Gartner estimates that the amount of data that companies collect, store, and analyze is growing at a rate of 40 percent per year. For companies, it can be all too common to get caught up in the sheer volume of data, but the variety is equally—if not more—important than the magnitude. This was one of the key themes of the Gartner Customer 360 Summit in San Diego in May.
With big data expected to drive $232 billion in IT spending through 2016, Gartner expects more companies to begin moving from experimental stages to harnessing insights from big data across their sales, marketing, and customer service departments.
Of those, customer service is the most prominent. In fact, it ranked at the top of the list of factors driving innovation and IT plans and operations this year, according to Gartner's CIO Survey 2013.
Despite this, session after session at the conference pointed to the many struggles companies face when it comes to the bare basics of trying to optimize marketing and sales processes by tapping into big data analysis. Customer service, obtaining full visibility of their customers, and being consistent with customer support across the various stages of enterprise workflows are still among companies' top challenges.
Companies are still in the very early stages of thinking about big data under the guise of customer support. At present, only 2 percent to 3 percent of organizations have a dedicated customer service executive in charge of running big data analysis and business intelligence efforts, noted Michael Maoz, a Gartner research vice president and distinguished analyst.
Additionally, about 54 percent of companies identified data mining and analysis as the top big data challenge; another 28 percent need ways to tie big data insights into marketing efforts.
To provide positive multichannel customer experiences, Gartner says organizations must understand that big data isn't owned by any one department in the enterprise.
"There is a lot of data that doesn't fit into a neat column," Maoz said. "The big data challenge is 'How do I tag [or categorize] it?' and 'How do I codify it?'"
That's an issue that plagues companies ultimately looking to apply data insights to real business outcomes, such as increasing sales on an e-commerce site by factoring in social media listening, communities, recommendations, fluctuations in pricing, and past purchase transactions.
Companies can apply big data to their own customer experience strategy by breaking it down into digestible parts and functions, such as video, purchase histories, text, location, speech, and social media, noted Gareth Herschel, a research director at Gartner. "You don't want to have a conversation about big data. You want to have a conversation about what information you have and what you can do with it," he said.
And then those companies will need to begin moving to a model where customer experience or support services capture, analyze, and communicate the voice of the customer to marketing to drive personalized and real-time targeting.