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Predictive Analytics for High Business Performance through Effective Marketing

Journal: International Journal of Trend in Scientific Research and Development (Vol.2, No. 2)

Publication Date:

Authors : ;

Page : 1046-1050

Keywords : Computer Engineering; Customer Relationship Management (CRM); Machine Learning; Customer Segmentation; Customers Targeting; K-means algorithm; Smote; Logistic Regression; Classification; Clustering;

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Abstract

With economic globalization and continuous development of e-commerce, customer relationship management (CRM) has become an important factor in growth of a company. CRM requires huge expenses. One way to profit from your CRM investment and drive better results, is through machine learning. Machine learning helps business to manage, understand and provide services to customers at individual level. Thus propensity modeling helps the business in increasing marketing performance. The objective is to propose a new approach for better customer targeting. We'll device a method to improve prediction capabilities of existing CRM systems by improving classification performance for propensity modeling. Supriya V. Pawar | Gireesh Kumar | Eashan Deshmukh"Predictive Analytics for High Business Performance through Effective Marketing" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-2 , February 2018, URL: http://www.ijtsrd.com/papers/ijtsrd9502.pdf http://www.ijtsrd.com/engineering/computer-engineering/9502/predictive-analytics-for-high-business-performance-through-effective-marketing/supriya-v-pawar

Last modified: 2018-08-02 17:23:15