The Ecommerce Demo features various capabilities of Fusion for ecommerce related use cases. Search results for recommended items are driven by the results of an ALS (Alternating Least Square) machine learning job. Each logged in user will have a different set of items. While Item to Item recommendations uses the same signals data from the users to determine item level similarity. This allows you to use user signals to automatically group items that are similar to one another.
The Query Intent Classifier uses a pre-trained Machine Learning model to analyze the query intent of user and dynamically create relevant facet fields that contains categories relating to the query. Rules and Signals will play side by side to deliver a cohesive search experience to customers. Allowing you to accelerate trends and push products to sell
The demo can be used with the standard admin/<password> pair available on the labs instance detail page OR by using andy/password123 or delores/password123 for the logins.
To start this instance with your Github account, click on the Launch Now button to the right. The video below covers using the running application to demonstrate how Fusion provides a wide variety of ecommerce related search and recommend features.