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Retail chatbots: The challenges and opportunities of conversational commerce

Author

Listed:
  • Leung, Chi Hong

    (Department of Management and Marketing, The Hong Kong Polytechnic University, Hung Hom)

  • Yan Chan, Winslet Ting

    (Department of Management and Marketing, The Hong Kong Polytechnic University, Hung Hom)

Abstract

Artificial intelligence (AI) refers to the ability of machines and/or robots to perform intellectual tasks like humans. AI technologies are widely used to support different activities in retail operations. In particular, retail firms have adopted chatbots to interact with consumers through various communication channels, including social media, live chat, SMS etc. In addition, chatbots have been used to support conversational commerce in which companies automate conversations with consumers about product selection and assist consumers to make informed choices throughout the shopping and decision-making processes. To investigate the state of the art of chatbots in the retail industry, this article qualitatively studies commercial chatbots from 40 retail firms. The study finds that chatbots assist consumers in completing general tasks, such as searching information, purchasing products, making reservations and collecting feedback. Chatbots are good enough to perform such general tasks, although they have limited capability with respect to processing and interpreting natural language. Chatbots also provide menus to address the most predominant issues encountered by consumers while running at a lower operational cost. It is anticipated that chatbots will gain popularity in the retail industry, and consumers would benefit from chatbots with improved features like more accurate predictions and better product recommendations.

Suggested Citation

  • Leung, Chi Hong & Yan Chan, Winslet Ting, 2020. "Retail chatbots: The challenges and opportunities of conversational commerce," Journal of Digital & Social Media Marketing, Henry Stewart Publications, vol. 8(1), pages 68-84, June.
    • Handle: RePEc:aza:jdsmm0:y:2020:v:8:i:1:p:68-84
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    Citations

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    Cited by:

    1. Muhanad Shakir Manshad & Daniel C. Brannon, 2023. "Gender-based conversational interface preferences in live chat systems for financial services," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(4), pages 822-834, December.
    2. Li, Chia-Ying & Zhang, Jin-Ting, 2023. "Chatbots or me? Consumers’ switching between human agents and conversational agents," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    3. Li, Chia-Ying & Fang, Yu-Hui & Chiang, Yu-Hung, 2023. "Can AI chatbots help retain customers? An integrative perspective using affordance theory and service-domain logic," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    4. Hildebrand, Christian & Hundertmark, Sophie, 2021. "A Strategy Framework to Boost Conversational AI Performance," Marketing Review St.Gallen, Universität St.Gallen, Institut für Marketing und Customer Insight, vol. 38(4), pages 10-16.

    More about this item

    Keywords

    artificial intelligence (AI); chatbot; conversational commerce; retailing;
    All these keywords.

    JEL classification:

    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

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