Defining Big Data in Telecom Applications

Logi Analytics

“Can you hear me now?” If you’ve watched television anytime in the last decade, you’ll likely recognize that catchphrase from the “Test Man” commercials Verizon ran constantly in the early 2000s. Today, communications service providers (CSPs) continue to throw money at advertising or any other method that gains them market share – and it isn’t cheap. In fact, telecoms spend hundreds of dollars to acquire just one new customer.

At the same time, many companies are losing their current customers to other providers; annual churn rates average between 10 and 67 percent, according to the Database Marketing Institute. And the reason people switch wireless providers isn’t necessarily cost – it’s service (or in this case, lack thereof).

The numbers don’t lie; in this economy, it pays more to keep customers than to poach them from competitors. Now, by leveraging the big data they generate every day, telecom companies are shifting focus from acquisition to retention. Using intuitive business intelligence (BI) applications and dashboards, CSPs are able to track their performance, improve their services, and ultimately find new ways to provide value to their customers.

Today’s Telecom Challenges

In the telecom industry, one of today’s greatest challenges is that providers have become “smart pipes” for an array of third-party apps that eat up bandwidth – FaceTime, WhatsApp, Pandora, and so on. By improving service, telecoms can begin to make themselves a more beneficial member of the chain.

But providing that great experience is about more than good coverage, call quality, and even customer service; today’s subscribers expect something extra. They want a high level of service across all the applications they use on their devices. These ancillary services add load to the networks, resulting in the poor experiences most customers have likely encountered – video re-buffering, voice quality degradation, and slow start times, to name a few.

Monitoring these services is essential to improving the customer experience, yet that presents another challenge. Because these elements are typically composed of multi-vendor solutions, it’s difficult for telecoms to gain visibility into the complete end-to-end service path. This “visibility gap” places the Quality of Service (QoS) at risk when issues arise. That’s because wireless companies have no control over how a third-party application might negatively affect the customer’s experience on their network.

A Data-Driven Solution

So, how do CSPs improve the overall experience to keep their customers satisfied? The obvious choice is to build out infrastructure – but that route costs billions of dollars, time, and resources. The smarter, more cost-effective way to improve all aspects of the telecom service chain is data monitoring.

There are lots of ways telecoms can use big data to enhance their business. Let’s focus on the two that will provide the greatest impact: monitoring quality of service for customer retention, and analyzing usage to develop value-added services.

Prioritizing High-Use Services

In order to offer better service and avoid the “smart pipe” phenomenon, telecoms can analyze data usage and prioritize specific services for their customers. This allows them to give more attention to the data/bandwidth quality of those services and proactively govern a customer’s experience listening to online radio or streaming video, for example.

BI dashboards enable telecoms to monitor Quality of Experience (QoE) metrics in near real-time. These dashboards offer a high-level view of QoE status levels by market using geomaps. For example, the color of the market coverage might change when it deviates from established thresholds for various service offerings. Each market area would also include a drilldown option to view the underlying QoE metrics for supported services.

A telecom dashboard will also show the details behind the service-level performance indicators. For instance, we can plot QoE metrics – such as blocked or dropped calls for voice services – and their correlated QoS values over time; consequently, the rate of change reveals emerging trends. Then, these plots can be compared to average and threshold levels for the appropriate metric.

Monitoring social media is another way to measure customer satisfaction and public sentiment. Here, too, BI dashboards can be used to mine content from blogs, news sources, and Twitter feeds.

Finding Up-Sell Opportunities

Another key way big data can save the day is by helping CSPs to determine what new services customers might want to add to their coverage. Through analysis of customer usage patterns, telecoms can come up with appealing “up-sell” opportunities and pricing structures.

Essentially, big data can help attract current customers in more targeted ways. For example, if a customer uses vast amounts of data to stream videos, you might offer them uninterrupted or guaranteed data connectivity for a slightly higher monthly fee. Or, you might find out what third-party apps customers are always using and come up with something better – for example, providing superior video conferencing services to FaceTime.

Big Data = Customer Retention

By leveraging big data, telecoms can retain their customers and increase the bottom line. If these companies optimize the customer experience to alleviate pain points – and at the same time, justify their pricing – customers are more likely to remain loyal. What’s more, CSPs can further bring in revenue by offering personalized add-on services their customers will get excited about. Either way, data monitoring is an especially cost-efficient way for telecoms to make themselves a valuable member of the service chain.