Can Big Data improve CSP’s margins?


The customer is king (or queen) in voice and data networking, and has been for some time. Nowadays, when customers say “jump!”, network providers answer “how high?” New technologies, liberalization of voice and data markets, and a host of startups mean that communication service providers (CSPs) are under constant pressure to produce new, even more enticing offers of service and offer even better customer experiences. A paper written by Analysys Mason on behalf of Openet examines the roll-out of big data analytics solutions, including the use of data preparation solutions, in supporting Customer Experience Management (CEM) processes in CSPs.

Benefits of Good CEM

However, there is a silver lining for communications service providers. They may no longer have monopolies, but they have access to more data than ever before about what really counts for their customers. Once they know this, they can adjust their marketing and offering accordingly and realize a number of important advantages:

  • Retain customers. The bigger the lifetime value of a customer to a provider, the smaller by proportion the effort and expense of acquiring that customer. In other words, get customers to stick around for longer.
  • Increase consumption. Services that meet customer needs and expectations sell better. For network providers offering paying upgrades to services, happy customers are vital.
  • Sell additional services. Beside upselling to get customers to use more of a service (increase consumption), there is also a correlation between a good experience, as perceived by customers, and the purchase by customers of additional services and solutions.
  • Cost reduction. Not only can customer acquisition and marketing costs be reduced (good customer experience encourages word-of-mouth sales), but so can the costs of customer care and of hiring new staff to replace the old ones who left because of irate customers.

Big Data Holds the Key

The next question is how to collect and use the data to generate the insights to improve customer experience management and thus gain these advantages. There is no shortage of data anymore. Databases can hold large amounts of structured data, operational systems add considerably more through their system logs, and email systems and social networks can contribute huge amounts of unstructured data.

All of this amounts to big data, which needs different solutions for processing, compared to traditional datasets. Multiple, disparate datasets must be stored, normalized (made compatible in structure with one another), and adjusted to remove inconsistencies or multiple instances of the same data. They must then be analyzed, using algorithms that may also be highly complex. In addition, different approaches to measuring the quality of customer experience may have to be evaluated: for example, the Net Promoter Score (NPS), individual system KPIs (key performance indicators), and the Customer Experience Index (CEI).

Open Source Technology and CEM Project Priorities

Solutions exist in the shape of open source software applications that can help drive down the costs of processing big data. Frameworks are often based on Hadoop for handling and processing very large data files by portioning out the processing to several standard or commodity computers, and recombining the individual results afterwards. Data storage costs continue to decrease, while capacities increase, although data volumes must be correctly managed and reduced where appropriate to contain these costs.

New big data technology is therefore bringing down the costs of good customer experience management. However, telecoms service providers will need to be careful they do not get sucked into huge projects aiming to analyze everything under the sun. A more practical approach yielding results earlier is to select specific aspects of the customer experience to extract insights that lead to the most positive financial impact. For many service providers, the priority is to reduce customer churn. They would then select their datasets on this basis and focus on data preparation and analysis in this area.

Tying CEM Automatically to New Networks

As network technologies themselves develop, communications service providers will then have new possibilities to dynamically adjust their levels of service according to the results of the big data analytics. Next generation wireless networks for instance will have the planned ability to adjust throughput and latency in real time. So may other NFV (network function virtualization) and SDN (software defined networking) installations.  Big data analytics systems could then be connected to drive mobile network control systems to automatically and immediately tweak the quality of service, according to the customer sentiment and levels of satisfaction being picked up from the big data available.

Maravedis and 4G 360 provide leading market research and content marketing for the wireless industry.


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Mr. Fellah, is a Senior Analyst and founder of Maravedis with 20-year experience in the wireless industry. He authored various landmark reports on Wi-Fi, LTE, 4G and technology trends in various industries including retail, restaurant and hospitality. He is regularly asked to speak at leading wireless and marketing events and to contribute to various influential portals and magazines such as RCR Wireless, 4G 360, Rethink Wireless, The Mobile Network, Telecom Reseller to name a few. He is a Certified Wireless Network Administrator (CWNA) and Certified Wireless Technology Specialist (CWTS).


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