Measurement is at the center of digital marketing. It is essential that we can demonstrate the direct link between an ad served and the desired action, whether it is lead capture or even a product purchase. This is how marketing professionals demonstrate the achieved ROI.
Currently, third-party cookies—which allow clients to be tracked across different websites—are the tool that enables the measurement and effectiveness of online advertising and customer segmentation. But this is a very active scenario: recently we saw Google backtrack on the end of third-party cookies in Chrome, an initiative that has been widely debated in recent years and has been in initial testing with the market since January 2024.
The proposal now is not to interrupt the use of third-party cookies, but to give the user more autonomy in their choices about them. This is just one of the important changes happening that will make it more challenging for professionals in the field not only to measure campaigns but also to segment them.
The use of AI in Retail Media
I recently read aresearch with advertisers in the consumer goods industrywhich pointed out that the vast majority of interviewed professionals are ready to adopt AI for segmentation, delivering relevant ads to clients, and other aspects of advertising.
Since Retail Media covers the entire customer journey, including the final decision moment when buyers are in the retailer's digital channels or in the physical store, we can understand that using AI to connect with customers during this crucial moment can give advertisers a significant competitive advantage.
The study in question shows that 45% of respondents believe that AI will assist in analyzing and leveraging purchasing behavior. But it is important to remember that human analysis will continue to be fundamental throughout the entire process.
Other relevant data from the survey refers to other challenges faced by advertisers: 54% consider AI crucial for the seamless integration of online and offline data; 29% consider AI useful but not essential, as other tools can perform data integration; and 15% have privacy concerns regarding AI integrations.
Therefore, it is important to understand the complexity of analyzing and using buyer data – especially when there is a crossover between e-commerce and physical store data.
The end – and return – of third-party cookie support
In recent years, the market has been strongly debating Google's decision to end the use of third-party cookies in its Chrome browser. Although Firefox and Apple have already made this decision some time ago, the biggest impact is on Chrome – at the time this article was written, the browser holds a 65% share of the global market. However, in July 2024, the company decided to change course again: to maintain support for cookies but to give users more control over them. There is still not much clarity on how this will work, but it is a decision that has a significant impact on online advertising.
Regulations such as GDPR (in Europe), CCPA (in California), and LGPD (here in Brazil), for example, are here to stay, and the pressure for more privacy will continue to grow in the coming months and years. This, of course, means that advertisers need to invest in the evolution of their processes and adopt innovative approaches to maintain effectiveness and monitor the impact of their campaigns.
Thanks to the new partnership with Google and its Ads Data Hub (ADH), the market can develop solutions to address these challenges, enabling the capture of advertising media indicators and subsequent measurement of a campaign's sales performance without the need to use third-party cookies. This is what RelevanC has been doing, combining Google's DSP platforms with transactional data and producing relevant sales indicators for clients.
By linking the ADH together with proprietary data, we can now reconcile online advertising with first-party in-store sales data, enabling the analysis of how many people saw a particular ad while cross-referencing this impacted audience with buyers of a similar or tangential product. With this level of information, we can provide relevant indicators to analyze the impact of an advertisement on the sales of a product or similar categories.
One of the main points of solutions that use only aggregated and anonymized data is that Google ADH ensures that customer privacy and regulations such as GDPR or LGPD are respected, preventing the inspection of personally identifiable data. If a calculation submitted to ADH does not comply with privacy checks, for example, the result will not be accessible.
The ADH allows the use of various data sources, such as Display Video 360 (DV360) and Google Ads, and these data contain information such as who viewed an ad and when. Thus, it is possible to determine how many people viewed that specific ad on that day, but we cannot identify the individuals involved.
By providing retailers with the ability to reconcile advertising exposure with sales data, as well as direct customer segmentation without the use of third-party cookies, it is indeed possible to help advertisers maintain their investments in profitable and continuous Retail Media strategies. Besides, of course, measuring and visibly demonstrating the results of the campaigns. And it is important to emphasize: strategies that follow data usage regulations and keep consumer privacy protected are a priority!
