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  • KPI System Development for Marketing Department of the Retail Company Based on Data Analysis Using Corporate DWH

KPI System Development for Marketing Department of the Retail Company Based on Data Analysis Using Corporate DWH

Student: Ratushniak Dmitrii

Supervisor: Oleg Simakov

Faculty: Graduate School of Business

Educational Programme: Business Informatics (Master)

Year of Graduation: 2017

These years the economy is developing incredibly rapidly, and in such circumstances, information technology, coupled with intellectual capital, is becoming more important. Factors that previously provided companies with a competitive advantage can no longer alone predetermine the successful growth and development of the enterprise. During the heyday of information technology, a very important role is played by various kinds of information resources. They are becoming one of the most important engines, providing companies with a competitive advantage.  For retail companies in the conditions of severe competition, the need for competent management of such resources is particularly acute, since marketing is the key for the company to attract new and retain existing customers, and this department, with almost invisible physical assets, is the concentration of intangible assets .  In this paper, a strategic control system is being developed for the marketing department of the retail network. The system is based on the BSC concept, supplemented by modern methods of data analysis. For this development, the following steps were made: the creation of data marts containing the necessary marketing indicators, the transition to the target infrastructure through the implementation of the necessary components, the development of indicators for evaluating the department performance, the analysis of historical data for the creation the target values, the identification of potential growth points and the development a set of recommendations to achieve these target values . As part of this recomendation set, machine learning models were built - random forest and neural network, providing better communications with the customers.

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