Predictive Marketing is a data-driven way to approach marketing. It is used, much like its name implies, to predict customer preferences and customer engagement. It is a science that uses a variety of statistical techniques to help marketers get the right message to the right audience at the right time.

This is the conclusion to my predictive marketing blog post series, and the focus here is on the types of tools that are available to marketers.

New technologies are now available to do the data science piece of predictive marketing 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 improve outcomes.

First, let’s start out with Customer Relationship Management (CRM) systems. Most CRM vendors have propensity models that are used to predict who the most-likely-to-buy repeat customers are. By identifying this group, marketers can design the right promotion for this ready-to-buy demographic. Check to see if your CRM has this capability and, if you are not using it, add it to your future initiatives. These customers are ready to buy. You just need to have the right messaging.

Next, are Campaign Management technology products. These products help automate marketing campaigns across multiple channels including; email campaigns, web campaigns, social campaigns, and mobile campaigns. Many of these tools started in the email channel automating triggered email campaigns based on demographics, buying, and browsing behavior. They enable brands to scale with minimal effort to deliver the personalized experience consumers want. Many of these tools are now adding more context to their behavioral programs by including engagement level and purchase probability. In addition, by adding store data and catalog data, they are able to show the full impact of your marketing campaigns.

And finally, we get to Data Management Platforms. DMPs provide analysis about the audience segments of website visitors by layering first-party data with third-party cookie-based data and can find audiences that look-a-like and behave-a-like your customers. This analysis is used to target specific audiences with display, search, video, and social prospecting campaigns. There is a convergence of DMP and Predictive Marketing Platforms that will enhance not only finding the look-a-likes and behaves-a-likes but who in those audiences are most-likely-to-buy.

A whole new set of Predictive Analytics Tools/Business Intelligence Tools are emerging and are getting closer to being your “Data Scientist in a Box.” These new tools have much more intuitive interfaces and typically provide dashboards to visually show how the current business is doing, provide business intelligence analytics capability to do deeper dives into the data to optimize current performance, and provide predictive models to predict future performance. These are very powerful tools and require skilled data analysts that understand your business to leverage their capabilities fully.

If you haven’t gotten started in investing in predictive marketing, now is the time. Many companies, perhaps your competitors, are investing and gaining a significant competitive advantage from their early experiments. Remember, the big companies like Amazon, Walmart, and Ticketmaster were early adopters and have proven that Predictive Analytics has the potential to yield enormous value and return.