Snackable Content™ enables you to identify relevant segments of a TV program for each of your individual viewers and recommend those to them as soon as they’ve been broadcast.
Our technology distills content based on faces, objects, interests and topics, among others, which is what makes it highly accurate and precise.
Based on the rich metadata we’re able to collect from your content, you can provide customers with video recommendations, tailored specifically to their interests and viewing history.
Despite having a large amount of media content available, Pay TV services have not been able to offer a user experience similar to OTT and VoD offerings, which can cater to their audiences with short snippets and binge watch possibilities. In order to address this shortcoming, TV providers offer short-form content by manually “cutting” the linear content into VoD assets. However, this is often neither feasible nor a scalable solution. Besides, it is not the only aspect that frustrates consumers: research shows consumers are also struggling to discover new content.
Read the full 10-page paper in which we present our platform that utilizes state-of-the-art Machine Learning algorithms for the real-time analysis of thousands of hours of multilingual multimedia content, including television and VoD. These analyses enable us to obtain rich metadata from the content of videos and suggest small chunks of personalised content (”snacks”) to users based on their preferences.