Today’s media is more dynamic than ever, with short publish cycles bringing up-to-date news to consumers as it happens. When we think about content contextualization in the future (and at Spectrum the future is here today), we realize that speed has to accompany precision in order for contextual to be a strong, free-standing signal alongside whatever version of user-based targeting emerges from the cookiepocalypse.
That’s why we built Fast Match, the new sub-second contextualization engine driving the Spectrum Platform. Speed provides two benefits in any contextual platform. One is that the faster we can process new or updated content, the better chance that content has at having a relevant ad on it as it’s published. The lag time that exists in understanding consumed content can be expensive in terms of lost ad opportunities.
The second benefit is that the faster you can process, the more you can process. As before, Spectrum allows us to affix topics to a piece of content - not just a keyword, which may or may not be accurate - but now more rapidly than ever. The dreaded “screenshot”: how many times do we see an auto ad on an auto accident page? That’s why we moved past keywords in Spectrum. If we’re able to ignore the accident page and focus on the auto review pages, performance goes up for the brand and yield goes up for the publisher.
All of this becomes super critical in a world dominated by fast-changing Web and CTV content. Think about a world where bids can happen just as a piece of content is being published because the engine underneath has been able to process that new content in sub-second time, regardless of media type. That world exists today with the Spectrum Platform.