Enhancing Chatbot User Experience: A Qualitative Analysis of Linguistic and Cultural Challenges on Iranian E-Commerce Platforms

This study examine the role of chatbots in enhancing user experience and service quality on Iranian e-commerce platforms, specifically focusing on Digikala.ir and Snapp.ir. It evaluates key attributes responsiveness, empathy, and reliability based on user feedback, and assesses the bot’s ability to interpret Persian while accounting for Iran’s cultural and linguistic context.Transparency emerges as critical to building user trust. Through in-depth interviews with 30 participants, the study applies a SWOT framework to identifies Strengths (such as scalability and fast track resolution), Weaknesses (limited conversational depth, dialect issue), Opportunities (improved natural language processing, customisation), and Threats (increasing competition, data privacy risks). Although the chatbots on Digikala and Snapp perform well for simple tasks, they require improvements in more complex interactions and cultural adaptation. Personalization, Privacy, and trust are key drivers of user satisfaction. This research offers actionable insights and future directions to guide the development of culturally attuned chatbot systems in Iran’s digital economy.