Predictive modeling helps companies optimize their internal operations, improve customer satisfaction, manage budgets, identify new markets and anticipate the impact of external events, among other uses. Moreover, as the technology becomes more accurate, easier to use and cheaper, the benefits of this type of analytics will continue to increase.
What is predictive modeling?
Predictive modeling, or predictive analytics, uses standard statistical techniques, machine learning, deep learning and other types of artificial intelligence technologies to predict future outcomes based on current and past data. It builds on descriptive analytics, which describes what happened, and is the precursor to prescriptive analytics, analyzes why something happened or will happen and what to do next.
One of the best-known and oldest examples of predictive models is weather forecasting. Predictive models are also used to create election forecasts, spread of diseases or estimate the effects of climate change.
But there are also plenty of enterprise applications of predictive analytics. Here are the top seven specific business use cases for predictive analytics today.
