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Crafting a Big Data Strategy for Customer Service
Focus on business outcomes driven by information and intelligence.
Posted May 3, 2013
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SAN DIEGO, CALIF.--Big data can transform a customer service organization, but companies still face a few key challenges in applying data insights to customer support practices.

 During Thursday's presentation of "What's the Big Deal with Big Data for Customer Service?" at the Gartner Customer 360 Summit here, Gartner analysts Gareth Herschel and Michael Maoz touched on some of the key issues companies come up against in priming their big data strategies for customer service.

"In your industry, you're being measured against what [companies like] Facebook and Google are doing, [both] companies that are good at gathering a lot of data and using it in support of the customer experience," Maoz said. According to recent Gartner statistics, 54 percent of companies hit roadblocks in data mining and analysis, while 28 percent want a way to tie data insights to marketing efforts.

Companies are wrestling with a high volume, variety, and velocity of data, but rather than trying to define what big data means for a particular organization, a digestible way to form an action plan is to break down the components of big data into actual business uses like video, speech, text, social media, and location. The key, Herschel noted, is to have a conversation about "what information you have and what you can do with it."

At present, only 2 or 3 percent of organizations have a customer service delegate who manages big data analysis or business intelligence within the department, according to Maoz, but this is expected to change as more companies tap into customer service data across social media, eBusiness, mobile, and other channels.

Although a big data customer service strategy will vary by the industry vertical, a company must decide how it will tag or categorize data, and answer the question, "How do I codify it?" Companies should determine what the business use case is for their big data strategy. Government, for example, may look at more transparency or process optimization. A retailer can tap into big data gathered from social networking sites and communities and use customer references or social recommendations in order to fuel more sales on the e-commerce site.


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