As big data's popularity dwindles from novelty to commonplace, the aftereffects of it are coming to the foreground.
We wouldn't quite say hidden aftereffects, but maybe underestimations would be a better word.
After all, data was intended to make the decision of buying a certain good or service easier for consumers, since, historically speaking, consumers hate choice. Yes, decision-making is an arduous process.
Data seemed to eliminate the hard stuff.
Based on new tracking methods, predictive modeling, and the like, we've been narrowing down what consumers like and dislike, what they are likely to buy, and when they are mostly likely to buy it.
Naturally, then, the items, sites, and services that miss the mark are discontinued amongst the data's consideration sets.
Why, then, are we surprised if data turns into a wave of discrimination claims? Imagine a McDonald's and Nordstrom both offer loyalty cards. Based on the data, one can safely assume that the customer profiles will be a tad different.
Just like we tell our students, discrimination doesn't always refer to being a bad thing. It's actually good for marketing.
Dwayne W. Waite Jr. is partner and principal at JDW: The Charlotte Agency, a marketing and advertising shop in Charlotte, NC. He enjoys consumer behavior, economics, and football.
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