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Classifying potential users of live chat services and chatbots

Author

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  • Lova Rajaobelina

    (Université du Québec À Montréal)

  • Line Ricard

    (Université du Québec À Montréal)

Abstract

Live chat services and chatbot functionalities are experiencing significant growth within companies in the financial sector and growing consumer interest. But which consumers (segments) are more or less interested in these tools? Companies with an online presence would be well advised to profile potential users of these two important tools. This study seeks to classify potential users of live chat services and chatbots. A telephone interview questionnaire is administered to 342 panelists of a recognized Canadian research firm. A two-step cluster analysis is used to reveal natural groupings in the data set. Research conducted identifies four distinct segments, namely Women divided interest, Men partially interested, Age 35–44 partially interested and Older disinterested. This study brings to the fore information essential to the development of effective marketing strategies for reaching the different segments [e.g. develop and evidence an online end-to-end purchasing process for segment (1); provide good Web visibility for segment (2); ensure the presence of competitive offers and Web comparators for segment (3); and, pursue a more traditional approach for segment (4)]. This study represents the first ever classification of individuals based on their interest in emerging services (live chat services and chatbots).

Suggested Citation

  • Lova Rajaobelina & Line Ricard, 2021. "Classifying potential users of live chat services and chatbots," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 26(2), pages 81-94, June.
    • Handle: RePEc:pal:jofsma:v:26:y:2021:i:2:d:10.1057_s41264-021-00086-0
    DOI: 10.1057/s41264-021-00086-0
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    References listed on IDEAS

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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. Omar H. Fares & Irfan Butt & Seung Hwan Mark Lee, 2023. "Utilization of artificial intelligence in the banking sector: a systematic literature review," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(4), pages 835-852, December.
    3. Poornima Gupta & Preeti Goyal, 2024. "Herding the influencers for investment decisions: millennials bust the gender stereotype," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 29(2), pages 229-241, June.

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