Getting the most from CRM systems: Data mining in SugarCRM, finding important patterns

Abstract

An automated approach to business intelligence can help improve key performance indicators (KPIs) for businesses using SugarCRM. Data mining techniques will be used to analyze and present recommendations in a meaningful way to users of SugarCRM. One of the important outputs of the data mining process will be recommendations made to the user that effect KPIs of the business. Data mining can also be used to give users a better understanding of the dynamics of their own business and industry as predictable patterns can emerge from CRM datasets. While the approach and conclusions are general, the proposed strategies in this paper and the implementation are based on a SugarCRM installation. Predictive analytics in conjunction data mining has the potential to further improve reporting mechanisms from SugarCRM. © 2014 Springer International Publishing.