Identity resolution algorithms help programmatic advertisers better identify and understand their audiences. However, marketers continue to face problems driving the same ads to target audiences across their various devices.
The multi-device issue has proven problematic for programmatic advertisers when optimizing their identity graphs for ad targeting. Think about all of the devices in your home connected to the internet. The data points produced from these various devices create a monsoon of unstructured data – some valid and some produced by bots.
These issues ultimately net in a partial view of audiences – leading to wasted marketing dollars and poor experiences for customers. However, for advertisers still aiming to improve their data and draw linkages to better understand your audiences, deterministic identity resolution is the best path forward.
Probabilistic vs Deterministic Identity Resolution
Identity resolution is the best way for advertisers to build a cohesive, omnichannel view of their audience. In short, it means building profiles to understand potential customers on an individual basis and improve ad targeting. But there are a number of ways of achieving identity resolution, some more effective than others.
Identity resolution algorithms take unstructured data and attempt to draw linkages between them based on pattern recognition. Even in the best case scenario, these algorithms are using educated guesses to resolve identities.
The use of identity resolution algorithms is also known as “probabilistic” identity resolution. This is because advertisers are guessing at the likelihood of two identities being the same. While probabilistic identity resolution algorithms provide a level of confidence for identity linkages, there is still a margin of error.
This is one of the main reasons programmatic advertisers have shifted their focus to deterministic identity resolution. As opposed to probabilistic, deterministic identity resolution uses first-party data that has confirmed linkages between two identities. Deterministic means that advertisers know for certain that the identities they are targeting across devices are the same.
Why Deterministic Identity Resolution is Better
Bots and click farms produce a lot of digital noise. If left in an identity graph unvalidated, it can cause you to spend money targeting bots instead of people. Deterministic identity resolution aims to suppress this noise.
With deterministic tools like BDEX ID Graph, marketers are able to integrate new data into their existing customer records by searching for matches among identifiers they already have. In the case of BDEX ID Graph, all of the data marketers search for matches in are deterministic rather than probabilistic. As a result, the junk data is removed, and the remaining data used to target ads is validated. This gives advertisers confidence in their identity graphs, knowing that the deterministic data has authenticated and certified the identities.
Unlike the probabilistic approach, BDEX ID Graph’s deterministic approach focuses on the certainty of consumers’ actions rather than assumptions. This gives programmatic advertisers a more precise identity graph thanks to a proof-based approach to identity resolution.
For programmatic advertisers using identity resolution algorithms and probabilistic methods for cleaning up identity graphs, it’s time to explore the certainty that deterministic identity resolution can provide. With validated data, advertisers can be surgically precise in their targeting and help improve return on ad spend (ROAS) by over 40%.
For more on how to un-junk your data with deterministic identity resolution, read about BDEX ID Graph here.