Google has unveiled a series of new technologies which aim to enhance programmatic advertising by adopting a multi-signal approach to building audiences in Display & Video 360. The introduction of these technologies has been motivated by a desire to safeguard user privacy, increase the resilience of programmatic advertising through the utilization of an array of audience technologies, and enhance the utility of programmatic advertising through the provision of greater accuracy, scalability, sophistication, and accessibility than cookies or alternative IDs.

A key focus of these new technologies is the utilization of first-party data. First-party data refers to information that a company has collected about its own customers or users, and its effective utilization allows advertisers to foster direct relationships with their customers, thereby increasing trust. Publishers, meanwhile, can utilize first-party data to serve more relevant ads to site visitors, resulting in increased revenue. Google is supporting programmatic advertising solutions that build upon direct relationships and aid advertisers and publishers in delivering more relevant ad experiences, such as the Publisher Advertiser Identity Reconciliation (PAIR) feature in Display & Video 360. This enables publishers and advertisers to reconcile their first-party data for marketing purposes in a privacy-safe manner, creating first-party audience lists which advertisers can utilize to target their ads more effectively.

In addition to first-party data, Google is also leveraging the power of machine learning to improve programmatic advertising. Machine learning involves the use of algorithms and statistical models to allow systems to automatically improve their performance without explicit programming. Advertisers have long utilized automation and machine learning to handle complex operations at scale and enhance efficiency, and Google is now using machine learning to create “modeled” audience-based advertising solutions that can be tailored to specific audiences and improve the efficiency of ad targeting. Through the implementation of machine learning, Google is able to deliver more personalized and relevant ads to users.

Finally, Google is expanding the use of its own signals to improve programmatic advertising. Google signals are data that the company has collected about users’ online activities, such as the websites they visit and the ads they click on. Advertisers can utilize these signals to target ads more effectively and deliver a more personalized experience to users. Google is making it easier for advertisers to access and utilize these signals through a feature called Audience Sources, which allows advertisers to select from a range of signals to create custom audiences and target their ads more precisely.

Overall, Google’s new technologies for improving programmatic advertising are designed to protect user privacy, increase resilience, and enhance the utility of programmatic advertising for both advertisers and publishers. By adopting a multi-signal approach and leveraging the power of first-party data, machine learning, and Google signals, Google is striving to aid marketers in delivering more relevant and personalized experiences to consumers.