Predictive Analytics uses past data, current data, demographics information and other relevant data, to predict future events. In business applications, events could either be discrete (e.g., whether a customer will respond to a product offering or not, whether she will churn and move to another provider or not,…) or continuous (e.g., the donation amount for a charity organization, the amount of money spent on purchasing from a catalog,…). Since events cannot be forecasted with certainty, prediction results are often given in in probabilistic terms, for example the probability that a customer will respond to a new product offering, the expected donation amount to a charity, and so on.
Predictive Analytics encompasses a variety of techniques from statistics, machine learning, AI, data mining, optimization and others to analyze the relevant data in order to predict the future events. Applications of predictive analytics are all over the place, including targeting, churning, fraud detection, user experience analysis, risk analysis, and many others.
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