Title :
Impact of social attributes on Predictive Analytics in telecommunication industry
Author :
Hashmi, O.Z. ; Sheikh, S.
Author_Institution :
SZABIST Islamabad, Islamabad, Pakistan
Abstract :
This paper will be presenting how the social attributes impact the Predictive Analytics results when applied on the telecommunication industry dataset. Predictive Analytics is the new emerging field in data mining, and is actively being applied to solve multiple business questions, such as Customer Churn, Product Up-Sell and Cross-Sell, etc. Predictive Analytical models exploit patterns that are found in historical and transactional data to identify risks, opportunities and future events. During comparative analysis it was noticed that with the Addition of Social Attributes, the Efficiency and Reliability of these Models is greatly enhanced.
Keywords :
consumer behaviour; data analysis; data mining; telecommunication industry; business questions; customer churn; data mining; predictive analytics; product cross-sell; product up-sell; social attributes; telecommunication industry dataset; Customer Churn Prediction; Data mining algorithms; Predictive Analytics; Social Network; Social Network Analysis;
Conference_Titel :
Multitopic Conference (INMIC), 2012 15th International
Conference_Location :
Islamabad
Print_ISBN :
978-1-4673-2249-2
DOI :
10.1109/INMIC.2012.6511470