IDEAS home Printed from https://ideas.repec.org/a/dbk/manage/v3y2025ip177id1062486agma2025177.html
   My bibliography  Save this article

Leveraging Digital Marketing and Artificial Intelligence to Assess Enhanced Customer Experiences

Author

Listed:
  • Kalai Lakshmi TR
  • Jyoti Ranjan Das
  • Subhash Kumar Verma
  • Roopa Traisa
  • Varsha Agarwal
  • Charu Wadhwa

Abstract

Introduction: Incorporation of Artificial Intelligence (AI) into Digital Marketing (DM) has changed customer engagement by providing a personalized and efficient way to give service and interact with customers. For all of these advancements, there is limited empirical research that has explored how AI-driven personalization, convenience, and service quality impact customer experience through trust. Objective: This research uses a quantitative, survey-based research design to investigate how AI and DM influence customer experience. Method: Data is collected from 350 respondents that currently engage with an AI-enabled platform. Key constructs Perceived Personalization (PP), Perceived Convenience (PC), Customer Trust (CT), Customer Experience (CE) and AI-Enabled Service Quality (AESQ) were analyzed in this research. Result: Outcomes expose that PP (β = 0.34), PC (β = 0.28), and AESQ (β = 0.31) significantly influence CT, which in turn has a strong effect on CE (β = 0.62). The model explained that CT was 62% and CE was 56% variance, with statistical support of all hypothesis. Conclusion: This analysis concludes that AI-integrated DM strategies provide a better customer experience primarily because of developing trust. There are implications that marketers find practical in designing trust-centered AI interactions to enhance overall satisfaction and loyalty.

Suggested Citation

Handle: RePEc:dbk:manage:v:3:y:2025:i::p:177:id:1062486agma2025177
DOI: 10.62486/agma2025177
as

Download full text from publisher

To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a
for a similarly titled item that would be available.

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:dbk:manage:v:3:y:2025:i::p:177:id:1062486agma2025177. 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: Javier Gonzalez-Argote (email available below). General contact details of provider: https://managment.ageditor.uy/ .

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.