AI Clustering & Feature Engineering for Smart Retail Insights
Created using ChatSlide
Explore AI-driven techniques in retail analytics, focusing on clustering, feature engineering, and predictive modelling. Analyse supermarket sales data, derive customer metrics, and apply K-Means for segmentation. Utilise PCA for cluster visualisation and leverage machine learning for high-spender prediction. Uncover actionable marketing insights, enhance CRM systems, and optimise retail strategies. Ideal for improving loyalty programmes and inventory management, with scalable applications...