#HOME DEPOT FOOT TRAFFIC HOW TO#What recommendations can you provide on how to form and manage data science teams? We have seen lift in the engagement and conversion rates after deploying these advanced data-driven techniques especially when those techniques enable personalized experience. We used NLP and NLU to understand customer reviews and extract the pros and cons of the products. Khalifeh: We used Statistical Analysis and Association Rules to discover the relationship between different categories. What are some examples of how The Home Depot has leveraged different aspects of AI to solve challenging e-commerce problems? Our AI-based engine uses different modals like text, images, click-stream, and profiles data to match our customers with the most relevant recommendations that match their intent and interest. Khalifeh: Home Depot has invested in building personalized recommendation engines leveraging cutting-edge techniques such as deep learning, active learning, and graph mining. How is The Home Depot using AI to provide better recommendations for related products? This system helps our customers quickly understand what other customers liked or disliked about a product without a need to read thousands of reviews. Khalifeh: Home Depot has built a state-of-the-art sentiment analysis system which automates the process of understanding customers complaints as well as the features that customers like about our products. How is The Home Depot leveraging data science to gain insights and feedback on products?
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