Understand the varying, complex datasets available and how data can affect their media mix and drive campaign results. The VideoAmp Platform is purpose-built with this in mind, powered by the most trusted, highest quality TV dataset in the industry.
VideoAmp’s linear TV dataset is one of the largest commingled, deduplicated and enriched Set-Top Box (STB) and Automatic Content Recognition (ACR) television exposure datasets in the industry, across 39M households and 63M devices.
Our digital dataset is built from first- and third-party data sources, log-level ad server exposure files, transactional attributes and 240M unique user profiles.
unique user profiles
Following a fully FTC-compliant methodology for household identity matching and consumer attribution, we combine these datasets to create a unified, proprietary ID powering TV to digital connections: the VideoAmp ID.
The VideoAmp ID
Without access to a complete picture of their media performance, those who use a single source of TV viewership data struggle to develop actionable insights and measure with confidence. Each dataset inherently contains its own benefits and drawbacks. While new TV viewership data sources are plentiful and continue to become available, these sources individually are not an accurate reflection of the demographics and viewership habits of the entire U.S. population.
We take multiple raw, disparate sets of viewership, schedule and metadata, some of which may contain conflicting or overlapping information, and combine them to make one accurate, holistic view that answers the question: “Who is watching what and when, and where are they watching it?” While the process appears straightforward, each step involves complex data science algorithms, processes and programs in order to execute these tasks at the scale and accuracy required.
The commingling process takes place in three phases:
Properly receiving and storing TV viewership data is an essential first step of commingling to ensure both data and privacy integrity.
Once the data has been ingested, it’s essential that the data is properly scrubbed and cleansed of additional inaccuracies. This process will continue to reduce the number of total viewership sessions, but will increase the overall accuracy of the information.
The real commingling process begins by joining separate, enriched datasets to form a holistic, unified dataset with enhanced accuracy and completeness.
The three distinct data types leveraged within our industry are detailed below, including current challenges and how VideoAmp fine-tunes and enhances these data types to ensure maximum results.
Platforms often license and repackage unprocessed, uncleansed TV viewership datasets since few have the data science and engineering capabilities to properly clean and correct these complex datasets. This results in unstable and inaccurate data.
We source anonymized, raw data across the linear and digital ecosystem, which is ingested, cleansed, processed, stored and published in a familiar format. This ensures the data is available and actionable in market.
The purpose of ad exposure data is to indicate whether a household saw a specific airing of a creative ad.
We leverage multiple sources of ad exposure data — from STB, Automatic Content Recognition (ACR), Over-The-Top (OTT), commercial airings and TV schedule data — to create a proprietary matching system that identifies ad exposure at the household and device level.
All raw datasets are inherently biased, skewed by age, income, geography, ethnicity, etc. In order to have a balanced and accurate U.S. panel, these skews must be corrected.
We complete a rigorous process to cleanse raw datasets that includes using demographic weights to correct for demographic skews, modeling the audience to match the size and composition of the U.S. census. Our proprietary method of skew-correction and modeling to census ensures the accuracy of our TV viewership datasets across age, gender, income, education, ethnicity and geography.
Advertisers need reliable measurement solutions that are not only trustworthy, but scalable, interoperable and cross-screen to form the foundations of their media investment initiatives. From planning to activation, negotiation and attribution, advertisers who leverage commingled data will exceed the competition in every facet of business.
Supports in-flight optimization for linear and digital.
Improves overall confidence in network recognition and mitigates the effects of phantom viewing sessions where cable boxes are left on, while TVs are off.
Increases match rates of first- and third-party attributes between platforms due to increased footprint and span.
Includes ACR sources to ensure future measurement capabilities of national addressable audiences.
Our commingling methodology is designed to power TV to digital connections — enhancing the entire advertising experience by solving today’s most advanced use cases and paving the way for the future.