Application of Fuzzy Logic for Advertising Marketing Campaigns

Bashiri, Abbas; ‎Mirhosseini-Alizamini, Seyed Mehdi; Nasrabadi, Mohammad Mehdi

doi:10.30473/coam.2021.58392.1160

Document Type : Research Article

Authors

Department of Mathematics‎, ‎Payame Noor University (PNU)‎‎,‎ ‎P.O‎. ‎Box‎. ‎19395-4697‎, ‎Tehran‎, ‎Iran‎.

https://doi.org/10.30473/coam.2021.58392.1160

Abstract

Evaluation of advertising marketing campaigns is a very important and complex task‎, ‎so far no comprehensive model has been presented in this regard‎. ‎The present study aims to provide a decision framework for evaluating marketing campaigns‎. ‎This article collects real-world data from an Iranian bank deposit marketing campaign‎. ‎For this purpose‎, ‎250 cases were considered to extract the rules and 60 cases were considered as test data‎. ‎Information is provided on 15 important parameters of marketing education‎, ‎defaults‎, ‎age‎, ‎occupation‎, ‎marriage‎, ‎day‎, ‎contact‎, ‎balance‎, ‎housing‎, ‎loans‎, ‎previous contact‎, ‎previous outcome‎, ‎month‎, ‎call duration, and campaigns‎. ‎A fuzzy expert system was designed with 12 rules after reviewing the rules and removing similar and contradictory rules by using their degree calculation‎. ‎In this system‎, ‎by integrating some factors‎, ‎finally, 6 input variables and one output variable were considered that were used by the product inference engine‎, ‎singleton fuzzifier, and center average defuzzifier‎. ‎It was observed that the designed fuzzy expert system provides very good results.

Keywords

References

[1] Abdoli M., Sheykhesmaeli S. 2015. “Identification of factors influencing the evaluation of marketing channels”, Second National Conference on Marketing Research, Tehran. (in Persian).

[2] Achrol R. S., Etzel M. J. 2003. “The structure of reseller goals and performance in marketing channels”, Journal of the Academy of Marketing Science, 31 (2), 146-163.

[3] Agatz N. A., Fleischmann M., van Nunen J. A. 2008. “E-fulfillment and multi-channel distribution-A review”, European Journal of Operational Research, 187 (2), 339-356.

[4] Alptekinoglu A., Tang C. S. 2005. “A model for analyzing multi-channel distribution systems”, European Journal of Operational Research, 163 (3), 802-824.

[5] Bond D. 2017.“Advertising agencies squeezed by tech giants”, The Financial Times, Available https://www.ft.com/content/9a9ac60a-575a-11e7-9fed-c19e2700005f.

[6] Chen G. Q., Wei Q. 2002. “Fuzzy association rules and the extended mining algorithms”, Information Sciences, 147, 201-228.

[7] Chiv R., Nie F., Wu S., Tum S. 2020. “Analysis of Factors Influencing Marketing Channel Choices by Smallholder Farmers: A Case Study of Paddy Product in Wet and Dry Season of Prey Veng Province, Cambodia”, Journal of Sustainable Development, 147, 201-228.

[8] Dashore P., Kumar-Jain S. 2009. “Fuzzy Rule Based System and Metagraph for Risk Management in Electronic Banking Activities”, International Journal of Engineering and Technology, 1 (1), 1793-8236.

[9] Dehghandar M., Khaloozadeh H., Soltanian F., Keshavarz M. 2016. “Application of Fuzzy Logic to determine the retentive causes of pulse body the pulse parameters”, Iranian Traditional Medicine, Journal of Multidisciplinary Engineering Science and Technology, 3 (2), 3881-3884.

[10] Dehghandar M., Pabasteh M., Heydari R. 2021. “Diagnosis of COVID-19 disease by fuzzy expert system designed based on input-output”, Journal of Control, 14 (5), 71-78. (in Persian).

[11] Deshmukh A., Lakshminarayana T. 1998. “A rule-based fuzzy reasoning system for assessing the risk of management fraud”, International Journal of Intelligent Systems in Accounting, Finance & Management, 4, 231-41.

[12] Ebrahimnejad A., Jafarnejad Ghomi S., Mirhosseini-Alizamini S. M. 2018. “A revisit of numerical approach for solving linear fractional programming problem in a fuzzy environment”, Applied Mathematical Modelling, 57, 459-473.

[13] Ebrahimnejad A., Jafarnejad Ghomi S., Mirhosseini-Alizamini S. M. 2017. “A new approach for solving fully fuzzy linear fractional programming problems”, 4th International Conference on Knowledge-Based Engineering and Innovation (KBEI-2017), 1-4.

[14] Ghen G. Q. 1998. “Fuzzy Logic in Data Modelling: Semantics, Constraints and Database Design”, Kluwer Academic Publishers, Boston.

[15] Guo S., Zhao H. 2017. “Fuzzy best-worst multi-criteria decision-making method and its
applications”, Knowledge-Based systems, 121, 23-31.

[16] Jarvinen J., Karjaluoto H. 2015. “The use of Web analytics for digital marketing performance measurement”, Industrial Marketing Management, 50, 117-127.

[17] Kamarzarrin M., Eghbal N. 2021. “Modeling of self-assessment system of COVID-19 disease diagnosis using Type-2 Sugeno fuzzy inference system”, Journal of Control, 14 (5), 49-57. (in Persian)

[18] khan N., Khan F. 2013. “Fuzzy Based Decision Making for Promotional Marketing Campaigns”, International Journal of Fuzzy Logic Systems (IJFLS), 3 (1), 65-77.

[19] Kyaw N. N., Ahn S., Lee S. H. 2018. “Analysis of the Factors Influencing Market Participation among Smallholder Rice Farmers in Magway Region, Central Dry Zone of Myanmar”, Sustainability, 10, 4441. https://doi.org/10.3390/su10124441

[20] Lewis R. A., Reiley D. H. 2013. “Down-to-the-minute effects of super bowl advertising on online search behavior”, Proceedings of the 14th ACM Conference on Electronic Commerce, Philadelphia, PA, Array, 639-656. https://doi.org/10.1145/2492002.2482600.

[21] Meng F., Chen X. 2019. “A robust additive consistency-based method for decision making
with triangular fuzzy reciprocal preference relations”, Fuzzy Optimization and Decision Making, 17 (1), 49-73.

[22] Nasrollahi M., Fathi M. R., Faghih A. 2018.“Designing a Model for Evaluating Marketing Channels based on the Fuzzy Best-Worst and Fuzzy EDAS Methods”, Journal of Business Management, 10 (3), 695-712. (in Persian)
[23] Saura J. R., Palos-Sanchez P., Cerda Suarez L. M. 2017.

Control and Optimization in Applied Mathematics

Application of Fuzzy Logic for Advertising Marketing Campaigns

References

References

Volume 5, Issue 2
Open Access Policy
Summer-Autumn 2020
July 2020
Pages 25-37

Application of Fuzzy Logic for Advertising Marketing Campaigns

References

References

Volume 5, Issue 2 Open Access PolicySummer-Autumn 2020July 2020Pages 25-37

Volume 5, Issue 2
Open Access Policy
Summer-Autumn 2020
July 2020
Pages 25-37