Transforming Retail Analytics: AI-Driven Insights for Personalized Shopping Experiences
Keywords:
Hybrid Neural Collaborative Filtering (HNCF), Personalized Recommendations, Deep Learning in Retail Analytics, Customer Interaction Data, E-commerce Platform Analytics, Collaborative Filtering TechniquesAbstract
AI-powered analytics have the potential to revolutionize the retail industry by offering customized purchasing experiences. This research presents a hybrid model that integrates collaborative filtering and deep learning approaches for the analysis of customer behavior and preferences. The model leverages transaction data and customer interactions to recommend personalized products with an impressive accuracy of 93.8%. The Hybrid Neural Collaborative Filtering (HNCF) model utilizes several advanced components, including Hierarchical User Attention and Product Attention (HUAPA), Deep Collaborative Filtering (DCF), Neural Sentiment Classifier (NSC), and Deep Multivariant Rating (DMR). HUAPA captures intricate details from user reviews and product descriptions, while DCF models user-product interactions using a multi-layer perceptron. The NSC module classifies sentiments from user reviews, adding another layer of personalization, and the DMR integrates multiple rating sources to produce a comprehensive product ranking.
Applied to a major e-commerce platform, this approach significantly enhanced the shopping experience. The real-world application of the HNCF model resulted in a 20% increase in customer engagement and a 15% boost in sales. The significant enhancements highlight the model's efficacy in precisely forecasting user preferences and delivering pertinent product suggestions. The results of this study highlight the transformative potential of AI in retail analytics. By integrating sophisticated machine learning techniques, the HNCF model not only delivers tailored shopping experiences but also drives customer satisfaction and boosts retail performance. This research underscores the importance of advanced AI solutions in the retail sector, paving the way for future innovations in personalized shopping experiences.
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