With today’s enterprise software you no longer have to take a shot in the dark at decision making. Regardless of your organization’s size, industry, or the
|Scooped by Tony Agresta|
I would expect predictive analytics technology to surge in growth, especially with the deluge of data arriving every day. We are well beyond the early days when direct marketing pioneers applied predictive models to forecast response or performance (although that still happens more often than you think!). Today, models can take advantage of more independent attributes than ever before – including structured and unstructured data In turn, the predictive precision of the models increases. There are more than a few ways to apply the results. The obvious one is applying the scoring algorithms to new sets of data. But don't lose sight of the fact that model scores can also be used as filters in queries to segment and report on your big data. They can also be used as attributes in link analysis graphs designed to pinpoint fraud, cyber breaches, and networks of frequent buyers. Imagine a network graph where links between people are scaled based on their predicted spend or the number of products they will buy during the holiday season. It would easy to identify clusters of loyal customers which you could then study in more detail. When coupled with other characteristics and contact info, targeting becomes precise and the meaning behind your big data becomes obvious.