Marketing Machines — Possible or Pipedream?
True data-driven marketing is still “just a dream” for many marketers, rather than a reality. Under this vision, systems data-mine autonomously, and present fresh actionable insights at your desktop in the morning.
For about 99 percent of marketers, this may sound too good to be true — and in all candor, it usually is.
But it is important to know and recognize that the intelligent application of mathematics and statistics, and the creation of purpose-specific algorithms, have been quietly creating value for years now. Yet the typical marketer still struggles to find enough time to get the mail out, or execute well-thought-out website marketing experiments against a control. (see “Analytics Isn’t Reporting”)
So there have never been more skeptics of the legitimate power of the intelligent application of data, even as the C-suite expectations of a data strategy that creates competitive advantage grows. Sound like your experience, industry or career? Sure it does.
But as investment continues to grind higher and competition grows, progress continues to be made.
The 'Amazon' of Data, Is of Course, Amazon.
You may know that Amazon.com elected to release to the public some technology it uses internally in making recommendations and determining what you’d be likely to buy and when. Amazon took the same tool-set it uses and published it on Amazon Web Services. “Pretty neat” you might say …
Because we get so many questions about how Amazon does it, and how all of this actually works, we’ll break down the AWS Machine Learning and Prediction tool-set so that qualified organizations have an idea of what’s possible.
For the purposes of this article, a “qualified organization” is one that has development talent, experience with data and at least a basic working knowledge of statistical methods. Of course, experience developing models is very helpful, as well.