Content Recommendation

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.

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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.