Predictive analytics is the science of taking a wealth of data and applying a combination of algorithms and machine learning to make predictions about which future outcomes are most likely. Many technology companies are already adept at predicting the next product a consumer wants to buy and then serving up a recommendation. For instance, Amazon’s recommendation engine is estimated to generate more than one-third of its consumer purchases by using artificial intelligence to identify, rank and serve up the most appropriate product recommendations. Over the last few years, hospitality companies have begun to deploy predictive analytics to better anticipate and meet customer needs and preferences. For example, in 2013-14, the US economy-hotel chain Red Roof Inn used public weather and flight data to predict which customers would face flight cancellations. Based on the results of this predictive analysis, Red Roof Inn launched a targeted marketing campaign aimed at mobile-device users in the areas most likely to be affected by harsh weather. In those areas where the strategy was deployed, Red Roof Inn saw a significant increase in business. Similarly, the Hawaii Tourism Authority ran a “Discover Your Aloha” campaign that used facial recognition software to analyze travelers’ expressions via webcams as they viewed a video. The campaign then applied predictive analytics to generate a custom offer along with a booking link. Get the full story at McKinsey & Company