User Profile Based Behavior Identification using Data Mining Technique

In regular retail shop the shopkeeper may predict the behaviour of customers using their facial expressions which can results in increase in their sell. However, while considering online shopping it is not possible to see and analyse customer behaviour such as facial expressions, products they check or touch etc. In this case, click streams or the mouse movements of E-Customers may provide some hints about their buying behaviour. In this, we have presented a model to collect, analyse click streams of E-Customers and extract information and make predictions about their shopping behaviour on an online shopping market place. The model we present predicts category of most likely bought products on a digital market place by the customer and according to that it gives recommendations of products to the E-customers. We are also going to provide offers on items added in basket of most likely bought category by customer through basket analysis. For analysis and prediction we are going to use Naive Bayes algorithm. Result of this analysis can be used in Customer Relationship Management and Business Intelligence.