Editor’s Note: Welcome to our weekly Reality Check column. We’ve gathered a group of visionaries and veterans in the mobile industry to give their insights into the marketplace.
Users love their smartphones and tablets and are increasingly comfortable in being in contact with the Web all the time; mobile data is getting big and estimated to be doubling every year. This is resulting in challenges not just in the network and traffic management, but also in terms of the business of providing profitable data service products. Leveraging the traffic flowing through the system to understand what is happening is a business critical function. In other words, in an era of “big data” the business needs to decide how it will define success and then develop key measurable and actionable insights around this using mobile data analytics to keep the business focused.
Developing intelligence and actionable insights starts first with understanding the user’s relationship with their device (and apps) – can more users be encouraged to use more mobile data? Secondly, the user’s relationship with the network should be understood – when and where and how long do they stay connected? At a third level the user’s aggregated relationship with the Internet is critical to provide application level insights into what users do when consuming mobile data. From a business perspective big mobile data is more attractive if the footprint of revenue and load can be spread among a larger group of the user communities (targeting different demographics). In this regard, providing users with alternative options on data consumption to attract changes in user behaviour is under-pinned by mobile data analytics. The provider of data services needs data to be analysed at all levels (not just capacity) to develop a better relationship with the user. This relationship is focussed on developing brand loyalty (rather than treating the connectivity as completely commoditized), creating a differentiated user experience, understanding the profitability of current data products and developing new opportunities.
How can the next steps in the user relationship and engagement become more sure footed? As it transpires mobile data service providers are sitting on a vast amount of data simply due to running their networks. These networks are generating data faster than ever before because processes are becoming increasingly automated, systems are becoming increasingly interconnected and people are increasingly interacting. Intelligence and understanding can be gathered from the data flows, the customer self-care (demographics, preferences, billing), call center contact (issues with devices and services, and problem “hot spots”) and from the device itself (device types, apps and network connections). The question is how to make this available to the business data scientists? and consequently how do we translate key data points and tracking indices into segmented reports?
Rob Rich, managing director of TM Forum Insights Research, surveyed teams of senior executives from 17 service providers across North America; Europe, Middle East and Africa; Asia-Pacific; and Latin America for a recent report around big data. Forty-one percent of respondents gave themselves a grade of “C” or average when it comes to their ability to realize the benefits of analytics, while 18% graded themselves as “below average.” This is mainly because of the sheer volumes and the nature of the unstructured data presented to them. Trying to make sense of large data sets from multiple sources is challenging and, in fact, borderline impossible. Only by leveraging the right mobile analytics solution can they achieve a holistic picture of the technical challenges and monetization opportunities.
So, how do mobile data service providers know when they’ve found the right mobile analytics solution? From our experience working with operators around the world, here are some of the major items to consider.
Scalability: According to Cisco’s latest Visual Networking Index Global Mobile Data Traffic Forecast, mobile Internet data will see a 13-fold growth between 2012 and 2017, with a compound annual growth rate of 66%. With this exponential, year-over-year growth, the “right” analytics solutions should be extremely scalable to extract and analyze data accurately and efficiently, regardless of the volume of data.
Reporting: The reporting an analytics solution can provide a mobile operator is crucial to its success. There are various factors that make effective reporting including how quickly the solution can generate insights. Most analytics solutions work through a “push” model, pushing the data out on a regular basis. However, by adopting a solution that works on a “pull” model will enable carriers to aggregate network data based on multiple different subscriber segments, allowing them to easily discover trends within the segment.
Speed: The speed in which the analytics solution can generate insights is also an important factor within reporting that needs to be considered. As big data is considered “old” within about 24 hours, a solution that extracts the best data is behind the curve if it can’t produce actionable insights within an acceptable time frame.
Action: After data analysis has provided an array of user and network data, the challenging part still remains – making sense of it and acting on it. Ideally this is embodied in a single, end-to-end solution that pulls the data, analyses it, and enables the engagement with the user to act on it. Mobile data analytics has the potential to enable carriers to monetize their user’s behaviors simply by offering intuitive reporting that makes sense. For example, it could identify the data usage habits of their user, such as heavy high-definition video streaming, and deliver a personalized online experience through offering data plans targeted at heavy video viewers at a discounted rate.
Alternatively, mobile data analytics can anticipate network congestion by identifying times and locations that data usage is at its highest and address it, an application level, before the user experience is impaired.
There is also another way that the business marketing and operations departments can utilize the data gathered through mobile data analytics. Through using the deep analytical data collected, marketers can make evidence-based decisions for promotion and campaign strategies by enabling targeted real-time data service promotion, ensuring users receive relevant, meaningful offers based on their consumption profiles. A complete analytics solution does more than just extract data; it also helps data service providers to act upon it. Mobile data analytics will become integral to delivering personalized subscriber experiences and allowing operators to monetize on their behavior.
What next in the era of big mobile data? Intelligent, cost effective and comprehensive analysis of the mobile data to enable the business of providing data services to discover and action their relationships with users to sustain and develop differentiated user experience and revenue.
Fergus Wills is director of product management for Openwave Mobility, and has over 16 years of experience in telecoms, primarily on large scale server-side mobile internet data products. Holding a BSc in Information Technology from Queen’s University Belfast he has been involved in several industry bodies on mobile data.
