Impact of AI-Generated Recommendations on Consumer Purchase Intention and Brand Loyalty in E-Commerce
DOI:
https://doi.org/10.63075/jk7qq710Abstract
Artificial intelligence-generated recommendations have fundamentally transformed e-commerce, yet a comprehensive understanding of their impact on consumer purchase intention and brand loyalty remains limited. This study addresses critical gaps in understanding how AI recommendation systems influence consumer decision-making processes and long-term brand relationships. Given that 71% of consumers now expect AI integration in shopping experiences and AI recommendations achieve 30% higher conversion rates than traditional approaches, investigating these mechanisms is essential for optimising e-commerce strategies. This research employed quantitative analysis of three comprehensive e-commerce datasets, primarily utilising Retail Rocket's platform data. It encompassed 2,756,101 behavioural events from 1,407,580 unique visitors interacting with 235,061 products over 4.5 months. Analysis incorporated conversion funnel methodology, temporal pattern examination, customer segmentation analysis, and repeat purchase behaviour tracking. Findings revealed a 0.84% overall view-to-purchase conversion rate with significant stage-wise attrition, particularly at the view-to-cart transition (97.4% drop-off). Repeat purchasers, constituting only 1.9% of visitors, generated 57.3% of transactions, demonstrating disproportionate value. Category-specific conversion rates varied substantially (0.6%-2.1%), indicating product characteristics significantly influence purchase likelihood. Recommendations emphasise implementing AI systems to address initial conversion bottlenecks, personalising recommendations based on category-specific behaviours, and optimising timing strategies for loyalty reinforcement during critical post-purchase windows.
Keywords: Artificial Intelligence Recommendations; Consumer Purchase Intention; Brand Loyalty; E-Commerce Conversion Optimisation; Personalised Marketing
