Case Study: Allente Achieves Personalized Streaming Recommendations with KNIME

How Allente built a recommendation engine to deliver personalized content

Allente, a Nordic TV distributor serving more than one million customers across Sweden, Norway, Denmark, and Finland, wanted to reduce viewer decision fatigue and help customers quickly find content they would enjoy. To address this challenge, Allente turned to KNIME and its end-to-end data science platform to support marketing analytics, streaming analytics, and recommendation engine development.

Using KNIME, Allente built an automated data pipeline to connect cloud and on-premises sources, including event data, video-on-demand catalogs, and legacy Oracle data, then created and deployed a machine learning-based recommendation model in the same visual environment. The solution now delivers highly relevant content recommendations, including for new users without viewing history, improves content distribution efficiency, and helps Allente tune recommendations as new data arrives. KNIME also supports churn prediction, customer lifetime value analysis, and personalized upsell offers, helping Allente improve retention and drive a more data-driven culture.

Allente