SBIR Phase I: Diesel Labs: Leveraging social media analytics to solve for cross-channel media planning

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The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to trigger a major shift toward mobile content across the marketing industry - broadening the market and generating larger economic impact. Massive amounts of media dollars are poised to shift toward mobile video, but will not flow freely until ads can be delivered on the right content (engaging and safe) to the right people (targeted consumer segments) at the right time (when consumers are actively engaged). This SBIR Phase I project will radically advance the scientific and technological understanding needed for marketers to deliver ads this way, thereby enabling them to build their brands with sight, sound, and motion content delivered surgically through the most personal and engaging channel available - mobile. With the project facilitating this transition: 1) brands will be able to advertise more efficiently across TV and mobile media; 2) content producers, now able to extract fair market value for their efforts, will be motivated to create more and better content; and 3) audiences will benefit from improved content quality, selection and accessibility.This Small Business Innovation Research (SBIR) Phase I project is designed to enable brands and agencies to quickly and efficiently extend TV media plans into the rapidly growing mobile video space. While marketers have sophisticated TV planning tools at their disposal, they currently lack the ability to integrate TV/mobile video advertising in a way that optimizes their audience engagement and media spend. The research objective of this SBIR Phase I project is to develop social media-based recommendation technology to help marketers plan mobile video ad campaigns that seamlessly integrate with their traditional TV campaigns. The proposed project will 1) validate the technical and commercial feasibility of this approach and 2) produce an alpha version of the technology. Anticipated technical results include: building and testing a video content discovery engine; validating and implementing a planning system; initiating UI testing and user studies.