Alireza Rajabipoor Meybodi - Assistant Professor, Department of Business Administration, Faculty of Economics, Management and Accounting, Yazd University
Hossein Arjmandi - Master’s student in Business Management, Department of Business Administration, Faculty of Economics, Management and Accounting, Yazd University
Amir Reza Konjkav Monfared - Assistant Professor, Department of Business Administration, Faculty of Economics, Management and Accounting, Yazd University
Ali Morovati Sharifabadi - Associate Professor, Department of Industrial Management, Faculty of Economics, Management and Accounting, Yazd University

Nowadays, marketing is perceived not in its old sense -sales- but in its new sense: meeting customer needs. The development in electronic commerce (e-commerce) has also created a great volume of online customer reviews (OCRs), where the customers can discuss all the aspects of a product in their comments. Data mining techniques in machine learning have been used in many areas here. These techniques can be of great help to businesses in discovering the knowledge hidden among the large data in their databases. Indeed, various machine learning algorithm classes have been used in accomplishing the tasks related to natural language processing (NLP). Thus, these algorithms can be used to identify useful patterns in OCRs to get a better understanding of the customers. Hence, the study tried to design a model that could analyze OCRs using data mining and natural language processing techniques and divide them into marketing mix (product, price, place, and promotion) and then analyze them.

Marketing Mix, Artificial Intelligence, Natural Language Processing, Data Mining.