Investigating the Role of Artificial Intelligence in Predicting Consumer Preferences (A Little Study in the Tehran Market)

Kowsar Karami Nasrabad Sofla

doi:10.63053/ijmea.28

Authors

Kowsar Karami Nasrabad Sofla Master of Business Administration - Marketing, Department of Management, Mehr Alborz Institute of Higher Education, Tehran, Iran

DOI:

https://doi.org/10.63053/ijmea.28

Keywords:

Artificial Intelligence, Prediction of Consumer Preferences, Marketing, Random Forest, Support Vector Machine, Logistic Regression

Abstract

Accurately predicting consumer preferences is one of the key success factors in marketing strategies. This research investigated the effectiveness of different artificial intelligence models in predicting consumer preferences in the Tehran market. The required data was collected through a questionnaire including demographic characteristics and purchase preferences from 400 consumers in Tehran. After data preprocessing, random forest, support vector machine (SVM) and logistic regression models were implemented to predict consumer preferences. The results showed that the random forest model has the best performance among the investigated models with an accuracy of 87%. Also, the data analysis showed that the variables of age, income and education have the greatest influence in predicting purchase preferences. These findings can help local businesses to optimize their marketing strategies and achieve better results in attracting customers.

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