IDEAS home Printed from https://ideas.repec.org/a/taf/oabmxx/v11y2024i1p2326107.html
   My bibliography  Save this article

The power of AI: enhancing customer loyalty through satisfaction and efficiency

Author

Listed:
  • Pragya Singh
  • Vandana Singh

Abstract

In the rapidly evolving landscape of customer service, integrating AI-powered solutionshas emerged as a game-changer. This study delves into the intricate dynamics of AI-Powered Customer Service and its profound impact on customer loyalty, specifically focusing on the mediating roles played by customer satisfaction and perceived efficiency. Data were collected from 373 respondents in a cross-sectional study conducted in 2023. A structured questionnaire was administered electronically to individuals with recent experiences with AI-powered customer service within the last six months. The findings provide compelling evidence of the significant influence of AI-Powered Customer Service on customer satisfaction and perceived efficiency, as indicated by path coefficients of 0.91 and 0.95, respectively. Moreover, a strong relationship between customer satisfaction and loyalty (path coefficient = 1.05) and perceived efficiency and customer loyalty (path coefficient = 0.22) underscores their pivotal roles in driving customer loyalty. Organizations should strategically embrace AI-powered customer service, emphasizing efficiency and customer satisfaction. They prioritize customer-centric design in AI solutions to align technology with customer preferences and needs.

Suggested Citation

  • Pragya Singh & Vandana Singh, 2024. "The power of AI: enhancing customer loyalty through satisfaction and efficiency," Cogent Business & Management, Taylor & Francis Journals, vol. 11(1), pages 2326107-232, December.
  • Handle: RePEc:taf:oabmxx:v:11:y:2024:i:1:p:2326107
    DOI: 10.1080/23311975.2024.2326107
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/23311975.2024.2326107
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/23311975.2024.2326107?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    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:taf:oabmxx:v:11:y:2024:i:1:p:2326107. 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: Chris Longhurst (email available below). General contact details of provider: http://cogentoa.tandfonline.com/OABM20 .

    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.