We depend on telecoms or communications service providers (CSP) in our day-to-day lives not only to keep in contact with one another but also to keep our businesses going. Connectivity has become a modern day essential, however, any bottleneck in services can cause customers to switch providers.To reduce churn, new technologies leveraging big data can help CSPs differentiate from the competition and deliver a high level of customer service.
When you consider how many devices each individual might own and, in turn, use to interact with a CSP, you begin to appreciate the scale and speed of providing a personalized level of customer service across all devices and individuals. The explosive growth of smart phones is driving a huge expansion in the volume, frequency and complexity of data travelling across telecom networks. While CSPs have always collected voice data, today’s data is much more complex and includes photos, streaming video and music, location data, social media, text and email messages, web browsing, and more. Combine this with the data proliferation generated by a myriad of devices to support the Internet of Things, it becomes very clear that CSPs would benefit from game-changing technology to quickly manage and analyse big data. This technology would enable valuable insights from customer behaviour–that can in turn fuel improvements in customer service.
Traditional storage and analytics solutions cannot adequately manage the expanding, diverse volume of data generated today. Arguably, the game changer to manage big data is an open source technology called Apache Hadoop. In practical terms, how do telecom service providers build an environment based on Hadoop where they can take advantage of all their data and integrate the insights immediately back into their business?
Firstly, the data needs to be stored and managed appropriately so that applications can yield real insights. MapR Technologies offers a unique carrier-grade Hadoop distribution that can integrate into existing data flows, while taking advantage of the benefits offered by high performance parallel computing. By utilising parallel computing and effectively scaling horizontally on commodity hardware, there are significant speed improvements as well as cost reductions both in terms of storage required and subsequent computing costs.
In adopting an infrastructure like Hadoop, organisations are able to effectively create data lakes where information of all formats, including structured and unstructured data, and whether online or archived, can be stored. When you consider that a customer may have been with a particular provider across both wireless and wireline divisions for numerous years across multiple devices and contracts, being able to store and quickly access all that data requires a comprehensive infrastructure.
By implementing such a big data platform, a CSP can make better use of the vast quantity of data it is processing in real time on a daily basis. Being able to use predictive analytics and process multiple types of data in context will help CSPs develop new insights about their customers, deliver relevant location-based services and targeted promotions, and help to manage networks more efficiently for better performance. They can also protect and better serve their customers by proactively detecting fraudulent activities. Hadoop can be leveraged to analyze usage data, location-specific data and customer account data in real time to model baseline “normal” behavior.
Shortening the time-to-act on big data can significantly improve customer service provided by CSPs. The challenge for providers is to ensure they have the right infrastructure and applications in place to deliver the benefits to customers well into the future.
By Sameer Nori
Sameer Nori is Senior Product Marketing Manager at MapR Technologies with responsibility for solutions and industry marketing. He has 10+ years of experience in the technology industry in marketing, pre-sales and consulting with domain experience in the business intelligence, analytics and big data markets. Some of the companies he has worked at include SAP Business Objects, MicroStrategy and Jaspersoft.
