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The Future of Predictive Analytics For Marketing

Why Marketers are using Predictive Analytics

Predictive Analytics Makes You a Better, Smarter Marketer

Predictive analytics is the branch of advanced analytics that uses myriad techniques such as data mining, statistics, modeling, and machine learning to analyze current data and make predictions about the future.  In spite of its rising popularity, predictive analytics is still in its infancy, and today, the most common use cases are customer acquisition, cross-sell/upsell, and protection against customer churn.

As with any new technology, companies have been struggling with how to operationalize the output of these models. To some, it seems like just another dataset, when in fact, the intelligence that results from predictive analytics is based on advanced techniques that are quite sophisticated in their ability to ingest and filter data. In an attempt to operationalize the data, many companies are taking this highly sophisticated output and plugging it into 15-year-old automation systems.  Is it any wonder they aren’t seeing the value inherent in this data?

At MRP, we believe predictive analytics will migrate away from this batch approach of processing data, and move toward a more programmatic approach that can be applied across all stages of the customer’s buyer journey, and across all tactics, from display advertising to outbound sales.

 

At MRP, we believe predictive analytics will migrate away from this batch approach of processing data, and move toward a more programmatic approach that can be applied across all stages of the customer’s buyer journey, and across all tactics, from display advertising to outbound sales.

James Regan, CMO

And this will be possible because of machine learning.  The basic premise of machine learning is that it uses feedback to continually improve its output, and well, to get smarter!  The machine learning algorithm sits on top of the predictive intelligence input that comes from first, second and third party data.  In addition, the results of programs being executed are also part of that feedback loop. That means that every email you deliver, every piece of direct mail you send, and every customer interaction your sales reps have – positive or negative — provides input back into the algorithm, strengthening and improving every subsequent prediction.

This is all possible and happening now.  But we can see the day when machine learning will be advanced enough to determine what types of marketing tactics we should use, what content we should deliver, and when we should deliver it.  We can see the day when you select the segments you want to target, apply a budget amount to that segment, and machine learning allocates those dollars appropriately, based on the past experience of campaign success and conversion rates.  Minimal human intervention required!

Will machine learning ever replace humans? We can’t see that far into the future, but what we do believe is that it will remove a lot of the grunt work, manual labor, and frustrations marketers deal with on a daily basis.  In the short term, machine learning offers unparalleled advancements in the way you deliver results for your customers

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