Over the past year, brand safety within the video advertising medium has become an increasingly visible issue. The key takeaway has been that brands don’t really understand where their videos are being shown. We all got a peek at the … READ MORE
Video Content Targeting & Real Video Categorization
What is Video Content Targeting?
Veenome Contexial Targeting is a classification and targeting API that takes millions of impressions a day and automatically assigns them categories like: automotive, technology etc. The taxonomy or structure of those categories can be defined by our customers. Some use IAB categories, some use YouTube categories while others provide their own custom categories. These categories get used for contextual targeting, auditing, curation and simple business intelligence.
Why Veenome Content Targeting?
Our customers categorize their videos for a couple of reasons. Since it’s too labor intensive to categorize their videos manually they need a scalable solution like the Veenome platform to do it automatically. Uses include:
- Run-time Content Targeting : Veenome customers see a huge increase in performance when they are able to match ad verticals to the actual video content. This only reliably works when matching the actual video content (and not for page content or other simple metadata) For instance, placing Nike ads in front of sports videos lifts the performance by over 2X for the same inventory cost. By targeting consistently in this way, our clients see massive improvements in their campaigns across all categories.
- Campaign Analysis and Auditing: Ad networks see rich analytics on their video ad campaigns including content category, player size, duration, autoplay factors and more. They can also see rich publisher content profiles.
- SEO: Publishers and ad networks see more views(and revenue) for their videos because they are easier for their viewers to find when they are organized into surf-able categories.
- Search: Quicker and more efficient analysis and placement of videos via internal indexed access.