Sep 06

MEDIAGENIX is IABM BaM Awards® 2019 finalist

Friday September 6th, 2019

Industry recognition for power of innovation

MEDIAGENIX is among the four vendors shortlisted for the IABM BaM Awards® 2019 in the category ‘Monetise’. The IABM BaM Awards® recognize innovations that deliver real business and creative benefits in a field of activities. The ‘Monetise’ field includes management of business processes for content rights and royalties, scheduling linear and non-linear services, and selling content.

CTO Peter Heinckiens: “We are of course very pleased to be among the four finalists for this industry award. We value this as a recognition of our rich history of innovations and state-of-the art solutions, which stem from our content-centric vision. It is this vision that led us to be one of the very first tech vendors to offer a single toolset for both linear and nonlinear content workflows.”

Living up to their global reputation as a leading tech vendor, MEDIAGENIX invested in an innovative architecture that enables them to swiftly develop, and implement solutions that offer media companies the speed and flexibility they need amid constant change, cutting through complexities and boosting efficiencies. A case in point is the current development for AI based automation of off-peak linear scheduling.

Product Manager Lucas Denys: “Whether you are planning high value content in primetime or the umpteenth rerun in a day part that serves a rather small audience, it takes you the same number of manipulations. With our solution the scheduling experts will be able to focus on primetime scheduling, which is their true art as this involves a lot of strategic decisions, and a business as well as a marketing vision.”

Also the success of off-peak scheduling depends on a great variety of dimensions, and the relative importance of these dimensions differs between broadcasters and channels. Using state of the art technologies such as machine learning and serverless architectures, the MEDIAGENIX solution will automatically optimize the off-peak schedule regarding viewer ratings and the use of available stock, while the planners will be able to finetune which criteria (cost, ratings, stock optimization, …) they find most important. The AI algorithm will learn which choices result in the best schedule.


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