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Coca-Cola is The Beatles of Facebook. Actually, with more than double the fans of The Beatles, you might say Coca-Cola is the new black. But how did the cola giant garner more than 70 million fans? And how are they leveraging what they know about their total audience both online and off to sell more Coke and other Coca-Cola beverages? Big data, that’s how—very big data.
Known for its highly complex web of big data in the world of business intelligence, Coca-Cola collects data from a huge variety of sources to identify patterns. Those 70 million Facebook fans are the tip of the iceberg, and the new black is Coca-Cola’s Black Book model—the methodology used by the beverage mogul to procure and control big data from social networks, online sales, and point-of-sale locations like Target, Walmart, and even the corner liquor store. Putting this amount of data to work means implementing a level of analytics that can make good use of enormous amounts of raw data. It also means a keen ability to perceive what that data means for futures is the key to making that data work efficiently.
Storage of this data alone is a feat in itself. Coca-Cola amasses entire petabytes of information in a short time, and makes sense of them so they can make snap marketing decisions. For example, by seeing how they're trending on Twitter and layering that across how they're selling at grocery stores on the Fourth of July, Coca-Cola can decide whether or not to play more ads on television, promote more posts on Facebook, or where to ship more inventory quickly. In the blink of an eye, more Coke, Dasani water, Sprite, Powerade, Nestea, and Odwalla become available at retailers.
Take examples from contemporary culture. The gas stations, grocery stores, and other retailers close to Burning Man will more likely want to stock up on Odwalla and water during the days of the festival, while large retailers across the country will want to stock more Coke, Sprite, and Dasani during March Madness. Coca-Cola can use big data to see this, and use their massive infrastructure to get the process underway in the time it takes to send a text.
Perhaps more important than this year’s Burning Man and March Madness is what Coca-Cola learned using big data analysis and business intelligence from last year. What they know about sales from 2013 will shape decisions made for 2014, and when the averages taken from the past five years are compiled in their Black Book model, Coca-Cola can make even more accurate determinations about what they need to have in place across the entire planet in the coming year.
And then there’s that tip of the iceberg—Facebook. Using simple analysis of how many fans are “liking” and commenting on posts can be useful, but using this information based on real-time engagement will create even more return on investment. The best example of this is the 2012 Super Bowl which had 111.3 million viewers—engagement on social media for Coca-Cola was substantial, and helped the company gain powerful new information about how consumers see the brand and how they engage with it.
Other more predictable time-sensitive examples are important too. For example, reminding consumers that Coke is there during the Christmas holiday season, reminding Latinos that Inca Kola is around during Dia de Los Muertos, and reminding moms that Hi-C is around at the start of the school year are imperatives to sales based on online visibility.
Coca-Cola's Director of Business Growth Drivers in The Global Customer and Commercial Leadership department, Anthony J. van der Hoek, tells us, “I believe that it is this essential combination of people, process and technology change that will be crucial to everything we do in the future.” If the past two years are any indicator of how successful this combination of business intelligence variables are, Coca-Cola will remain the big data heavyweight in the foreseeable future.
Article written by Nathan Roberson of The Marketing Robot, Follow Nathan and his co-horts on Twitter @robthemarketer or add him to your circles on Google+
Business analytics dashboard in general terms can be elaborated as retrieving useful information or knowledge for further process of analyzing from various perspectives and summarizing in valuable information to be used for increasing revenue, cut cost, to gather competitive information on business or product.
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