TY - GEN
T1 - Predicting customer churn
T2 - 14th European, Mediterranean, and Middle Eastern Conference on Information Systems, EMCIS 2017
AU - Katelaris, Leonidas
AU - Themistocleous, Marinos
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - Churn is the opposite of growth. Losing customers has serious impact on company’s overall performance. More specifically, means lost in sales and revenue, but also negative sentiment and potential negative impact to organization’s image for the competition. The increased importance of managing churn in subscription-based organizations, lead various efforts by subscription-based organizations to face the problem. Both, academic researchers and business practitioners, focusing on techniques around customer behavior forecasting. During the last years, various technologies have been used to forecast customer behavior in subscription-based organizations. To investigate further this area this paper aims to report on the research issues around customer churn and investigate previous customer churn prediction approaches in order to propose a new conceptual model for customer behavior forecasting.
AB - Churn is the opposite of growth. Losing customers has serious impact on company’s overall performance. More specifically, means lost in sales and revenue, but also negative sentiment and potential negative impact to organization’s image for the competition. The increased importance of managing churn in subscription-based organizations, lead various efforts by subscription-based organizations to face the problem. Both, academic researchers and business practitioners, focusing on techniques around customer behavior forecasting. During the last years, various technologies have been used to forecast customer behavior in subscription-based organizations. To investigate further this area this paper aims to report on the research issues around customer churn and investigate previous customer churn prediction approaches in order to propose a new conceptual model for customer behavior forecasting.
KW - Behavior forecasting
KW - Churn prediction
KW - Customer churn
KW - Prediction
UR - https://www.scopus.com/pages/publications/85028678864
U2 - 10.1007/978-3-319-65930-5_11
DO - 10.1007/978-3-319-65930-5_11
M3 - Conference contribution
AN - SCOPUS:85028678864
SN - 9783319659299
T3 - Lecture Notes in Business Information Processing
SP - 128
EP - 135
BT - Information Systems - 14th European, Mediterranean, and Middle Eastern Conference, EMCIS 2017, Proceedings
A2 - Morabito, Vincenzo
A2 - Themistocleous, Marinos
PB - Springer Verlag
Y2 - 7 September 2017 through 8 September 2017
ER -