The emerging science of Big Data Analytics has been a hot topic in the industry for several years but, until now, progress towards widespread utilisation of the insights it can reveal has been relatively slow. There are two primary reasons for this. First, while everyone knows that Big Data offers huge potential, the issue has been, where to start? With so much data available, it’s been hard to see the wood for the trees. Second, the ability to work with big data has been restricted to a few specialist data scientists.
This has changed. Today, Communications Service Providers (CSPs) are showing clear signs that Big Data strategies and plans have reached maturity by accelerating deployment of solutions that enable them to begin to capitalise on this rich resource. The difference driving this gathering momentum is that there are now clearly identifiable targets that enable a step-by-step approach to the implementation of Big Data strategies.
Many CSPs, for example, have chosen to focus on Subscriber Analytics as the first step in their Big Data strategies. This is because Subscriber Analytics is believed to offer the greatest potential to deliver rapid returns, enabling them to build better relationships with subscribers, among other benefits.
There’s a simple reason for this: a deep understanding of customer behaviour, while fundamental to business success, has traditionally been an expensive and imprecise discipline. Imprecise, because extrapolation from the few to the many is no guarantee of accuracy; and expensive, because efforts to obtain statistically significant data from which more accurate conclusions can be drawn, can be exceedingly costly.
While isolated data sets can deliver insight, conclusions that can be drawn may not be sufficiently representative. For CSPs, the ability to obtain accurate, timely insight into what customers actually do from a sufficiently broad sample base provides an unparalleled opportunity to not only provide better service and support, but also to reduce the costs of customer research. Big Data provides the constant flood of real-time, objective information about customer behaviour that makes this possible. The difficulty has, until now, been to make this information available to the many, not just data scientists.
Happily, there are now solutions like ones from Polystar that address this problem. A new class of advanced processing engines is available that sort information collected from the network and filters it so that it can be made relevant to different users. This pre-processing removes the pain from Big Data Analysis and delivers the right information in an accessible manner to people within the organisation. Smart solutions provide different views, so that, for example marketing teams can see the information they need, while customer services obtain a different view – and can interrogate the data with different queries and questions.
This simplification is critical. It democratises data and, for the first time, enables its potential to be realised. Data analytics is not longer a specialist discipline. Now, not only can anyone ask the right questions, but we can ensure the right people are able to discover the answers.
Meet Polystar at AfricaCom (Stand F14a) to explore how your company can benefit from a fast and efficient Customer Experience Management solution and get aggressive return on investment in a short time period.
This blog post was initially published on AfricaCom/Informa Blog
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