电子商务与消费者行为:人工智能驱动的个性化和市场趋势综述

Mustafa Ayobami Raji, H. B. Olodo, Timothy Tolulope Oke, Wilhelmina Afua Addy, Onyeka Chrisanctus Ofodile, A. Oyewole
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摘要

在电子商务(e-commerce)的动态环境中,了解并适应不断变化的消费者行为对于在线业务的持续成功至关重要。本评论深入探讨了电子商务与消费者行为的交叉点,重点关注人工智能(AI)驱动的个性化的变革作用及其对市场趋势的影响。人工智能的出现彻底改变了电子商务平台接触和迎合个人消费者偏好的方式。人工智能驱动的个性化技术利用先进的算法分析庞大的数据集,从而能够提供高度定制的相关内容、产品推荐和用户体验。本综述探讨了人工智能驱动的个性化的复杂机制,研究了它如何提高客户参与度、满意度和忠诚度。此外,本研究还探讨了人工智能在电子商务中形成的显著市场趋势。从促进无缝客户互动的聊天机器人和虚拟助理,到优化库存管理的预测分析,人工智能正在推动在线零售业各方面的创新。分析深入探讨了机器学习算法在预测消费者偏好、简化购买流程和促进更个性化的购物之旅方面的整合。随着电子商务的不断发展,本报告还探讨了与人工智能驱动的个性化相关的挑战和道德考量。对数据隐私、算法偏差以及定制化与侵入性之间的微妙平衡等问题进行了研究,以全面了解人工智能在塑造消费者行为方面的广泛影响。最终,这篇综述为电子商务与消费者行为之间的共生关系提供了宝贵的见解,揭示了人工智能驱动的个性化的变革力量及其对新兴市场趋势的影响。随着企业在数字领域的不断发展,要保持竞争力并满足精通技术的消费者不断变化的期望,了解和利用人工智能驱动战略的潜力势在必行。
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E-commerce and consumer behavior: A review of AI-powered personalization and market trends
In the dynamic landscape of electronic commerce (e-commerce), understanding and adapting to evolving consumer behavior is critical for the sustained success of online businesses. This review delves into the intersection of e-commerce and consumer behavior, focusing on the transformative role of Artificial Intelligence (AI)-powered personalization and its impact on market trends. The advent of AI has revolutionized the way e-commerce platforms engage with and cater to individual consumer preferences. AI-powered personalization techniques leverage advanced algorithms to analyze vast datasets, enabling the delivery of highly tailored and relevant content, product recommendations, and user experiences. This review explores the intricate mechanisms of AI-driven personalization, examining how it enhances customer engagement, satisfaction, and loyalty. Furthermore, the study investigates the prominent market trends shaped by AI in e-commerce. From chatbots and virtual assistants facilitating seamless customer interactions to predictive analytics optimizing inventory management, AI is driving innovation across various facets of the online retail landscape. The analysis delves into the integration of machine learning algorithms in predicting consumer preferences, streamlining the purchasing process, and fostering a more personalized shopping journey. As e-commerce continues to evolve, the review also explores the challenges and ethical considerations associated with AI-powered personalization. Issues such as data privacy, algorithmic bias, and the delicate balance between customization and intrusiveness are examined to provide a comprehensive understanding of the broader implications of AI in shaping consumer behavior. Ultimately, this review offers valuable insights into the symbiotic relationship between e-commerce and consumer behavior, shedding light on the transformative power of AI-powered personalization and its influence on emerging market trends. As businesses navigate the digital landscape, understanding and harnessing the potential of AI-driven strategies become imperative for staying competitive and meeting the evolving expectations of tech-savvy consumers.
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