Measurement is at the heart of digital marketing. It is imperative that we can show the direct link between an ad served and the desired action, whether it is the capture of the lead or even the purchase of a product. This is how marketers demonstrate the ROI achieved.
Currently, third-party cookies (which allow customers to be tracked across different websites & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & 'but this is a very busy scenario: we recently saw Google backtrack on the end of third-party cookies in Chrome, an initiative that has been hotly debated in recent years and was, since January 2024, in the initial tests with the market.
The proposal now is not to interrupt the use of third party cookies, but to offer the user more autonomy in the choices about them. This is just one of the important changes that are happening and that will make it more challenging for professionals in the field not only to measure campaigns but also their segmentation.
Using AI in Retail Media
I recently read one research with advertisers in the consumer goods industry the vast majority of respondents are ready to adopt AI for targeting, serving relevant ads to customers, and other aspects of advertising.
Because Retail Media covers the complete customer journey, including the final decision moment, when shoppers are on retailer digital channels or in-store, we can understand that using AI to connect with customers during this crucial time of the journey can give advertisers a great competitive advantage.
The study in question shows that 45% of respondents believe that AI will help in the analysis and leverage of buying behavior. But it is important to remember that human analysis will continue to be fundamental throughout the process.
Other relevant survey data refer to other challenges faced by advertisers: 54% considers AI crucial for seamless integration of online and offline data; 29% considers AI useful but not essential as other tools can do data integration; and yet, 15% have privacy concerns regarding AI integrations.
Thus, it is important to understand the complexity of analyzing and using buyer data, especially when there is the intersection of e-commerce and physical store data.
The end & the back & forth of support for third party cookies
In recent years, the market has strongly discussed the decision of Google to end the use of third-party cookies in its browser, Chrome. Although Firefox and Apple have already made this decision for some time, the biggest impact is in Chrome (at the time this article was written, the browser holds the share of 65% in the world market. However, in July 2024, the company decided again to change course: maintain the support for cookies, but offer the user more control over them. It is still not very clear how this will work, but it is a decision that brings great impact to 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 we are seeing for more privacy will continue to grow in the coming months and years. This, of course, means that advertisers need to invest in evolving 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, allowing the capture of advertising media indicators and subsequent measurement of the sales performance of a campaign without the need to use third-party cookies. This is what RelevanC has been doing, combining Google DSP platforms with transactional data and producing sales indicators relevant to customers.
By linking ADH together with our own data, we can now reconcile online advertising with first-party in-store sales data, enabling us to analyze how many people saw a particular ad, while crossing that 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 ad on 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 respect privacy checks, for example, the result will not be accessible.
ADH allows the use of various data sources, such as Display Video 360 (DV360) and Google Ads, and this data contains information such as who viewed an ad and when. Thus, it is possible to see how many people viewed that specific ad that day, but we can not 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 worth noting that it is, yes, possible to help advertisers keep their investments in profitable and continuous Retail Media strategies. In addition, of course, to measure and palpably show the result of campaigns. And it is important to note: strategies that follow data usage regulations and keep consumer privacy protected are a priority!
