Impact of AI-Based Personalised Services on Customer Loyalty

Abstract: Artificial intelligence (AI) has fundamentally transformed the capacity of organisations to deliver personalised recommendations, communications, customer service and digital experiences at scale. This study develops and empirically tests a comprehensive model linking AI-based personalisation with customer loyalty through the mechanisms of trust and customer satisfaction, while simultaneously examining AI service quality and privacy concern as contextual factors. Using a quantitative cross-sectional design, data were collected from 400 digital-service users through a structured 5-point Likert-scale questionnaire. The analysis encompasses descriptive statistics, reliability testing, KMO and Bartlett's tests, correlation analysis, multiple regression, mediation and moderation analysis, and selected demographic tests. The results demonstrate acceptable internal consistency for all constructs, with Cronbach's alpha values ranging from .801 to .865. The KMO value was .916 and Bartlett's test was statistically significant, indicating that the item correlation matrix was suitable for factor-oriented analysis. AI-based personalisation exhibited a positive association with customer loyalty (β = .380, p < .001), explaining 14.4% of its variance in the simple regression. The full regression model explained 42.4% of the variance in loyalty. A bootstrap test of the serial indirect pathway through trust and satisfaction was positive (indirect effect = .060, 95% CI [.040, .085]). Privacy concern significantly moderated the AI personalisation–loyalty relationship (interaction β = .060, p = .040). The findings contribute to the growing body of knowledge on AI-driven personalisation by demonstrating that trust and satisfaction serve as critical mediating mechanisms, while privacy concerns represent an important boundary condition. Keywords: artificial intelligence; AI personalisation; customer loyalty; trust; customer satisfaction; privacy concern; AI service quality; digital services

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-13
DOI
https://doi.org/10.5281/zenodo.23339434
Primary Topic
Customer Service Quality and Loyalty
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Impact of AI-Based Personalised Services on Customer Loyalty

Kishor Chauhan
Zenodo (CERN European Organization for Nuclear Research)
Customer Service Quality and Loyalty
article

Impact of AI-Based Personalised Services on Customer Loyalty

Kishor Chauhan
article en

Abstract

Abstract: Artificial intelligence (AI) has fundamentally transformed the capacity of organisations to deliver personalised recommendations, communications, customer service and digital experiences at scale. This study develops and empirically tests a comprehensive model linking AI-based personalisation with customer loyalty through the mechanisms of trust and customer satisfaction, while simultaneously examining AI service quality and privacy concern as contextual factors. Using a quantitative cross-sectional design, data were collected from 400 digital-service users through a structured 5-point Likert-scale questionnaire. The analysis encompasses descriptive statistics, reliability testing, KMO and Bartlett's tests, correlation analysis, multiple regression, mediation and moderation analysis, and selected demographic tests. The results demonstrate acceptable internal consistency for all constructs, with Cronbach's alpha values ranging from .801 to .865. The KMO value was .916 and Bartlett's test was statistically significant, indicating that the item correlation matrix was suitable for factor-oriented analysis. AI-based personalisation exhibited a positive association with customer loyalty (β = .380, p < .001), explaining 14.4% of its variance in the simple regression. The full regression model explained 42.4% of the variance in loyalty. A bootstrap test of the serial indirect pathway through trust and satisfaction was positive (indirect effect = .060, 95% CI [.040, .085]). Privacy concern significantly moderated the AI personalisation–loyalty relationship (interaction β = .060, p = .040). The findings contribute to the growing body of knowledge on AI-driven personalisation by demonstrating that trust and satisfaction serve as critical mediating mechanisms, while privacy concerns represent an important boundary condition. Keywords: artificial intelligence; AI personalisation; customer loyalty; trust; customer satisfaction; privacy concern; AI service quality; digital services

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 6%
Customer Service Quality and Loyalty
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.