There is an inherent mistrust of customer data-gathering processes and in-network analysis, due to the story of the NSA’s requesting subscriber data from large U.S.-based operators. Operators and over-the-top (OTT) service providers are just looking at the flows of data, not subscribers’ email, unlike Google or Facebook – two everyday, familiar consumer brands. Third-party network solutions providers hide individual subscriber details but aggregate information to improve the Quality of Service (QoS) and the user experience.
Even before the NSA story broke, service providers of all shapes and sizes collected subscriber data. It is understandable that data collection is under more scrutiny than it was before, but this is nothing new. If subscribers wish to receive refined service packages, application-based pricing, and other innovative mobile data offerings tailored to their usage habits, they must continue to allow operators to collect their data or ask service providers for an option to opt-out.
Cisco’s “Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2012-2017” predicts that global mobile data traffic will increase 13-fold between 2012 and 2017. For mobile operators, this growth and subsequent analysis represents a potential boon but also a red flag. How do operators reconcile the fact that mobile data analytics can generate better quality of experience (QoE) for their subscribers, while satisfying subscribers’ demand for privacy?
There are core user scenarios where the examination of content being access by users is important – from a legal and legislative perspective (for example UK’s recent war against porn). In this case, the legitimate policing of the net access for specific information can be agreed to voluntarily with the subscriber (opt-in). This is different from mobile data analytics, in which the data service provider aggregates data to establish patterns of behavior in groups of subscribers and connect these to general trends. This is very useful to look at capacity and quality of experience on a per device basis or to see what is driving the increases in the capacity on the network.
For instance, one of the most bandwidth-intensive forms of mobile data usage is from high-definition video traffic. Faster mobile devices, with myriad video application choices, proliferate mobile video data traffic but operators must be able to gauge network traffic spikes of mobile video traffic accurately.
Only when operators have a comprehensive understanding of data traffic patterns will their network components and solutions adjust to enhance data flow, mitigate congestion, and offer targeted services effectively. In understanding how users are consuming application data across wireless connections will improve the way the business of providing that access is run, from the provision of new attractive data plans for users to measurable quality of service metrics for end users with different applications.
The NSA data collection story, along with ever-changing social media privacy policies, worries people who consider data-gathering a threat to their privacy. In the telecom world data access records will be gathered from the perspective of billing reconciliation and non-repudiation, it is how these records, or derived information may be further used which may raise the concern in respect of privacy.
The concern is also on the operator side as they do not want to jeopardize the relationship with the subscriber. The mobile data market is highly competitive and an end goal of operators is to establish, develop and continue their relationship with their users – so even in the process of aggregation and analysis of data access service providers are, in our experience, extremely sensitive to privacy concerns of their customers.
We have seen an increasing trend globally for operators to use data analysis from the perspective of providing more refined user services or data services. Instead of a one-size-fits-all service, service providers are creating different services tailored to specific subscriber segments such as premium video packages for avid YouTube fans or roaming packages for the world traveler. In providing these packages the operator must consider the quantity of data or time to offer at the right price point to be successful in the market and that means more data analysis of the subscriber base.
A wider variety of service options means subscriber QoE will continue to improve and operators will see additional opportunities for incremental revenue increases. Having clear QoE metrics for services can be used as a service guarantee for subscribers and measurable from both sides of the relationship between subscriber and operator, ensuring the subscriber gets what the pay for. In order to provide this type of guarantee in next generation networks data analysis will be an on-going requirement.
Instead of offering all-you-can-eat packages, advanced data analytics will help derive application-based packages. This refers not only to specific applications, but application types, such as online games or HD video. Operators can offer packages based on the time of day or day of the week, and even peak vs. off-peak packages. For instance, a subscriber can purchase a monthly video-watching package that allows him to watch four or six hours of online video per week. These package offerings allow users to judge their data spend by the type of access they are getting.
Operators use intelligence gathered on their networks to sell differentiated data services via applications. This can extend to more innovative group packages allowing allocations not just by GB but by app, device type, network access type, or time of day allowances for example.
The clear advantage here for the subscriber is more tailored packages reflecting what they want to consume, where they want to consume it and at the right quality of experience; thus developing the relationship between themselves and the operator. The clear advantage for the operator is in establishing and maintaining that relationship with differentiated services which will be under-pinned by mobile data analytics.
It should be noted that operators are not the only ones capturing and analyzing subscriber data. OTT enterprises, such as Google and Facebook, capture a lot of subscriber data as well. They do so because they want an increasingly secure environment and to understand what’s happening with their applications in the mobile network data flow.
Today, it is not a question of whether organizations collect customer data. There are bound to be privacy concerns attached to this process but the intent of data aggregation and analysis is not malicious. In fact, it has to be the opposite, as the misuse of personal information will significantly affect the business the operator is in and will probably be casual factor in churn.
As subscribers, it will only benefit us to allow operators a better understanding of our personal preferences and behavioral patterns. Easier-to-understand, granular price points and tailored offerings will only improve our experience and that is ultimately what we are looking for, after all.
This blog was published by Mobility Tech Zone on Oct 16 Click Here