The amazing growth of big data continues to transform the way that businesses can serve customers, and nowhere is this more true than in the world of mobile. We’ve entered an exciting new era in which big data is redefining the mobile experience with the enablement of more personalized services. One of the newest of these services involves making use of the mass of subscriber data that mobile network operators have accumulated to better cater to individual mobile users’ needs – a concept that Syniverse calls “mobile context.” Over the last year, I’ve had the opportunity to present some insights on this topic at several industry conferences, and in this post, I would like to share some of them.
Big data continues to grow at an incredible rate. According to the Cisco Visual Networking Index Global Mobile Data Traffic Forecast Update, global mobile data traffic grew an incredible 81 percent in 2013, with last year’s mobile data traffic nearly 18 times the size of the entire global Internet in 2000. What’s more, it’s still only the early days for making use of big data. In 2013, only about 22 percent of digital information was a candidate for analysis, and only 5 percent was actually analyzed, according to IDC.
The opportunity associated with all this data is huge. Importantly, mobile data driven by smartphone use has disrupted what up to now has become a cycle for the evolution of mobile services and led to a new cycle termed a “fourth curve.” The term comes from a report by mobile industry analyst Chetan Sharma, “Operator’s Dilemma (and Opportunity): The 4th Wave,” in which he breaks out voice, messaging and data services by revenue growth “curves” and subscriber growth. In the cycle for these three services, each curve slowly rises when subscriber penetration is below 25 percent, accelerates until penetration reaches 70 to 90 percent, and then flattens and declines.
However, the latest wave of mobile services, or fourth curve, challenges this cycle. The fourth curve isn’t a single function as the other curves represent, but it includes a number of new formats, like cloud services and mobile payments. In addition, it includes a mix of companies and over-the-top (OTT) providers rather than mostly mobile network operators (MNOs) as with the other curves, and the average market cycle has shrunk to 16 months.
In light of this increased competition and shorter market cycle, harnessing big data to more contextually serve users represents a crucial opportunity. Mobile devices are now used by most of the world, and new technologies have fueled the way users integrate mobile devices with their personal patterns. As a result, today’s users want engagement in real time, and, significantly, in context to their usage. For example, users expect to be able to set up personal accounts with their favorite retailers to receive real-time alerts about order shipments and special offers.
A critical part of this engagement will involve using big data to better determine and serve users’ expectations. MNOs and companies must be able harness big data from real-time interactions and address the new needs of what Syniverse refers to as “mobile context.” Significantly, a large amount of mobile context information is available in the mountains of subscriber data that MNOs have amassed. The data includes everything from information on a subscriber’s device location, to a subscriber’s type and number of devices, to the amount of voice, messaging, and data services a subscriber uses.
The use of this kind of data for mobile context – which requires explicit end-user opt in – is now opening a world of exciting possibilities for more personalized services, from everything to fraud protection to marketing optimization to customer service. For example, to prevent fraud, banks can request that the location of an account holder’s mobile device be verified when the account holder attempts to use a credit card in a foreign country. Similarly, to promote sales, companies like airlines or MNOs can present special offers for flights or roaming to users whose mobile devices are detected to frequent a certain foreign location.
I’m excited about what lies ahead for big data and mobile context, and what new services will evolve to enable us to continue to enhance the user experience through mobile context.
What parts of the user experience do you think offer the most promise for mobile context? I would love to get your comments.