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The Impact of AI and Machine Learning on E commerce Personalization

Shoh Jakhon KhamdamovAlfraganus university, Tashkent, UzbekistanMuhammad ShahbazDepartment of International Trade and Finance, Beijing Institute of Technology, Beijing, ChinaZоkir MamadiyarоvАнвар УсмановPlekhanov Russian University of economics Tashkent branch, Tashkent, Uzbekistan, UzbekistanBobur XonturayevSharofjon RashidovHuman Resources Management department, Tashkent State University of Economics, Tashkent, UzbekistanAlisher IzzatillayevTashkent State University of Economics, Tashkent, Uzbekistan
2024en
ABI

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The rapid evolution of e-commerce has propelled personalization to the forefront of digital marketing strategies. This study investigates the transformative impact of Artificial Intelligence (AI) and Machine Learning (ML) on e-commerce personalization, examining their effects on customer engagement, sales performance, and long-term market dynamics. We conducted a comprehensive econometric analysis using panel data from diverse e-commerce platforms over multiple years. Employing difference-in-differences models and instrumental variable approaches, we isolated the specific impact of AI and ML-driven personalization on key performance metrics. Our research encompassed various product categories and market segments to assess heterogeneous effects across the e-commerce landscape. The implementation of AI and ML-driven personalization strategies led to statistically significant increases in conversion rates (10-15%) and customer lifetime value (20-30%). These insights have significant implications for e-commerce strategy, investment decisions, and regulatory frameworks in an increasingly AI-driven economy. This research contributes to the growing body of literature on AI economics, providing empirical evidence of its impact in e-commerce. It offers valuable guidance for practitioners in optimizing personalization strategies and informs policy discussions surrounding digital market regulation, data privacy, and technological competition.

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