AI-Powered Personalization in Retail: Technical Implementation and Business Impact (Published)
This comprehensive article examines the transformative impact of artificial intelligence on retail personalization strategies. The article explores the technical architecture underpinning AI-powered retail systems, including data collection infrastructure, processing pipelines, and specialized machine learning models that enable personalized customer experiences. It addresses implementation challenges like real-time processing requirements and cold start problems while detailing key business applications such as intelligent product recommendations, dynamic pricing optimization, personalized marketing automation, and conversational commerce. It evaluates business impact across revenue metrics (conversion rates, order values, customer lifetime value), operational efficiencies (marketing costs, inventory management, return rates), and customer experience indicators. Ethical considerations including data privacy compliance, algorithmic fairness, and transparency practices are thoroughly examined. Finally, the article identifies emerging technologies shaping the future of retail AI, including computer vision applications, voice commerce integration, and augmented reality experiences. This synthesis of technical implementation and business outcomes provides stakeholders with evidence-based insights into the strategic value of AI personalization in contemporary retail environments.
Keywords: Customer Experience, artificial intelligence in retail, data privacy ethics, machine learning models, personalization strategy