In the mid-1990s, Target was a discount superstore behemoth. The retailer had set itself apart from chief rival Walmart with a focus on more upscale but wallet-friendly fashion and lifestyle lines, spurring double-digit growth by double-digits each year for more than a decade. That fruitful streak came to an abrupt halt with the United States financial crash in the fall of 2008. Target was hit hard—much harder, in fact, than Walmart. Five years later, the company was still struggling. With more than 1,800 stores and a relatively new e-commerce site, Target was collecting reams of data about its online customers—products purchased, browsing habits, items abandoned in shopping carts—,yet it wasn’t fully leveraging all that information. The company began to see this huge pile of e-commerce data as the needle-in-a-haystack key to driving higher sales, says Harvard Business School Professor Srikant M. Datar in a recent case study, Data Science at Target, co-written with research associate Caitlin N. Bowler. Read more at Forbes.