Personalized content proposals are now an established element of the Web. Most social media serve content to their users based on multiple touchpoints of the user’s interaction with the platform. (Some of them also track the user outside their pages, which has caused a whole discussion about privacy and blocking cross-domain tracking.) Usually, the aim is to increase some interaction rate (i.e. measured by the number of visits, purchases or other actions per user).
Online shops increase their revenue with clever recommendations of products that appear at every stage of the sales funnel. But non-retail sites can also benefit from the advantages of recommender systems. If you run a website that provides content, you can use content recommendations to maintain user attention and increase visits.
In this article, using an example of a movie database web site, I’ll show you how to add content recommendations to your website. We’ll discuss basic approaches to this and then use a SaaS called Pipeless, which allows you to create a database with built-in recommendation algorithms.