International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 2 (March-April 2025) Submit your research before last 3 days of April to publish your research paper in the issue of March-April.

A Structural Equation Modelling Approach to Analyse the Impact of AI-Driven Personalization for Customer Acquisition

Author(s) Devakumar G, Ekta Goplani, Sanjana Valecha, Aman Agarwalla
Country India
Abstract Enhancing customer acquisition in e-commerce requires a strategic integration of trust, customer engagement, transparent data policies, and AI-driven experiences. This study explores how these factors collectively shape consumer decision-making and brand loyalty.
The research objectives include, Examining the influence of trust and transparency on first-time purchases, Evaluating AI’s role in personalization and customer retention and Identifying engagement strategies that drive acquisition. A quantitative research design using Structural Equation Modelling (SEM) was employed to analyse factor relationships. Data was collected from a diverse sample of 400 e-commerce consumers, spanning different age groups and online shopping behaviours. Key findings indicate that AI-powered personalization and chatbot efficiency significantly enhance customer engagement. Price transparency and clear policies strongly influence consumer trust, while brand reliability plays a pivotal role in fostering long-term customer relationships. Although customer engagement has a notable impact, trust and AI-driven personalization emerged as the strongest drivers of acquisition. Based on these insights, the study recommends: Enhancing AI-driven chatbots for better customer interaction, Improving pricing transparency to build consumer confidence, Strengthening trust-building initiatives to drive long-term loyalty
Limitations include a geographically restricted sample and potential self-reporting biases. Future research could explore industry-specific applications and cross-cultural differences in customer acquisition strategies, refining digital commerce models for sustainable growth.
Keywords Customer Acquisition, AI-driven Personalization, Trust and Relationships, Customer Engagement, E-commerce Strategies.
Field Business Administration
Published In Volume 7, Issue 2, March-April 2025
Published On 2025-03-15
DOI https://doi.org/10.36948/ijfmr.2025.v07i02.38712
Short DOI https://doi.org/g895qq

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