Insider’s personalized recommendation engine Smart Recommender analyzes users’ on-site behaviors and makes recommendations, predicting the products that visitors are most likely to engage with. Machine-learning technology streamlines unstructured user data to create meaningful patterns and identifies the true intent of customers. This enables personalized recommendations for each customer based on their relationships with products and their resemblance to other users. The intelligent algorithms constantly learn and adapt to changing user behavior, increasing the relevancy of recommendations over time.
Even with massive product inventories, Smart Recommender was able to consolidate such data and make sense out of it, creating customer profiles in order to deliver compelling and relevant content to consumers.
The built-in A/B/n testing capability of Insider’s personalization platform was exactly what LC Waikiki was looking for to be able to test their recommendations on a grounded base. With its A/B/n testing module, Insider helped LC Waikiki determine the actual monetary uplift generated, measuring the effectiveness of recommendations against a control group.