Big Data Analytics for Telecom Operators: Use Cases and Benefits

Today’s telecommunications operators are soon aware if they are failing to keep their customers happy, live up to their expectations and meet their demands. They simply jump ship and sign up with the competition.

But the drive to win new customers and keep them on board (the former being more expensive than the latter) is only one way in which telcos can leverage the masses of information to which they have access. Big data acquisition, management and interrogation are all now sophisticated processes which feed into profitable analytics for telecom operators.

The sources of data for telcos are now more varied than ever before. They include social media, the ways in which customers leave feedback and behave, and even information derived from device location and use. There’s always the risk that, with so much information flowing into the organization, an operator might end up with a data swamp rather than the desired data lake. Thus, analytics for telecom companies can be deployed to derive benefits in several use cases – all of which can, in some way, enhance customer experience and reduce churn.

Telcos deploying advanced big data analytics products can gain a great deal of information about what their customers want, which in turn lets them target offers precisely and match KPIs to individual requirements. For example, customers who predominantly use location services, basic call and text facilities, email, messaging and standard web browsing are likely to have different demands to those who are intensive media consumers. The right analytics solution can help telcos differentiate between these customers.

Feedback analysis is another area in which analytics for telecom operators can improve performance. Here, it’s possible to segment customers extremely precisely, so the operator understands who are most valuable, and why. One segment might be prone to leaving negative feedback via various channels based on short-term emotions; another might never leave any feedback at all; yet another makes purchases defined by easily identifiable patterns; and another has been extremely loyal… all of this is valuable information for operators, as they can deploy automated big data analytics to ensure an appropriate and profitable relationship with each of the above sectors (and more).

And it goes further. Big data analytics for telecom service providers can show operators when and how their customers react to offers. For example, if there’s a group that responds positively on Friday evening – perhaps after a tough working week when they wish to treat themselves – this information can be discovered and acted upon. As another example, automated big data analytics can prevent sales calls being made to customers who don’t respond well to this kind of approach; this may sound like something very simple, but customers can switch providers in a moment of irritation at one unsolicited phone call too many…

Taking into consideration the bigger picture, big data analytics lets telcos understand how their networks are being used as a whole, based on geography and time, or even specific events such as streamed sports competitions or concerts. In this way, network services can be automatically optimized – which improves customer experience by ensuring there’s never a lack of service at peak demand times. Remember the “network busy” messages at two minutes to midnight on New Year’s Eve? That should never happen with automated network data analytics. And, of course, knowing what’s “normal” for a device, SIM or the network as a whole means that algorithms can be deployed to detect anomalies and enhance security for all.

All of which feeds into the ultimate goal of keeping the customers happy – which should be the goal of every telco that intends to make a profit and keep operating.

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