Welcome to the era of the cookieless world, where the landscape of digital advertising is undergoing significant changes. With the imminent phase-out of third-party cookies, the role of first-party data is becoming increasingly crucial. In this article, we’ll delve into how advertisers are navigating this shift and harnessing first-party data to fuel retargeting campaigns effectively. Let’s take a look at innovative solutions like OBTD (Outcome-Based Turtledove) and delve into practical use cases and technical details in this evolving digital ecosystem.

In this article, you will learn:

• The significance of first-party data in a cookieless environment.
• How OBTD enables effective use of first-party data in retargeting campaigns.
• The role of Deep Learning in maximizing the potential of first-party data for personalized retargeting.

Importance of first-party data

In ecommerce, where transactions and interactions are inherently digital, the collection and analysis of user data are crucial. This data, whether derived from online activities or combined with offline interactions, forms a powerful tool for enhancing customer experiences and tailoring offers to individual users. However, the approaching phase-out of third-party cookies raises questions about the future use of this rich data.

Furthermore, the shift toward privacy-friendly advertising is not only limited to the phase-out of third-party cookies in Google Chrome. A much broader change is unfolding, with numerous changes introduced in the regulatory and technical environment, cutting down on many additional practices e.g. fingerprinting. All these changes are leading to what is called “signal loss.” With fewer signals available, the value of advertiser’s first-party data becomes increasingly significant, especially for retargeting campaigns, which increases the importance of whether it will be possible to tap into this valuable data in the future.

OBTD as a solution for harnessing first-party data in Privacy Sandbox

In response to the challenges posed by the upcoming cookieless future and recognizing significant value in utilizing first-party data, RTB House designed a forward-thinking solution: the Outcome-Based Turtledove (OBTD). OBTD was first proposed by RTB House in 2020. It has been accepted by Google in its entirety and finally deployed to Chrome’s Privacy Sandbox.

For the first time, the outcome-based approach allowed a new point of view for microtargeting prevention. Instead of restricting the signals used for bidding purposes, it focused on analyzing and validating the outcome from the auction.

This approach allowed the use of user-level data while still adhering to the most stringent privacy requirements. OBTD boosts the efficiency of retargeting campaigns by facilitating the usage of advertisers’ first-party data to allow for better message personalization and making more informed bidding decisions. And all of this is in a cookieless, privacy-friendly environment.

Technical details

Interest groups, as defined by Protected Audience API, are in fact small data structures that allow for keeping not only the interest group’s name and owner but also multiple additional data. OBTD allows, among others, the use of these fields to store additional user information passed directly from the advertiser.

What’s more, this user-specific information is kept either on the user’s device or on the trusted server, that means it is neither in DSP’s nor in SSP’s database, respecting user’s privacy and legal requirements. Some of this information can even be updated in real time, allowing the campaign to correctly operate in a limited data access environment. During the PA API auction, this information is shared only with the bidding algorithm to allow it to make proper bidding decisions. The bidding algorithm itself is also stored on the outside server; therefore no third party can access granular user’s data.

Practical use case of OBTD

Let’s take an example: there is an interest group for users who are interested in books. Even though they belong to the same interest group, they’re not the same.

User A reads one novel from time to time and buys a few new books once every 2-3 months but visits the bookstore often to check the novelties. The average order value for user A is $50.

User B buys books for the whole family, and they’re all bookworms. The average order value for this user is $200, and they buy often. They are interested in both adult series and children’s literature.

In our example, not only do the interests of both users differ significantly, but the conversion value and conversion rate make them different from each other. Obviously, the bid value for user B should be higher than for user A. How do you handle it without cookies?

OBTD provides technology that allows RTB House to use first-party data delivered by the advertiser and make the user’s probability of conversion and predicted conversion value available for the bidder to evaluate the user correctly during the auction.

OBTD allows for advanced targeting scenarios

In more advanced scenarios, the bookstore could pass multiple pieces of information about specific user’s online behavior or offline visits to enrich their profile. For example, they may pass the information on whether the user placed an order with in-store pickup and tailor the advertising message to present offline promos and discounts.

OBTD enables addressing first-party data usage needs for cookieless retargeting campaigns, mimicking nearly all anticipated user targeting functions within a privacy-safe environment. At RTB House, this feature is already fully implemented and working. We are already running the first live campaigns using the advertiser’s first-party data for user targeting in the cookieless environment.

Deep Learning unleashing the full potential of first-party data

Capability to leverage first-party data in retargeting campaigns in a cookieless world is only half of the battle. At RTB House, we understand that the analysis of first-party data is only as powerful as the technology behind it. Our advanced Deep Learning algorithms offer a significant edge, extracting more insightful and actionable information from first-party data compared to traditional analysis methods. This approach allows for a more sophisticated analysis, identifying subtle patterns and preferences in customer behavior. Furthermore, instead of developing new algorithms, we’re adapting the tried-and-tested algorithms we’ve successfully used for years, tapping into our vast experience and harnessing it to a new cookieless landscape. It all translates into very effective and personalized retargeting campaigns, even in the absence of third-party cookies.

Our mastery of OBTD and the superior capabilities of our Deep Learning technology put us at a distinct competitive advantage. We can unlock the full potential of first-party data, not just for bid valuation but also for ad personalization, even in an omnichannel context.

Join us to future-proof your retargeting

RTB House is at the forefront of digital marketing innovation, offering advertisers future-proof retargeting strategies in a cookieless era. By partnering with us, you gain access to our cutting-edge solutions, including OBTD and ContentGPT, backed by our advanced Deep Learning technology. This ensures that your retargeting is not only effective and relevant, but also compliant with the evolving digital landscape.