Navigating the Shift to Privacy-Forward Advertising

As Google Chrome prepares to bid farewell to third-party cookies, advertisers worldwide are grappling with the need to adapt to alternative methodologies while maintaining effectiveness and compliance, ushering in a new era of privacy-conscious advertising practices.

Navigating the transition away from third-party cookies demands a multifaceted approach for all parties involved. Advertisers and publishers must actively engage with these solutions and optimize the use and capture of first and zero-party data. Adtech providers—who help advertisers target, deliver and measure their digital ad campaigns—must offer diverse solutions to maintain targeting and personalization capabilities.

Changes for Adtech Providers 

Third-party cookies are a technical feature that much of advertising technology depends on. As such, it is the onus of the adtech industry to change its infrastructure to adopt new privacy-forward solutions.

The largest and most well-known of these efforts is Google’s Privacy Sandbox. The Privacy Sandbox consists of several APIs intending to allow advertising targeting and measurement to occur without the use of third-party cookies. Current tests are focusing on the efficacy of Protected Audience API, Topics API, Attribution Reporting API and Protected Aggregation API, all resulting from years of proposals and testing. [Note: Similar solutions are expected to come from other browsers and adtech providers should be prepared to test and integrate these solutions; most recently, Microsoft Edge announced its initial plans.]

While the Privacy Sandbox is promising, it will not likely provide the same reach and functionality advertisers see today. Adtech providers should also explore new identity solutions to complement the Privacy Sandbox proposals. The two main types of ID solutions are deterministic IDs and probabilistic IDs.

Deterministic IDs are based on personally identifiable information (PII), such as email addresses. Deterministic IDs offer a precise means of user identification, allowing advertisers to deliver targeted ads with a high degree of accuracy. By leveraging authenticated user data captured through zero-party data strategies, advertisers can establish direct connections with their target audience, enhancing the effectiveness of their advertising campaigns. Deterministic IDs also allow publishers with high authentication rates to create and provide publisher-defined audiences.

Probabilistic IDs leverage browser-readable first-party data—like user agent, browser version, IP address, etc.—to create a replicable ID. Because these browser data points change over time, probabilistic IDs will also change over time, limiting the useful life of the ID compared to PII-based deterministic IDs. While probabilistic IDs may offer less precision and longevity than deterministic IDs, they provide advertisers with a solution to targeting and measurement while maintaining privacy without the need to collect PII.

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Changes for Advertisers

While removing dependency on third-party cookies falls largely on adtech providers, there are some changes and steps advertisers can take to prepare by evaluating their adtech stack, focusing on what data is collected and driving an increase in the quality and quantity of data collected.

First, advertisers should familiarize themselves with the above solutions. What are their pros and cons for your advertising needs? For example, suppose your brand is able to capture a large number of email addresses from current and prospective customers. In that case, ensuring a robust approach to deterministic ID activation is necessary. Working directly with your adtech vendors will help to ensure your needs are met or that you can find new partners to help address any gaps found.

To enhance the scope of data collection beyond vendor evaluation, advertisers can strategically leverage both first-party and zero-party data.

First-party data is generated and collected directly from consumer interactions on a company’s owned digital properties, such as their website. For example, e-commerce platforms like Amazon use first-party data to power recommendation engines, tailoring product suggestions based on past purchases and browsing history.

Zero-party data is information explicitly solicited from consumers. It is often identity or preference-based information, such as a retailer site collecting email addresses or a streaming service asking users about their favorite TV genres. When a user provides their email address, it allows the marketer to interact with that person via many channels, including advertising. Preference data further allows marketers to deliver personalized marketing experiences.

Marketers should consider opportunities to increase the amount and quality of zero and first-party data collected. What kind of value exchange can be created to foster a trusted relationship with consumers? Brands that improve their zero and first-party data collection will have more options to provide the right marketing to their audience.

Finally, marketers should also consider non-person-based advertising tactics. If it’s been a while since working with targeting options like contextual targeting, this is a perfect time to start testing and finding what works best for your brand!

What Lies Ahead

Over the coming months, it is imperative that adtech vendors implement and test post-third-party cookie solutions. We in adtech owe it to the industry to rigorously test and share our results with the advertising community and our own customers.

Advertisers need to stay close to their adtech partners’ development work, evaluate whether their planned solutions meet their partners’ specific advertising needs and participate in testing themselves as the opportunity arises. Having the right adtech stack and improving the quantity and quality of the data collected will help pave the path to post-third-party cookie success.

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