The Role of AI-Driven Personalization in Enhancing Customer Experience and Purchase Intentions: Exploring the Impact of Consumer Data Privacy Concerns

For this research, the primary objective is to investigate the impact of utilizing AI for personalized experiences on consumer purchasing behaviour. The study focuses on the level of customer engagement, the perceived value of the personalized experience, and overall satisfaction with the personalized interaction. Understanding these factors is crucial, especially with the increasing use of AI in personalization. Additionally, the study aims to examine how concerns regarding privacy, trust in digital technology, and general comfort with technology influence these relationships. To achieve these research goals, a combination of methodologies will be employed, including surveys and in-depth interviews. Convenience sampling, a non- probability sampling technique, will be utilized to select interview participants who have prior exposure to AI-driven personalization. The gathered data will then be analyzed using Structural Equation Modeling (SEM), with SMART PLS 4.0 being employed to drive the results of the study

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-01
DOI
https://doi.org/10.5281/zenodo.15314419
Primary Topic
Animal testing and alternatives
Type
article
Field-Weighted Citation Impact
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article

The Role of AI-Driven Personalization in Enhancing Customer Experience and Purchase Intentions: Exploring the Impact of Consumer Data Privacy Concerns

Zenodo (CERN European Organization for Nuclear Research)
Animal testing and alternatives
article

The Role of AI-Driven Personalization in Enhancing Customer Experience and Purchase Intentions: Exploring the Impact of Consumer Data Privacy Concerns

article en

Abstract

For this research, the primary objective is to investigate the impact of utilizing AI for personalized experiences on consumer purchasing behaviour. The study focuses on the level of customer engagement, the perceived value of the personalized experience, and overall satisfaction with the personalized interaction. Understanding these factors is crucial, especially with the increasing use of AI in personalization. Additionally, the study aims to examine how concerns regarding privacy, trust in digital technology, and general comfort with technology influence these relationships. To achieve these research goals, a combination of methodologies will be employed, including surveys and in-depth interviews. Convenience sampling, a non- probability sampling technique, will be utilized to select interview participants who have prior exposure to AI-driven personalization. The gathered data will then be analyzed using Structural Equation Modeling (SEM), with SMART PLS 4.0 being employed to drive the results of the study

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 47%
Animal testing and alternatives
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