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Predictive Analytics In BI: Foolproof Or Weak?

By SiliconIndia   |   Thursday, 10 May 2012, 06:27 Hrs
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Bangalore: Predictive Analytics has been used over the years to analyze consumer behavior. Every marketer wants to understand how a customer picks products.

An article mentioning predictive analysis used by Target Stores was published in the NY Times Magazine. Target had hired a statistician to look into consumer habits so that revenues could be multiplied. The company issued a unique code (known as the guest ID) to the customers whenever possible. A large quantity of data regarding the consumer and his/her shopping habits was linked to this ID. The analysts worked on this information and came up with a scheme targeted specifically at pregnant women and their spouses. The theory formed was that if they were shopping for baby products, giving them rewards on their guest id might induce them to get groceries and clothing as well.

This article however seems to suggest that retailers are far too focused on their appeal to pregnant women. There are no clear studies that suggest a significant increase in revenues due to the practices suggested by these predictive analyses.

The best example to counter the case for predictive analysis would be Netflix and its journey from a Wall Street sweetheart to Dot Com nightmare. Netflix’s downfall has been significantly documented. First, this video service alienated its subscribers by increasing monthly rental rates by 60%. Then it decided to split the company operations to two websites. Consequently, it lost out on more than 800,000 subscribers. The company claimed to have a wholly data driven marketing strategy. However this non-analytics decision proved to be its undoing.

What one can deduce from this case is that predictive analytics cannot replace a faulty system that is not easy to use.

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