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Predictive Analytics: Not Just for Blue Sky Projects, But can Successfully Impact Daily Business Problems Too
Predictive Analytics is the combination of big data, analytics and forecasting algorithms. The algorithms make predictions based on models that use real-time, historical and third-party information. The predictions help businesses more accurately plan for business conditions, consumer sentiment, and market opportunities.
A report by MarketsAndMarkets estimates that the global predictive analytics market is growing at the rate of 27.4 percent annually and will exceed $9.2 billion by 2020.
The Forrester Wave research report found that “big data, gobs of compute power, and modern tools are making predictive models more efficient, accurate and accessible to enterprises. Why do it? Because enterprises that predict will win, retain and serve customers better than those that don’t.”
Mike Gualtieri, a research analyst with Forrester Research, said that “there are hundreds, if not thousands, of opportunities to use machine learning models in business processes and customer experiences. This is not day one, but it is still only day 2. There is tremendous opportunity today, but most enterprises struggle about how to think about AI. They are thinking too big. Successful machine learning models is about predicting one simple thing that can have a big impact on the business, such as the next best product to recommend for an individual customer.”
