There is chaos in the data marketplace. Not all screens are measured using the same systems. There are data privacy regulations to navigate and comply with. Different data partners support different objectives. And there is no one-size-fits-all when it comes to how you optimize your entire media buy, including linear TV, digital direct, reserved CTV, and programmatic CTV.
While there are many ways to view the same content across many devices, measuring that viewership is extremely difficult when data sources are siloed. Marketers need reliable and consistent viewership sources and the ability to streamline and future-proof how to plan, buy, optimize, and measure media exposure. This is especially true when considering the evolving privacy landscape around issues such as cookie and IDFA depreciation, as well as regulatory considerations related to GDPR and CCPA.
Here’s an overview of the many flavors of viewership data and how data partnerships can empower your marketing strategy, free you up from relying on a single data source, and take your teams’ data knowledge to the next level.
Automated Content Recognition (ACR):
This is a core foundation of digital viewership measurement today and provides an array of valuable opportunities for advertisers. ACR enables many forms of targeting, like competitive conquesting, or showing an ad on CTV to someone unexposed to the same spot on linear TV. ACR is device-level data, not user-level data, and the ACR chip-set is embedded in more than 20 TV brands across 120 million homes in the U.S. that own smart TVs. This number has increased by 39% YoY.
Why You Need It:
ACR tech has the potential to capture all types of TV viewing behaviors across linear, video-on-demand, CTV/OTT, commercials, and video games. However, in its pure form, ACR data only shows part of the data picture and often presents the classic linear TV viewership blindspot that can’t distinguish between what was watched on network television versus what was watched via a streaming platform. Despite this, ACR’s ability to capture whatever is running on-screen and link it back to digital campaign exposures makes it an integral component of any cross-channel planning and measurement initiative.
TV Panel Data:
More commonly known as Nielsen Panel Data, Nielsen’s People Meter data is the media industry “gold standard” for knowing who’s watching what on television and when across all geographical locations. The 45,000-household panel serves as the main data currency for the buying and selling of TV advertising. Nielsen’s panel data represent a cross-section of households throughout the country, and viewing is measured and captured using opt-in people meters.
Why You Need It:
TV panel data can be used to validate ACR and Set-top Box data and the linear reach of a given campaign. If your campaign is geared towards holistic activation, then Nielsen panel data is key for validating your cross-channel measurement. When leveraging ACR or STB (or a combination of the two) to model linear viewership, it is important that your reach projections align with the industry standard, or the currency by which the linear portion of your buy transacted.
This data source delivers linear television to a home without internet-based, over-the-top devices like Roku, Apple TV, Amazon Fire TV, or Google Chrome. STB data is collected in more than 40 million households nationwide, and because this is deterministic data, it enables marketers to understand the buying tendencies of households so they can more accurately target specific audiences and buy ads on the shows that the best prospects watch most. Many multichannel video programming distributors (MVPDs) license set-top box data to comScore, Nielsen, and ad tech companies, which is then sold to TV networks and ad agencies for its ability to track TV viewership, support control/exposed experiments, and inform the creation of custom audiences, and all data is securely anonymized by a third party.
Why You Need It:
STB data is often used to supplement Nielsen Panel Data so marketers can target beyond age and gender. STB can be overlayed with ACR data to determine if viewership data was from a linear airing or not. Modeled STB data can provide the basis for juxtaposing those who were exposed on linear with those who were exposed on digital, including CTV. Linking STB households to digital exposures via a hashed email or IP address can enable the measurement of linear-digital overlap, or incremental reach.
These organizations serve a variety of market needs, from evaluating consumer credit-worthiness, to providing advanced audience segmentation solutions for advertisers. This type of in-house transaction data, often combined with other proprietary consumer datasets, can serve as the basis for far reaching identity graphs that can be factored into sophisticated multichannel campaigns.
Why You Need It:
Credit Bureau data can help with audience profiling and segmentation based on purchase and transaction history or other indicators, which can then be linked to ACR, STB, and TV Panel Data to really drill down on performance at the strategic target level, regardless of channel. With advances in technology and shifts in how audiences consume content, CTV is benefiting from a growing share of media dollars from holistic campaign budgets. Given the enhanced targeting capabilities that CTV affords, the channel offers a tremendous opportunity to bring custom identity graphs (enhanced with Credit Bureau data) to strategic target audiences at scale.
A bid request is a set of information sent by ad exchanges to advertisers containing inventory details such as platform type, the number of impressions, and keys to user data (IP, pixels, tags, cookies). The most directly valuable bidstream data is GPS or location info. Location data is the only piece of the bidstream that is actively excised and sold separately, typically by app developers or publishers to location data specialists for targeting or attribution. For example, whether a person who saw a Home Depot ad walked into a Home Depot the next day or week.
Why You Need It:
Bidstream is used when digital activation comes into play, and it contains all of the granular impression and user-level metadata that can be used to inform an advanced analytics strategy. It can also be matched with viewership data from ACR and STB to deduplicate performance across linear and digital. The metadata from CTV activation can be used to uncover new audiences and identify areas to promote media efficiency. You can achieve this by identifying which audience segments indexed highly against which media properties, and how segments compare to each other from an in-flight conversion perspective (offline sales, app downloads, etc.). It is also possible to measure the audience exposure overlap between different publishers, so you can shift budget toward incremental reach.
One data partner does not fit all marketer needs
While TV is still bought and sold on the Nielsen Currency and will continue to be, no single data provider is a panacea. They all have limitations, and they all continue to evolve. It’s important to diversify your data sets in the correct way so you can elevate your analytics and strengthen your CTV strategy. Diversifying your data can help you future-proof against unexpected market conditions, especially as the industry undergoes systemic change in how identity is defined and traded against. You can achieve this by either partnering directly with the data provider, or by teaming up with a data expert to focus on reach incrementality and strategic audience targeting that combines and maximizes the data sets that can target the most valuable eyeballs across CTV and linear TV.
For more information on Amobee’s comprehensive data solutions that solve for a variety of programmatic trader, brand strategist, and TV investor needs, contact us at email@example.com.
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