is already a powerhouse in advertising and has volumes of data on users of Google’s search engine, Chrome internet browser, Android mobile OS and apps such as Gmail and Waze. Beyond this, the recent acquisition of NEST could even give them access to smart home data.
Just like the California gold rush of old, there are fortunes still to be made. Service providers are well positioned not only because of the quantities of data they hold, but also (and more importantly) because of the wide variety of their data sources and their ability to interact with customers in real time. But they’ll need to move quickly before the competition beats them to it.
Photo Credit: Shutterstock/ Gold nuggets