The First Rule of Big Data
The amount of data that's being generated today is simply staggering. Thanks to the explosion in machine-to-machine (M2M) data, social, customer, and other data types, the amount of digital information created annually is expected to grow by a factor of 44 between 2009 and 2020, according to EMC. For business leaders that are struggling with how to get started with using Big Data, the $64,000 question is often "Which data should I be using?" A better question to ask which goes to the first rule of Big Data should be "What business problem are we trying to solve?" since this will guide business leaders to identify the right types of data to use.
A good rule of thumb for getting started with Big Data is launching a pilot project that's aimed at addressing a particular business challenge. This could involve analyzing customer sentiment to determine whether it can signal potential churn or analyzing the most common reasons customers are calling to speak to customer service agents to resolve a product issue and whether there might lower cost channels (chat, IVR) customers could be guided to that could help them find the answers they're seeking.
Some data sets will prove to be more valuable for tackling specific business challenges than others. But as Niren Sirohi, vice president of predictive analytics at Peppers & Rogers Group noted in a recent blog, it's useful for companies to blend unstructured data such as information that's generated through customer Twitter posts or recorded contact center calls with structured data such as customer transaction or behavioral data "to gain a more holistic view of your customer."
Big Data can seem overwhelming to many executives. But when you know what you're trying to accomplish through the use of data and analytics, it makes the process a whole lot easier.
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