Theory of Moments Theory of Moments

Theory of Moments

Digital media consumption is at an all-time high while attention spans are at an all-time low. To increase ROI, content producers must target peaks of attention (moments) that contain the highest potential impact for a campaign. Filling these moments with relevant, personalized stories for an audience will have the greatest impact. Current processes to achieve this are laborious and expensive, but AI can help content producers tap into “smart content” more cheaply and quickly. Using hyper-tagging, and analytics, AI enables advertisers to build meaningful, compelling content and place that content in front of the audience at just the right moment.

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Artificial Intelligence has the capabilities to boost “moment intelligence” of media content accurately at scale. Computer vision and speech recognition – the principal modalities of AI – can identify and tag a large volume of varied video content via hyper-tagging. By layering analytics on top of those searchable entities, content makers, and advertisers can now access the most valuable moments for their campaigns. AthenasOwl integrates well with existing video indexing, search and retrieval technologies in play. It also integrates other data sets to enable highly predictive analytics around content performance and viewership responses.


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