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Predictive Analytics is a science that has been around for a long time, but you might not have realized it. For example, your credit score is calculated using predictive analytics. This algorithm, in short, is based on your past history and current debt. Thus creating a credit score that roughly predicts your level of credit risk.

Now, Predictive Analytics influences marketing and retailers. Amazon, Walmart, and TicketMaster were early adopters and have proven that predictive marketing yields enormous value and return.

So, what is Predictive Analytics? How does it impact marketing? Is it really a game changer? And how does a brand get started? Well, I will answer those questions in-depth in this four-part series.

Predictive Analytics truly is a science which leverages a variety of statistical techniques; such as data mining, pattern recognition, statistical modeling, and machine learning.

At a very high level, Predictive Marketing uses Predictive Analytics to:

  1. Deliver more relevant and cost effective customer experiences
  2. Select and deliver better product merchandising
  3. Find the best channels to reach potential customers
  4. Boost customer loyalty and revenue

The good news is that today’s marketers don’t have to hire a room full of data scientists to do predictive marketing. New technologies are now available to do the data science for you! These tools are becoming easier to deploy and more affordable. If you haven’t invested in these new technologies it is time to learn what they are and how they can improve your business.

Coming Up: My next post will highlight how to use predictive marketing to acquire, retain, and reengage customers. The third post will focus on use predictive analytics to improve product merchandising. The final post will summarize the types of tools that are out there for marketers to utilize.