Abstract—Identifying the best client is a significant factor to rising business as well as reaching triumph. Within the customer data reclines the legend of the customer’s buying behaviors, interests, desires, orientations, preferences, socio-demographic as well as geographic structure. Identifying how to furnish that database and decipher that story into one of actionable and triumphant marketing activities is the science and art of statistical modeling: the statistics constrain the conclusions and the art is the intertwining of the particular business rules connected to the ambitions. The current research enlists significant topics of predictive modeling: choice of variables, data analysis, management of missing data, as well as estimation of models. Issues roofed embrace stepwise choice and principal components approach of variable choice; imputation techniques, missing variables, and data fusion methods for missing data; and validation methods and metrics for assessing predictive models.

Index Terms—customer database, predictive modeling, data analysis, marketing

Cite: Hafedh Ibrahim, "Topics in Predictive Modeling in Marketing Research," Journal of Advanced Management Science, Vol. 4, No. 3, pp. 216-223, May 2016. doi: 10.12720/joams.4.3.216-223