Companies who want to have continued growth understand a key component of their success will occur when they are able to personalize their customer’s experience, rather than a one-size-fits-all approach. Not only is the personal approach ultimately more efficient for organizations, it also helps increase customer satisfaction, which in turn leads to more growth.
One company, Transamerica, decided to harness big data concepts in order to provide the best possible personal service to its 27 million customer base. Transamerica pulled in data from over 40 sources, including social media, third-party data, customer voice response systems and all its investment, retirement and insurance data sources. By using big data analytics and machine learning concepts, Transamerica was able to identify new data patterns and insights in order to quickly and efficiently develop, test and deploy its predictive models. Now building models takes hours instead of days, allowing for fewer processing cycles and thereby reduced infrastructure demands, while at the same time increasing the personal experience for its customer base.
So what are some of the tools that Transamerica used to accomplish its goals? Transamerica takes advantage of Hadoop, part of the open-source Apache project. By using a Hadoop-based data lake along with a host of other tools, Transamerica found it was able to store vast amounts of data in their distributed computing environment. Of course, security risks are always a factor when dealing with large stores of potentially personal data, so Transamerica’s entire platform was designed in such a way as to maximize appropriate use of data and adherence to legal and regulatory obligations, while minimizing security risks.
Want to know more about how Transamerica and its customers win big with big data analytics? Click here.