The Use of Meta-Heuristic Algorithm in Optimizing the Impact of Sensitive Marketing on Customer Loyalty: A Case Study in Iran's Textile and Apparel Industry

In the customer's interaction with the company, environmental information is received by the five senses. The compatibility or lack of compatibility of the environment's characteristics with the customer's sensory tastes can cause the customer's satisfaction or dissatisfaction. This research has two goals. The effect of mixed sensitive marketing on customer loyalty of Iranian clothing brands and optimization of the effect of mixed sensitive marketing on customer loyalty. The research method is descriptive-survey and practical in terms of purpose. The statistical population is unlimited and includes the buyers and consumers of clothes of 18 Iranian brands in the age group of children, teenagers and adults. The sample size of 384 was determined and selected using non-probability sampling method. In order to collect the data, the mixed sensitive marketing questionnaires of Kian and Loui 2009 and the customer loyalty questionnaire of vaida,kanopaite 2015 were used. In order to analyze the data, structural equations and LISREL software were used. The meta-heuristic algorithm part of the genetic algorithm was used for its optimal modeling. In this way, the rules related to the effect of the mixed dimensions of sensory marketing on customer loyalty were first identified by the decision tree and then these rules were optimized with the help of genetic algorithm with MATLAB software. The results of the research in the first part showed the approval of all sensory marketing components except the interaction component. In the second part, using the decision tree with the help of the genetic optimization algorithm, customer loyalty can be predicted with 97% accuracy and accuracy using 27 rules.