Predictive Model of Retail Chain Turnover in the IBM SPSS Modeler

Student: Belova Evgeniya

Educational Programme: Business Informatics (Master)

Year of Graduation: 2019

This paper is devoted to the developing of a predictive model of retail chain turnover. Resulting model is a single integrated solution based on the platform of predictive analytics IBM SPSS Modeler and SAP Business Warehouse based on SAP HANA. Source data for model is information about the activities of the trading network during the period from 01.01.2016 to 24.03.2009. The predictive model was based on weekly sales data. To conduct a comprehensive analysis, the predictive model was built at the aggregation level of retail network, stores and product categories. As part of the analysis at the level of stores, predictors, which are characteristics of sales points, were fed to the input of the model. The results are presented in the form of graphs and tables.

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