Why Telcos Can No Longer Rely on Traditional Machine Data Analytics to Deliver High Quality Service

May 19, 2014
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ImageIf you’re a telecom company, when a customer loses a call or can’t make one at all, the ramifications can be significant – lost business, compromised safety, foiled plans and general inconvenience.

ImageIf you’re a telecom company, when a customer loses a call or can’t make one at all, the ramifications can be significant – lost business, compromised safety, foiled plans and general inconvenience. When you consider that your customers are sending and receiving hundreds of thousands of calls and text messages every second, the need for real-time visibility is clear and significant. The ability to amass and correlate streaming data in real-time around a customer’s specific location, cell site performance, and call failure rates and prevents a momentary glitch from becoming a large-scale event. It also provides you with a huge opportunity to capitalize on this real-time data to engage in situational, 1:1 marketing.

Traditional analytics tools for machine data do a great job of collecting and warehousing data for analysis. You can glean insight on patterns and trends, evaluate program performance and pinpoint inefficiencies – after the fact.  For some industries this level of monitoring and reporting suffices.  If, however, you’re running a telecom company, you don’t have the luxury of sitting on operational data for days, hours or even minutes. 

Constant connectivity is critically important to your customers and you need to be able to identify issues and exceptions before they impact the customer experience. If you’re not able to keep up with what’s happening with your networks in real-time down to the actual second of occurrence, your service levels and customer satisfaction will be significantly compromised. Traditional machine data analysis tools are not cut out to handle live streaming data. What you need is a solution that will help you analyze and immediately act on insights gleaned from streaming data.

Using streaming Big Data analytics to identify and track VIP and high-value account customers empowers you to monitor and prioritize issues for these customers by triggering alerts when call failure thresholds are exceeded. This ensures that you’re focusing your resources where it matters most and it helps you monetize better service and improve customer retention.

You can also leverage streaming Big Data analytics to offer your customers much more targeted marketing offers, based on where a specific customer has recently been, where they are now and where they are going – a feat that traditional machine data analytics tools can’t accomplish.

With hundreds of thousands of interactions with your service occurring every second, there’s no time to waste.  Streaming Big Data analytics ensures that you deliver the constant connectivity that your customers deserve and that you have the opportunity to monetize the wealth of real-time information at your disposal.

Read this White Paper to learn how CSPs can benefit from streaming data analytics

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