Big data, Analytics and Recommendations

The audience’s knowledge base of the current media is based on large volumes of data that must be ingested and processed in real time. Therefore, it is essential to have services based on Big Data architecture to guarantee granular access, authentication, security, encryption and auditing of the collected data. TV and media, in general, must have a unified data architecture that integrates the traditional data sources of the broadcast world such as Kantar media with the rest of available sources such as Comscore, Facebook or Twitter. This 360 view of the audience allows a complete analysis of the viewers/users and the return generated by their contents, which help both decision making in business and in the editorial line. The control of the data by a medium allows to design the strategy, apply Business Intelligence plans in content distribution, and beyond that, the selection of the most suitable content distribution technology at all times. In addition, it is necessary to have a unified identity manager of all the digital channels of a media outlet integrated into a single database. The correct management of these data sources and those identities allows us to efficiently feed the common recommendation engine for all the contact points of the audience of a media outlet, and optimize business indicators, offering a personal and transversal user experience focused on Marketing Automation. Finally, the system suggests users different topics that may be of interest to complement their profile and adjust the recommendations dynamically according to each user’s changes of preferences.