Advanced analytics platforms such as Hadoop have been gaining traction within various industries for several years now. More organizations are coming to realize that they can utilize their massive volumes of data to glean actionable insights into their operations as well as identify opportunities for improvement. Big data has been utilized for a broad range of applications, but many companies in the mobile and software sectors have found they can get the most immediate impact by focusing on their customer engagement practices.
Customer satisfaction has long been a concern in the telecommunications industry, but companies have recently found that they can better engage their subscribers by utilizing various channels beyond customer care phone lines. According to an August 2013 J.D. Power report, wireless carrier customers take three primary paths to receive support: telephone, walk-in and online. Those three sources of customer information represent a wealth of data that telecoms can leverage to better understand customer needs and more effectively and efficiently market new services and products.
Wringing value out of all data
The main issue that companies looking to get the most out of data analytics may run into is that not all data is created equal. In those three cited sources of information, telecoms will have to capture data from phone conversations, records entered into a retail store computer and online transmissions that may include instant messaging sessions. This means that carriers will be faced with a stockpile of both structured and unstructured data that can be difficult to drill into and make sense of. With Hadoop, users can gather and store any type of data for later use. By simplifying this process, Hadoop enables mobile operators as well as software companies to broaden the scope of their data analytics ventures and utilize every piece of information for more accurate insights.
Address capacity issues
Another concern that may arise is an organization's storage capacity limitations. For instance, China Mobile Guangdong – a subsidiary of China Mobile – was having difficulty getting more productivity out of its relational database management system, resulting in an inability to adequately meet the needs of customers. China Mobile Guangdong has experienced a surge in subscription rates in recent years as the Chinese wireless market continues to grow at a fast rate. The company's legacy RDBMS was incapable of handling this additional workload, impeding customer engagement efforts.
According to Intel, China Mobile Guangdong deployed Apache Hadoop to utilize the platform's scalability and eliminate its capacity concerns. Because Hadoop runs on a series of clusters and nodes that can be easily customized and scaled up or down as needed, it provides far more flexibility in terms of storage capacity than a traditional system. In this case, whenever a China Mobile Guangdong operator needs to expand the system's capacity, he or she can simply add more nodes to the framework. With this capability, the telecom can scale up to as many as several hundred million subscribers without investing in a costly and massive storage solution.
The wireless company used the Hadoop platform to recreate its billing system to not only identify and respond to customer complaints more effectively, but to also improve the subscriber experience. China Mobile Guangdong customers can now pay their bills online as well as view all call data records relating to their account going back six months.
"Our new billing statement inquiry system has delivered a low TCO, high expansion capability and high processing performance, thus laying a very solid foundation to enable China Mobile Guangdong to constantly improve its customer services in the context of high-volume businesses," said Tang Hui, project manager at China Mobile Guangdong. "The successful accomplishment of this new system will undoubtedly bring our service quality to a new level."
