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Predictive analytics leads to better sales results By Amitabh Bose

Most of us on the listening end of a generic mass marketing call have usually turned down (often not too politely) the "special offer," even before the telemarketer is halfway through the script. As a result, it is no surprise that this approach produces very low response rates, presenting a challenge for marketing departments’ ROI.

But consider this. You get a call where the telemarketer hits a sweet spot- a free 4 day / 3 night holiday at your favorite beach resort which you haven’t been to in a while... suddenly the deal doesn't sound so bad; the car price covers insurance - you hate to pay insurance on a new car - and well, why not... sounds familiar. If so, you have been effectively profiled!

The company representative knew that this was around that time of the year when you go on your holiday and presented the right offer at the right time. The key to this success is predictive analytics. Past customer demographic and purchase data was automatically mined and customer behavior patterns and relationship information was captured to predict buying behavior for specific customer segments. This methodology helps marketers arrive at the most probable products you will purchase and a rating of your interest in them.

Predictive analytics helps sales persons understand what you purchased previously and the offer that you are most likely to jump at in the future. In a sense, it's like looking at the rear view mirror and then changing lanes. You could say that predictive analytics is used for targeted prediction of a potential customer and making personalized product recommendations that will help close a sale quickly. Having said that, this is just one of the many mainstream applications of predictive analytics.

Given the tough economic times, if this deceptively simple discipline can help maximize ROI, minimize risks and most importantly create happy customers, it surely deserve a serious consideration.

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