Why Predictive Analytics Can Drive Better Customer Engagement

Predictive Analytics on Customer Behavior, as implied by the term, predicts or forecasts what to expect from the customers. This is achieved by studying past data of customer behavior and applying that intelligence on current dealings with the customer.

For example, with predictive analytics, you may be able to say with which customer you are wasting your time selling your product. You might as well spend the time with those who might buy

Another example is, you might know from predictive analytics which customer is going to stop using your service, and this helps you to double your efforts at keeping the customer happy and retain in the process.

The advantage of using predictive analytics is that time, money and effort of both the customer and that of the serving organization is saved considerably by making only relevant conversations with customers. Imagine if we could live in peace without all those marketing calls and messages and receive only those that actually interests us.

World over there are several data analytics firms and consultants who engage with corporates studying their available data and coming up with algorithms and models that are used for such prediction.

Predictive analytics as a technique can be used for other internal business needs also, which is out of scope of this note.

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