Content Personalization for 9GAG Using Recombee

This case study details the collaboration between Recombee and 9GAG, a global cross-platform entertainment network, to enhance user engagement through personalized content recommendations. 9GAG, which has over 200 million audiences and ranks first in cross-platform video creation in the US, implemented Recombee's smart content recommendation system to optimize their homepage's infinite scroll feature. The objective was to increase key performance indicators (KPIs) such as post views, interactions, and session duration. The study outlines the challenges faced due to the continuous influx of user-generated content and the need for real-time recommendations. Recombee's solution involved developing a custom recommendation logic that utilized advanced techniques including collaborative filtering and reinforcement learning. The results demonstrated significant improvements, with a 37% increase in post views and a 22% rise in overall interactions. The case study highlights the effectiveness of Recombee's technology in achieving high-quality personalization and enhancing user experience on the 9GAG platform.