Big Data

While the concept of using data to better market a product/service isn’t new, you may have noticed marketing pubs are writing more about “Big Data.” (Both AdWeek and AdAge have/are dedicating issues on the topic this year.) And many superstar e-brands (think Amazon and Google) base their entire marketing and sales strategies around Big Data. If a marketer’s challenge has always been “to figure out how to make the right offer to the right consumer via the right touch point, at exactly the right point in time,” then consider Big Data your golden ticket.

I’ve pulled together a few ‘case studies’…hopefully you find these examples as interesting as I did!

1.     A marketing executive at Google noticed that the paid links that showed up in search results were a different shade of blue on Google search than on Google’s e-mail software Gmail. The marketing director decided to test which shade of blue would maximize users’ click-through rate on the ads. His team tested 40 different shades, covering the entire spectrum of blue, on 1% of Google’s web pages and compared them to a control group. It found that users preferred a blue shade that had less green and more purple in it. The change was made across the board and Google netted an additional $200 million in revenues.

2.     Nike set up NikeID.com, which lets customers design their own footwear, clothing, and equipment. The concept lets Nike engage its customers directly and offer personalized, and often higher-margin, products; revenue from NikeID surpassed $120 million in 2011.Nike now uses customer data to sift through the billions of possible permutations and choices to analyze its customer base and provide the basis for its next product designs.

3.     McDonald’s now tracks customer interactions, in-store traffic, flow through its drive-through lanes, and ordering patterns, using point-of-sale data, video, and sensors. Based on this data, researchers model the impact of variations in menus, restaurant design, and training, among other things, on productivity and sales.

4.     When a customer rang the call center of a U.S. insurance company, the agent used to just see the caller’s history (i.e. tenure as a customer, wait time, outstanding claims). With big data, the company had developed a real-time sentiment analysis system to assess the emotional state of the caller based on voice and inflection data. The system then made recommendations for how to respond—for example, keeping to the facts of the case or mellowing the tone—so the agent could manage the conversation better. These insights were critical because part of the call center was in the Philippines, where cultural differences made it difficult to manage emotional conversations with American customers.The system helped improve customer retention rates by 20 percent.

Steve Lohr of the NY Times said: “What is Big Data? A meme and a marketing term, for sure, but also shorthand for advancing trends in technology that open the door to a new approach to understanding the world and making decisions.”