What happens when you combine big data with some big math? Good things, bad things and things we have yet to truly comprehend. Big Data is the most talked about, misunderstood and nebulously defined component of online marketing. Big data can mean anything from large scale consumer behavioral analysis to a relatively simple study of baseline intent analytics.
Big data has effectively replaced predictive modeling as a buzz phrase in the digital marketing universe. As is often the case, search marketers feel they are the center of said universe—and rightly so—since all the best things begin and end with understanding defined intent.
As we learned last week at SMX Advanced, analyzing data can do great things for you. You can monitor changes in Penguin or other Google updates; you can isolate trends in an attempt to garner shoppers who may have not even considered buying something in your category. On the downside, analyzing big data also has the all the trappings of analysis paralysis, quicksand or a little malady I like to call, “Let’s listen to the guy who used to work at Google because he must be a genius” syndrome. Technical capabilities considered it’s still a good idea to spend some time with good old human intuition.
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