Blog about Digital Advertising & Marketing Technology

On April 18th, Google published the results from Google Ads’ interest-based advertising testing, where, among other tools, Topics API was analyzed. We are happy that the Google Ads team joined RTB House and Criteo in openly publishing findings from experiments with Privacy Sandbox APIs.

In the report, the Google Ads team compares the effectiveness of applying Topics API, contextual signals, and publisher first-party IDs instead of cookies for Interest-Based Advertising (IBA). Third-party cookies were allowed in this experiment for use cases unrelated to targeting, such as frequency capping and measurement.

The cookieless future is fast approaching, and this means that brands need to rebuild their marketing strategies around alternatives to third-party cookies. Navigating this new environment will require mastering a suite of tools, including another type of cookies: first-party cookies.

To understand how you can make the most of first-party cookies, let’s dive into what they are, how they work, and how advertisers use them.

People are bombarded with thousands of ads every day, both offline and online. With the growing popularity of ad-blocking, it’s clear that they are looking for ways to reduce the number of ads shown. One of the big challenges is that most of this ad content is irrelevant to users. This article will explain how AI technology can help advertisers to deal with it and to improve campaign performance with more precise targeting through Deep Learning.

In this Media Review, you can read 6 stories, including big tech antitrust update, Meta letting users opt out of some targeted ads (and only in selected countries), and ramping the FLEDGE origin trial back up and launching isolated experiments.

Everyone loves a good challenge, but some are tougher to tackle than others. For marketers, the big one is the personalization paradox. 71% of consumers prefer personalized ad content, but 74% are also concerned about how advertisers are actually using their personal data. This creates a problem for marketers. They want to reach out to their customers with personalized content but often rely on tracking technologies that are considered invasive. Fortunately, there is an answer to this particular paradox. Brands can use data-driven strategy to leverage large anonymized datasets that provide rich personalization at scale without compromising on privacy.

On March 7, 2023, Publicis, one of the world’s largest marketing and communications organizations, welcomed RTB House experts for a seminar centered on Deep Learning-powered campaign solutions. The well attended event took place in Seoul and was presented by members of the RTB House Korea Sales, AM and Inventory team, Josh Jang, Jieun Yang, Taekyung Kim, and Semi Hong.