The scale at which content is produced and monetized across social platforms makes human curation of media plans impossible. OpenSlate’s unique, data-driven approach enables us to analyze and measure the nature and quality of social video content at scale.
OpenSlate’s data platform allows us to observe billions of data points across 4MM+ channels and 1B+ videos. Leveraging advanced data science, we analyze a unique combination of creator, content, and audience engagement signals to classify content.
This unique content classification helps advertisers understand and assess the subject matter, suitability, and quality of content – and, ultimately, make better decisions about where their ads run and what caliber of content and creators they choose to support.
Our ratings system begins with an independent assessment of content subject matter. OpenSlate applies machine learning, natural language processing, image recognition and more to create our proprietary content taxonomy.
OpenSlate rates the suitability of content based on the presence and prevalence of harmful and brand-sensitive subject matter. Suitability is not one-size fits all; OpenSlate gives advertisers the ability to navigate away from dozens of misaligned categories such as kids content, politics, video gaming, and more.
SlateScore is OpenSlate’s proprietary content quality metric that empowers advertisers to align with high-quality content at scale. Driven by nearly a decade of iterative data science, SlateScore rates overall content quality by leveraging a robust data set including popularity, engagement, and predictability signals.