Abstract
A Predictive Analytical Study on Factors Enhancing Customer Acquisition and Retention
Highlights
Customer Relationship Management (CRM) is a term denoting practices, tactics and technologies used by organizations to handle customer interactions and concerned data during the customer lifecycle with the intent of enhancing customer experience and retaining them thereby increasing sales
CRM systems are intended to assemble data of customers that exist across channels and the various points of contacts such the company’s website, call logs, chat interfaces, mailing lists, records, social media and the other marketing materials. (Mirzaei & Iyer,2014 ; Wagner et al, 2006)
This analysis has been done in the current paper through a statistical method i.e. Logistic Regression using software R, which is known for statistical and predictive analytics
Summary
Customer Relationship Management (CRM) is a term denoting practices, tactics and technologies used by organizations to handle customer interactions and concerned data during the customer lifecycle with the intent of enhancing customer experience and retaining them thereby increasing sales. The analysis of deals has traditionally relied on assigned person, location, principal code, competitor, lead source, actual CM (contribution margin) and actual revenue. ISSN: 0972-8686 Online ISSN: 2455-0647 to explore this aspect of the subject organization where significant factors have been identified from data stored in the CRM to predict their effect in winning or losing a deal. Data terms used in the paper are Assigned Person referring to Location Sales Head. Detailed data have not been presented in this paper due to security concerns of the organization. It presents data used, the models created for predicting the customer orientation.
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