For programmatic advertisers, the ability to reach the right audience with the right message is crucial to the success of any campaign. In order to do this effectively, advertisers rely heavily on their data to access their target audiences. However, the value of audience data is only as good as the quality of the data being used.
In this blog post, we will explore the importance of data quality for targeting digital advertising, as well as the value of quality audience data in targeting social and connected TV (CTV) campaigns.
Why is Data Quality Important for Ad Targeting?
Inaccurate or incomplete data can lead to poorly targeted campaigns, wasted ad spend, and ultimately, a lower return on investment (ROI). Bad data costs the U.S. $3.1 trillion each year according to IBM. Low returns on ad spending, wasted sales time and poor ad performance are casualties of data that’s incomplete, obsolete, misplaced, or just plain fake.
Success for a given campaign depends on avoiding these bad sources and maintaining a high-quality data pool. For example, if a programmatic advertiser is targeting a specific age group but the data is inaccurate, the campaign may end up being served to people outside of the intended age range. This can result in a lower click-through rate (CTR), lower conversion rate, and ultimately, a lower ROI.
In addition to accuracy, data quality requires completeness and consistency of datasets being used to target campaigns. Incomplete data can lead to gaps in audience targeting, while inconsistent data can lead to conflicting information that makes it difficult to determine the most effective targeting strategy.
Now that we understand the importance of data quality for ad targeting, let’s explore the value of quality audience data in ad targeting for both social and CTV.
Social media platforms like Facebook, Instagram, and Twitter offer advertisers a wealth of targeting options based on audience demographics, interests, behaviors, and more. In order to effectively target audiences on social media, advertisers need quality audience data that accurately reflects the behaviors and interests of the intended audience on the platform.
One way advertisers can access social audiences is through a process called “lookalike targeting.” Lookalike targeting allows advertisers to expand their reach and target people who are similar to their existing customers or website visitors. In order for lookalike targeting to be effective, the data used to create the expanded audience must be accurate. It’s helpful if this data is first-party data that comes directly from existing customers, so the new audience will share similar characteristics to the existing base. If the data used to create the lookalike audience is inaccurate or incomplete, the resulting audience may be vastly different from the advertiser’s existing audience, which could result in poor ad performance.
Advertisers can also target social users through interest targeting. Interest targeting allows programmatic advertisers to target people based on their hobbies, activities, or lifestyle choices. In order for interest targeting to be effective, the seed data should be first-party, deterministic data so advertisers know the audiences they’re targeting are the audiences they aim to reach.
Connected TV (CTV) Advertising
Connected TV (CTV) advertising has become increasingly popular in recent years as more people move away from cable and migrate towards streaming services like Netflix, Hulu, and Prime Video. CTV advertising allows marketers to reach highly engaged audiences in a brand-safe environment, but it also requires quality audience data in order to effectively target those audiences.
Device targeting is one of the best ways to illustrate the value of quality audience data for CTV. Device targeting allows advertisers to target specific devices, such as smart TVs, streaming devices, or gaming consoles. For optimal performance, the seed data used to target audiences must accurately reflect the devices being used by that audience. This is why BDEX uses exclusively deterministic data as opposed to probabilistic data. Deterministic data helps ensure the devices advertisers are targeting are correct by drawing known linkages to an identity, instead of guessing that the device is connected to a given identity.
Geographic targeting is another way CTV advertisers can target specific geographic regions, such as cities, states, or countries.
BDEX Identity Graph
Using vetted data quality tools, such as the BDEX Identity Graph, is one of the best ways marketers can ensure they’re using the most accurate, comprehensive and reliable data to target their campaigns. The BDEX Identity Graph allows advertisers to track data tied to any identifier, without relying on outdated, blockable tools like cookies. Identifiers BDEX tracks include valid hashed email addresses (MD5) and Mobile Advertising IDs (MAIDs), which work across multiple platforms and enable advertisers to track and connect mobile activity to individual users.
Using these personal identifiers, BDEX connects location history, news sources, website visits, purchases, and more with the right consumers, ensuring the data programmatic advertisers receive is correct every time.
Learn more about how to improve data quality and improve return on ad spend (ROAS) with the BDEX Identity Graph here.