ON Applying K-means Personalization to a website
I have previously discussed the principles of E-commerce Personalization, within which K-means has been described as a way to provided targeted recommendation. K-means allows to setup clusters or micro-cluster based on behavioral data. In order to be setup properly on a website, it requires both a front end and backend implementation.
Different websites offer specific recommendations pages using algorithm such as K-means to provide personalized content on your website.
Front-End Implementation
Events would be sent to an API, tracking information such as detailed page views with associated content information, add to cart actions, purchases etc… These events will be used by the backend to store and process the different information in order to generate recommendations.
Either these events are individually collected and stored in a user/session profile on the server side and a backend API is responsible for fetching and computing the required cluster assignment.
This is typically the type of implementation that relies on customer profiles platform such as Unomi allows for the…
