Enhancing E-Commerce Customer Acquisition Through Trust, Customer Engagement, Transparent Data Policies, and AI-Driven Experiences
DOI:
https://doi.org/10.70112/ajms-2025.14.2.4274Keywords:
Customer Acquisition, AI-driven Personalization, Transparency, Trust and Relationships, Customer Engagement, E-commerce StrategiesAbstract
Enhancing customer acquisition in e-commerce requires a strategic blend of trust, customer engagement, transparent data policies, and AI-driven experiences. This study aims to explore how these factors collectively influence consumer decision-making and brand loyalty. The research objectives include assessing the impact of trust and transparency on first-time purchases, evaluating AI’s role in personalization and customer retention, and understanding engagement strategies that drive acquisition. A quantitative research design using Structural Equation Modeling (SEM) was employed to measure factor relationships. Data were gathered from a diverse group of 400 e-commerce consumers, representing various age groups and online shopping behaviours. The findings suggest that AI personalization and chatbot efficiency play significant roles in enhancing customer engagement. Price transparency and policy clarity were found to strongly influence consumer trust. Brand reliability was identified as a crucial factor in fostering long-term relationships. While customer engagement has an impact, trust and AI-driven personalization emerged as stronger drivers of acquisition. The study recommends enhancing AI-driven chatbots, improving transparency in pricing, and focusing on trust-building initiatives to optimize customer acquisition strategies. Limitations include a geographically constrained sample and potential self-reporting biases. Future research could explore industry-specific applications and examine cross-cultural differences in customer acquisition strategies, further refining digital commerce models for sustainable growth.
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