Neural Network Approach for Herbal Medicine Market Segmentation

Abstract

Market segmentation is the start point of executing targeted marketing strategy. This study aims to determine fit dimensions and appropriate specifications for the segmentation of herbal medicines market in order to provide production and market departments with fit strategies by identifying the profile of the market customers and recognizing their differences in the identified indices. This is an applied study in terms of objective and a survey-analytical cross-sectional study in terms of method. Data was collected using interview and questionnaire in the qualitative and quantitative sections, respectively. The population of study consists of the end users of different herbal medicines in Iran. Regarding the unlimited population of study, sample size was limited to 460 users selected from active pharmacies located in different regions of Tehran based on stratified sampling method. Neural network technique was used to analyze data and to determine the number of segments. According to the results by running neural network algorithm in different clusters, the best fit market segmentation is practiced by 5 clusters. Each cluster differs with others; therefore a fit strategy for each cluster should be formulated and executed in order to simultaneously attribute value to both customers and market.