Abstract

This research investigates the influence of Chatbot Marketing Efforts (CME) on brand loyalty, with a focus on the mediating roles of credibility, accuracy, system quality, and fulfillment quality. The study delves into the evolution of artificial intelligence in marketing, emphasizing the transformative role of AI, particularly in the rise of chatbot-based digital solutions. It addresses the need to understand how chatbot agents, along with mediating variables such as accuracy, credibility, system quality, and fulfillment quality, replicate the role of traditional service agents and impact brand loyalty. The research also aims to fill the gap in understanding the effects of chatbot marketing efforts in the Asian region, focusing specifically on Pakistan. A quantitative study was carried out, and one-shot, cross-sectional data was collected through questionnaires from a sample of 230 respondents. The target population was particularly from Lahore because it consisted of a lot of variation in terms of age and social status, increasing the authenticity of responses. Convenience sampling was used to reach out to customers who were already using chatbots. Once the data was collected, it was run through SPSS using Process Hayes Mediation Model 4. The findings of the conducted analysis supported five proposed hypotheses. These were: CME is positively associated with brand loyalty, credibility mediates the positive relationship between CME and brand loyalty, accuracy mediates the positive relationship between CME and brand loyalty, system quality mediates the positive relationship between CME and brand loyalty, and lastly, fulfillment quality mediates the positive relationship between CME and brand loyalty. These hypotheses emphasize the practical implication of the study and the potential for organizations in Pakistan to enhance brand loyalty among digitally engaged consumers by leveraging chatbot marketing strategies. Investing in the training and development of chatbot agents emerges as a crucial step to enhance their performance and improve customer interactions.

Full Text
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