Evaluating the Impact of Chatbots on Customer Satisfaction in Online Shopping in Iran

The rapid growth of e-commerce in Iran has catalyzed the adoption of AI-powered chatbots to enhance customer interactions and streamline service delivery on platforms such as Digikala, Bamilo, and Snapp Market. This study investigates the impact of key chatbot attributes—ease of use, information quality, response time, and personalization—on customer satisfaction among Iranian online shoppers, with perceived usefulness as a mediating factor. Data were collected from ۱۵۰ respondents in Tehran and Isfahan using a structured questionnaire and analyzed with IBM SPSS (version ۲۰۲۳) through regression analysis, chi-square tests, and percentage analysis. Results indicate that ease of use, response time, and personalization significantly influence perceived usefulness (p<۰.۰۱), which mediates their impact on customer satisfaction (R²=۰.۴۵۲, p=۰.۰۰۰). Information quality showed marginal significance (p=۰.۰۴۵), suggesting contextual relevance in Iran’s market. These findings underscore the importance of responsive, user-friendly, and culturally tailored chatbots in addressing Iran’s unique e-commerce challenges, such as trust deficits and logistical inefficiencies. The study provides actionable recommendations for Iranian e-commerce platforms to optimize chatbot functionalities, fostering customer loyalty and competitive advantage in a dynamic digital market.

کلیدواژه ها:

Chatbots ، Customer Satisfaction ، Online Shopping ، Ease of Use ، Information Quality ، Response Time ، Personalization ، Perceived Usefulness ، E-commerce ، Iran ، Digital Customer Experience ، AI in Retail ، Trust in E-commerce