The Content Recommendation API helps you identify different types of content which your customers would likely be interested in, and ultimately make data-driven Content Recommendations to your customers, with the flexibility to customize your recommendations as needed, to enhance your engagement.
Our Content Recommendation algorithms combine a sophisticated recommendation engine that leverages content-based filtering, collaborative filtering, along with a powerful statistical model. This accounts for a number of decision-making factors, such as previously visited pages, pages, and user meta-data into the ranking process, by assigning scores to each of the visited pages which helps ensure that you have reliable results to keep your customers further engaged.
Collaborative Filtering vs Content-based Filtering
The training scheme for content recommendation is dynamic through online training, which is updated on a semi-real time basis. Our recommendation system is flexible to digest any special requests either for the used features (adding customized features or boosting specific ones based on the use-case), or for the returned results (e.g. filtering and slicing to match customized needs).
Pelcro's Content Recommendation API is a handy tool that takes care of the heavy-lifting when it comes to content personalization, and supports you to offer your customers content that resonates with them.