Predicting Life stage of a customer using the retail data

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It is desirable for a retailer to have information of the life cycle stage of  a customer. This helps greatly to a retailer in offer optimizations. Targeting right customer with rights offers is greatest challenge for a retailer. They run hundreds of promotions and optimizing it saves huge cost and helps in retaining customers. 

In the era of super markets, large retailers issue loyalty cards and maintain customer purchase data. But most of the demographic data is not available with them as customers normally do not fill these fields and leave them blank. Although customer demographic data are not available using purchase data certain life stages of customer can be predicted using rule base techniques or predictive modeling. Life stages bring changes in purchasing pattern.

1.  A single male will mostly buy his needs and daily eatables.  Eating habits gets changed if he is married etc.  A man can occasionally buy woman's product but it will be regular if he is married or in a relationship.  Similarly single ladies wont buy man's product. Also the quantity  or variety of grocery item increases. These can be tracked and used.
2. Parenthood also brings change in the purchasing pattern. They start buying baby products.

These are some examples of life changes. There can be several such changes in life. Transition from student hood to working professional etc do contributes in changing behavior of any person.

Thanks
Lokendra


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