IDEAS home Printed from https://ideas.repec.org/a/vrs/gfkmir/v11y2019i2p36-41n5.html
   My bibliography  Save this article

AI-Driven Sales Automation: Using Chatbots to Boost Sales

Author

Listed:
  • Hildebrand Christian

    (Director and Professor of Marketing Analytics, Institute of Marketing (IfM-HSG), University of St. Gallen, Switzerland)

  • Bergner Anouk

    (University of St. Gallen, Switzerland)

Abstract

The implementation of bot interfaces varies tremendously in current industry practice. They range from the human-like to those that merely present a brand logo or a digital avatar. Some applications provide a maximum amount of information with limited turn-taking between the user and the interface; others offer only short pieces of information and require more turn-taking. Instead of simply implementing the default option provided by chatbot providers and platforms, companies should consider very carefully how the specifics of the chatbot interface might affect the user experience. Simple mechanics such as increasing the frequency of interactions leads to greater trust and a more enjoyable user experience. Also, personalizing chatbots with basic consumer characteristics such as gender increases trust and improves the perceived closeness between the customer and the chatbot – and ultimately the brand. Brand managers should therefore consider chatbots not as merely another digital marketing fad or a way to save costs through service automation. When implemented wisely, they are even able to increase a company’s upselling potential.

Suggested Citation

  • Hildebrand Christian & Bergner Anouk, 2019. "AI-Driven Sales Automation: Using Chatbots to Boost Sales," NIM Marketing Intelligence Review, Sciendo, vol. 11(2), pages 36-41, November.
  • Handle: RePEc:vrs:gfkmir:v:11:y:2019:i:2:p:36-41:n:5
    DOI: 10.2478/nimmir-2019-0014
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/nimmir-2019-0014
    Download Restriction: no

    File URL: https://libkey.io/10.2478/nimmir-2019-0014?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:gfkmir:v:11:y:2019:i:2:p:36-41:n:5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.