ContentWise, maker of the digital media recommendation engine proven to boost sales of VOD and live TV for several international service providers, today announced it will introduce ContentWise V4.2 at the 2012 IP&TV World Forum in March. V4.2 version brings two key new functionalities: A/B testing for operators and a social network data processing and presentation component.
ContentWise provides operators with a robust, scalable content discovery solution that incorporates detailed analytics. The software is designed for easy integration with IPTV services and, because of its cross-media and metadata processing capabilities, is ideally suited to providers that want to add recommendations to media stores that aggregate multiple media domains -- such as digital TV, e-books, games, music, and apps -- even with low-quality metadata input.
A/B testing is a new capability designed to help digital media operators test which approaches are successful with users by comparing a control group with a test group. Operators use A/B testing to measure the actual impact of each ContentWise business rule or combination of rules on any specific user segments or demographic in a real-life environment. With this method, operators can measure average revenue per user (ARPU), views per user, average time using the service, how much "lift" in consumption or revenue a specific recommendation or set of recommendations or business rule produces, and other performance indicators that would be impossible to measure without comparing a control group with a test group.
The new social component is a social network connector that enables the recommendation system to map and match operator content intelligently with external data sources, like Facebook. The external data source, Facebook or other networks, can be used both to improve the contextual information presented to the user and to enrich the catalog with additional metadata. It also ingests the "likes" of a user's Facebook friends to show what content that user's friends like -- recommendations that appear as an overlay/enhancement to the programming guide, music store, or app catalog. In addition, the information is used to provide quickly and seamlessly "cold-start" recommendations to new users who have not previously rated any catalog content.
"We approach recommendation from the perspective of both the operator and the user, and the latest edition of our ContentWise engine features improvements for both that will ultimately help generate revenue," said Paolo Bozzola, Moviri's CEO. "Now operators have a tool that enables them to be a lot more scientific and effective in knowing exactly how recommendations perform, which will help them fine-tune the service they deliver to customers. And users have a new mechanism for social engagement for a more personalized experience that translates to customer loyalty. One feeds into the other, and they both feed into revenue generation."