In order to optimise digital content marketing for broadcasters, the Horizon 2020 funded ReTV project developed an end-to-end process termed "Trans Vector Publishing'' and made it accessible through a Web based tool termed "Content Wizard''. This paper presents this tool with a focus on each of the innovations in data and AI-driven media analysis to address each key step in the digital content marketing workflow: topic selection, content search and video summarization. Firstly, we use predictive analytics over online data to identify topics the target audience will give most attention to at a future time. Secondly, we use neural networks and embeddings to find the video asset closest in content to the identified topic. Thirdly, we use a GAN to create an optimally summarized form of that video for publication, e.g. on social networks. The result is a new and innovative digital content marketing workflow which meets the needs of media organisations in this age of interactive online media where content is transient, malleable and ubiquitous.