Analysis of Users Buying Behaviour to Improve the Coupon Marketing

  • František BabičEmail author
  • Ľudmila Pusztová
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 303)


The paper describes a data-mining case study devoted to an analysis of the users buying behaviour with the aim to improve the effectiveness of the relevant coupon marketing campaign. A coupon represents a ticket or number in an electronic form that we can use for a financial discount when purchasing a product. We can use this type of marketing to increase the number of the new customers and to reward the current ones. In our case, we used the datasets available within DMC 2015 and implemented the analytical process in accordance to the CRISP-DM methodology. Based on initial form of data, we focused mainly on pre-processing phase to extract hidden information, potentially useful for better prediction. For this purpose, we used decision trees algorithms like C4.5, C5.0, Random forest, CART and Logistic model tree. The obtained results were plausible and in some cases more accurate as other already published.


Transaction Coupons Data mining Decision trees 



The work presented in this paper was partially supported by the Slovak Grant Agency of the Ministry of Education and Academy of Science of the Slovak Republic under grant no. 1/0493/16, by the Cultural and Educational Grant Agency of the Ministry of Education and Academy of Science of the Slovak Republic under grants no. 025TUKE-4/2015 and no. 05TUKE-4/2017.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and InformaticsTechnical University of KošiceKošiceSlovak Republic

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