A recent blogpost by Barbara Thau on Forbes (http://onforb.es/YFHSsl) posits that predictive analytics can help retailers avoid a J.C. Penney-style meltdown by moving beyond costly (and potentially disastrous) “trial and error” methods to using data to help predict how customers will react to proposed changes. NFLshop.com, Perry Ellis, and Hickory Farms have all used predictive analytics to identify new target segments and increase sales.
This is an approach that readers of our blog will recognize; the use of all available customer interaction data as well as customer profiles and primary research is fast becoming the cornerstone of the modern marketing arsenal. Marketers are making smarter and, importantly, less risky business decisions by running data-based models and scenarios – even though these methods often entail considerable expense in data warehousing, analytics, modeling, metrics, data purchases, and business process changes, they are often far less expensive than making a disastrous mistake through blind “trial and error.” If only J.C. Penney had learned that lesson just a bit earlier.
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