Modelling of Automatic Text Mining Framework on CRM Dynamics using Competitive Intelligence

Abstract

CRM is the acronym for the term Customer Relationship Management . It is possible to know the newlinecustomers behavior and their value of any business by using the technology and man power with newlinethe help of CRM in an organized way. Business credits can be improved with the help of different newlineCRM strategies. CRM strategies can be applicable to provide the services and products based on newlinecustomers need, offer cross selling products, help the employees for closing the deals as early as newlinepossible, retain the current customers, find new customers, create efficient call centers, make simple newlinesales and marketing process. But now a day s companies are facing the problem to achieve these newlineCRM strategies in an efficient manner. Every moment they have to plan a new strategy to retain the newlineexisting customer and attract the new customer by analyzing the market. It is very difficult to newlineidentify the valuable customers automatically by analyzing customer s behavior. As well as CRM newlinefaces the problem to manage the enormous customer s feedback or data or messages. Automatic newlinefeedback classification is a major challenge in the field of CRM. Many algorithms have been used newlineto classify the feedback but the performance is not that much high. As well as routs the specific newlinefeedback to the appropriate service is a challenging task in CRM. It is an essential factor for newlineconstructing the key of competitiveness in case of any service industries to run the business. newlineTo mitigate issues related to CRM, firstly we have outlined and implemented Naïve Bayes newlineclassification to classify customers automatically and effectively to get the benefit based on their newlinerelevant documents in the generation of card. newlineSecondly we have implemented a new approach using k-Means clustering and Dynamic Rule newlineclassification to identify different type of customer for the growth of their organization by analyzing newlinethe customer s behavior. This research discusses about message delivery to the Potential Profitable newlinecustomers based on their interest and the offer on products using competiti