Predictive analytics has hit its stride now that companies can use Web log data to predict how customers will react to advertising or special offers on the Web. But according to Dean Abbott, president of Abbott Analytics, it’s been a change in thinking and not in technology that has led the industry to new heights. Companies have been collecting the data for years, but now they know how to use it.
That doesn’t mean that increased computing power won’t help, he said; right now, a machine learning program must figure out what offer or ad is the right one to display in a matter of microseconds so it will reach the customer while it’s still relevant. As computing gets faster and faster, the machine can make faster decisions.
Depending on the case, Web analytics can work on smaller data sets too, Abbott said.
In this interview with Data Informed Staff Writer Ian B. Murphy, Abbott discusses how companies are getting value from their real time web analytics now, what has happened in the past to make it possible, and where the industry is going. (Podcast running time: 16:02.)
Abbott is also the chief scientist to a startup company, Smarter Remarketer, and has been a frequent guest speaker at conferences on predictive analytics.
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