Year of Graduation
Predictive Modeling in CRM Marketing
Smart-Marketing: Data, Analysis, Insight
This work was carried out on the basis of the Group for Applied Markets and Enterprises Studies in National Research University Higher School of Economics (Perm) under the guidance of the laboratory researchers and in collaboration with the Out of Cloud Studio of CRM Marketing. The work focuses on the real case of predictive analytics usage in restaurant customer relationship marketing. The effectiveness of predictions was considered for three segments in the context of churn activation: non-activated clients - did not make any transactions after registration in the loyalty program; churn clients who have made one or two purchases; churn customers who have made three or more purchases. The main conclusions on case comparison: the effectiveness of forecasting customer segments for churn marketing campaigns depends on the sufficiency of available data. The main limitations of the current project are the lack of data on customer responses to previous marketing impacts and the fact that confirmation of obtained results for the non-restaurant business is possible only by experience.