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Predictive Analytics uses data to predict future trends and patterns. Predictive analytics software looks at past and present behavioral patterns and uses them to choose a future course of action. What used to be the realm of mathematicians is now relevant to business due to the massive amounts of data now available, better technology, and various software platforms to extract and analyze useful information.
The methodology begins with mining data, which can include what customers buy or have bought, and customer demographics including gender, income, age, and similar. By using statistical algorithms, you can then attempt to predict the likelihood of a future purchase, uncover potential problems in your marketing strategy, create a more targeted marketing strategy, and find opportunities for future campaign implementation. Some applications for predictive analysis are direct marketing, resource management, risk/benefit scenarios, customer relationship management, customer lifetime value, cross sales, and cybersecurity. Examples of predictive analytics software include SAP InfiniteInsight, IBM SPSS, and SAS Predictive Analytics. Because predictive analytics relies on past behaviors and current information, it must make assumptions for the future, which always involves an element of risk as changes in these patterns can occur.
Once you have the data, understand it, and can apply it to your business, predictive analytics can be an interesting and powerful tool in your arsenal.
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