We built a recommendation engine that employs machine learning and deep learning algorithms. The recommendation engine has been used in several applications including a commodity trading platform and direct seller CRM.
Key Features:
- Content recommendation: Enable content recommendations in your application based on user interest and past browsing history.
- Customer Segmentation: Group customers with similar interests to personalize their experiences or run hyper-targeted campaigns.
- Product Segmentation: Group your products together on the product description, features, and visual attributes, and use it to make recommendations to buyers
- Collaborative Filtering: Collaborative filtering concentrates on gathering and analyzing data on user behavior, activities, and preferences etc., to predict customer behavior.
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