Background: Understanding the customer experience is the success key of any business. With the advent of the Internet as the main channel for the supply of products and services in recent years, the customers online shopping experience has become vital. Purpose: The purpose of this research is segmenting customers experience in online retail stores.
Methodology: This research is applied in terms of purpose, and descriptive-survey in terms of method. The statistical population of the study includes all people who had the experience of buying from online retailers. The required sample size was calculated using the Cochran's formula for infinite communities, 384 people, who were selected by available non-probability sampling method. The data collection tool was a standard questionnaire, wich the validity was confirmed by face validity, and the reliability of the questionnaire was confirmed by Cronbach's alpha coefficient. The data of this study were collected through the distribution of an online questionnaire link and verbal. In order to analyze the data and segment the customers, the approach of self- organizing maps based on artificial neural networks has been used by Viscovery SOMine software.
Findings: According to the findings, customers of online retailers were divided into three sections with different demographic characteristics and components of online experience. Results: Based on the research findings, These three categories of customers were named apathetics, utilitarian and visual customers. The first part (apathetics) are the high-income men who have the most online shopping in the short time, and the ones who are least affected by the components of the experience, and the ability to communicate with the seller is most important to this group. The second part (utilitarians) are young and low-income women who have the least online shopping in the short time, and for the customers of this section, benefits and trust has more importance, compared to other s