The post-cookie era of digital advertising is approaching. Google may have postponed its plan to remove third-party cookies, but the result remains the same: industry players must prepare for a huge amount of industry upheaval. Most notably, there will be a significant drop in data availability.

Publishers – with direct access to audiences and first-party data – are widely acknowledged as being best-placed to survive in the ecosystem’s data-frugal future. But having valuable first-party data at their fingertips won’t be enough for them to flourish. Moving forward, publishers must discover new ways to optimize their offerings, enhance their monetization strategies, and heighten the value of the user experience.

With technology powered by artificial intelligence (AI), publishers can harness the capabilities needed to become digital advertising’s main providers of quality, first-party data. They will also be in a position to build of scalable, privacy-safe data solutions. By combining the power of AI with valuable first party data, publishers have a significant competitive advantage.

AI helps publishers leverage their pair of aces

Publishers were already holding a pretty good hand, with content and consent their figurative aces. Publishers build trust among their regular users by generating high levels of audience engagement and loyalty through the production of editorial content. This, in turn, helps them earn consent from logged-in users to gather and use their first-party data.

Publishers’ first-party data strategies, therefore, give them a solid basis to achieve reach with known audiences. However, it is broadly acknowledged that consented data has its limits. At best, only one in 10 users are willing to share personal information, such as age and gender. However, almost a quarter (23%) are reluctant to do so regardless of how it could improve their online experience.

Consequently, optimizing reach beyond known users relies on publishers taking different approaches to data, aside from adopting log-in walls. To increase the effectiveness of their strategies, data processing and enrichment solutions driven by AI and machine learning are vital. Publishers looking to preserve the availability of their online content will find these especially advantageous. But all publishers stand to gain from their benefits.

Predictive modeling is one of the most valuable capabilities made possible by machine learning. The removal of third-party cookies will make deterministic data less accessible. However, with consent, publishers can leverage their logged-in user attributes as a robust analytical base for predictive models. These models then allow publishers to extend addressable reach with accuracy. This helps them target unknown audiences that exhibit similar attributes to their logged-in users.

The quality of these predictive models is also very high. For example, Ad Alliance – Germany’s number-one advertising sales house – achieved 70% market reach in a campaign for e-commerce company, OTTO (up from 32% for standard run of network campaigns), with 92% accuracy in age segment targeting.

Contextual is the trump card

To boost reach and engagement even further, publishers can also feed real-time contextual insights into their data solutions to enable privacy-friendly targeting. Contextual analysis upholds user rights to data privacy by utilizing inferred characteristics rather than declared ones.

AI technologies accurately predict audience preferences based on the content they consume. This information can then be used to personalize targeting and the user experience. For example, French publisher, Le Figaro, utilized 1plusX’s real-time audience targeting, contextual targeting and first impression targeting solutions to strengthen relevance, maximize impact, and enhance the user experience, all while adhering to data privacy regulations.

Bringing users’ content consumption into the mix, publishers can then use advanced AI analytics to develop precise, interest-based audience segmentation. This further improves targeting capabilities, resulting in stronger alignment between ad content, editorial content, and user intent. By leveraging data enrichment and machine learning capabilities on top of its contextual targeting tool, Le Figaro was able to deliver precise targeting solutions to connect with first-time users. As a result, the publisher generated an average campaign reach increase of 38% across campaigns from all verticals.

Publishers play a key role in shaping how the ecosystem accesses and uses first-party audience data sets. But simply being the gatekeepers of user data won’t give them the competitive edge they need. AI-powered solutions allow publishers to support privacy-centric advertising and optimize their own revenue streams.

With the enhanced capabilities of predictive modeling, publishers can make the most of their consented data and expand their reach to unknown audiences with a high degree of accuracy. By combining this with contextual data, they can deepen the personalization of the user experience and maximize the effectiveness of targeting methods with heightened relevance. Thanks to AI, publishers can ensure they have the optimal solution to identity challenges in the post-cookie era.