Crossing Minds Session Based Recommendation

Cold Start Recommendation

When a new user arrives on your website, attempting to provide recommendations without knowing anything of their interests and tastes can be challenging, this is what we would categorize as a cold-start problem.

Increase Early Engagement with Cold Start Recommendations


Increase in CTR


Increase in Engagement


API Clients and Integrations


Top Increase in Engagement

Predicting without Knowing

When a new user arrives on your website, providing recommendations without data-sets about their interests and tastes can be challenging.  This is what we would categorize as a cold-start problem.

To solve the cold start problem, we implement deep content extraction with cross-channel pattern recognition and innovative machine learning algorithms. Combined, these unique approaches provide a solution for creating personalized recommendations with limited data sets on user tastes & preferences.

Simply put, you can use Recommendation Engines anywhere you’d consider making an offer to a brand new consumer!

The Technology Behind

Deploying trained embeddings and algorithms allows us to leverage not only the user-item feedback but the proper content of the items and the noticeable feature of the users simultaneously. These embeddings can be harnessed and used with little to no user feedback.

In addition, by adding layers of collaborative filtering, even more, embeddings are generated by identifying users with similar preferences. This also provides a new & unique solution to the cold-start problem for integrating both new users and new content.

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