To deliver a great customer experience, operators are building next-gen networks capable of handling explosive volumes of traffic, even as subscribers continuously change devices, download applications and find new ways to communicate.
These networks must access information from every device, application, service and network element a subscriber touches to perform optimally. This yields a tremendous amount of data – Big Data. Operators are just beginning to understand how to leverage “pipe data” to predict consumer behaviors, preempt service issues and improve profitability.
The smartest operators are changing culturally. While the technological challenges of transforming data into actionable insight may seem difficult, early adopters are poised to enjoy the same agility that powered the most successful web, social media, and merchandising companies of our times.
Where is all this data coming from?
Every customer action leaves a trail. Networks carry billions of messages every second to query databases, ensure interoperability, measure QoS, access content, deliver key services, download applications, and more. The nuts and bolts of mobile communications – devices, network elements, towers, OSS/BSS solutions, policy management systems, application servers, and rich communications services – also contain a dazzling amount of information. Big data techniques for correlating and identifying patterns across these data sets will provide the insight operators need to make smarter decisions, from the control room to the board room.
As with all grand ideas, it can be difficult to determine how to get started. Mobile operators are huge organizations managing multiple initiatives and projects as they work towards strategic goals. Analytics can provide tremendous insight, but many companies are unsure where to start. Here are a few examples of the vast list of “Pipe Data” use cases:
Injecting Intelligence into the Design Process
An in-depth assessment of customer behaviors provides a smarter start to any design project. Consider the operator looking to leverage Voice over LTE (VoLTE) to offer new communications options. Knowing which features customers prefer, which options are trending, which applications are most popular and how behaviors change by device enables developers to design a more viable offering. Analyzing this data against Quality of Experience metrics will quickly show how the solution should be enhanced to improve performance from the user’s perspective.
Being able to closely predict customer behaviors and preferences – both from the start of a project and continuously throughout the development process – will ensure that mobile operators are optimizing their efforts in a way that most benefits users and effectively outpaces competitive offerings.
Implementing a Proactive Assurance Program
Network Operations teams are responsible for maintaining 99.999% service availability. Applying predictive assurance algorithms, operators can proactively and automatically scan the entire environment for anomalies that indicate an impending issue. Not only do these operators enjoy the benefits of an “early detection system,” they also receive root-cause information. For example, instead of seeing a red light somewhere in the network, an operator would receive a notification saying that the S-CSCF cluster that serves the Southeast is trending towards failure. When skilled personnel are able to start from an intelligent, informed position, issues can be resolved much faster.
Improving Service for Key Accounts
Ultimately, every subscriber’s experience is affected by bandwidth availability. Operators need to ensure that high-value accounts and corporate customers are getting the service they need while protecting against users who are hogging resources in a way that degrades performance for others. With an in-depth analysis of multiple quality and bandwidth metrics – by customer and by application – operators can carefully balance these two objectives.
Pinpointing Infrastructure Investments
More than just a geographic usage report, Pipe Data offers a wealth of intelligence on growth areas that mobile operators can use in the planning process to strategically improve performance and increase ROI. A complex analysis of preferred access methods (WiFi, LTE, broadband); devices (iPhone, Samsung, Windows); services (voice, video, data); applications (social, gaming, productivity); and/or user types (corporate, heavy, shared) not only enables operators to better determine where to deploy the next LTE or WiFi hotspot, but also ensures that individual platforms are configured for optimal performance.
Creating Revenue Opportunities
Operators can use Big Data to identify new ways to strategically increase revenue. Consider the set of Bronze Plan subscribers that are using 90 percent of their data package to stream movies. Based on this knowledge, operators could, for example, develop a service mechanism that would display a “pop up” when one of these customers starts a movie. The pop-up would mention that if the user wanted to pay an additional fee, that movie – or all NetFlix movies – could be displayed in HD. This type of analytics will reveal many similar opportunities.
Profiting from OTT Traffic
People who refer to mobile networks as dumb pipes tend to cite erosion of profits due to Over the Top (OTT) applications. Big Data can help operators combat this issue.
Armed with a detailed understanding of which applications are most popular, how much bandwidth they consume and the Quality of Experience provided, operators can begin to control the situation. Using analytics to predict consumer behavior is one of the best ways to determine which branded services will provide the greatest value to consumers. This analysis can also reveal how operators can fully monetize the traffic these applications generate. In many cases, the application providers themselves may pay to ensure their valued users receive the speed and quality they need to ensure a great experience.
Extracting the Wisdom
Many operators still view Big Data solutions as ancillary to core systems. They are often cut from the budget before their benefits can be realized.
Going forward, these tools will move from being “nice to haves” to becoming essential to an operator’s ability to outpace competitors. Employees will lead with intelligence rather than use data posthumously to justify their decisions. Big Data accessible by all opens up an endless set of possibilities as operators strive to maintain and increase revenues in today’s competitive landscape.
To get started, find a partner that can help you understand what you want to achieve. Together, you can then dive into all of your data – examine it, characterize it, correlate it – to determine how to best use it. By leveraging this powerful and strategic asset, operators can drive innovation, stifle churn and preemptively ensure optimal network performance. It will make every employee’s decision more effective – from those as simple as determining which WebRTC vendor’s product will integrate best with the existing infrastructure to more complex questions such as where new pricing structures will yield the highest revenue per cost ratios.
Today, the smartest operators are not simply transporting network data – they are profiting from it.