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How publishers can use predictive audiences to grow revenue

Predictive audiences, models based on behavior rather than attributes, offer publishers multiple paths to increased and sustainable revenue.

May 28, 2024 | By Danish Ahmed, Director of Product Management – Nativo@nativoinc

Publishers have faced intense headwinds in recent years when it comes to protecting and growing revenue streams. However, there are some equally powerful tailwinds that the industry needs to acknowledge and embrace to put publishers on a viable path forward. Perhaps the most significant one is predictive audiences

Predictive audiences, supercharged by growing AI capabilities, offer publishers multiple paths to increased revenue. Even more importantly: sustainable revenue. Let’s explore why that is, and the ways in which publishers can incorporate these capabilities into their monetization plans. 

A sustainable path within a landscape of crumbling identifiers

When Google announced its latest stay of execution for third-party cookies, some publishers breathed a(nother) sigh of relief. Third-party cookies have long been seen as an understood path to revenue thanks to their role in enabling cross-site ad targeting. However, this capability has been in decline for years. In fact, the reach and accuracy of third-party cookies has become increasingly limited. 

Publishers don’t need a replacement for third-party cookies. They need something altogether better. And that’s where predictive audiences come in. By fueling growth based on the strength of a publisher’s first-party data, predictive audiences offer a path to revenue that’s both in a publisher’s control and can be strengthened over time. 

The premise behind predictive audiences for publishers is fairly simple: By taking a publisher’s first-party data (i.e., everything the publisher knows about its audience), the publisher can build models capable of predicting likely behavior in current and potential new users. These predictions can be used to create better user experiences while simultaneously opening more and deeper monetization opportunities.

Here are a few areas where predictive audiences’s power to help publishers drive revenue has become most evident. 

Growing ad dollars

For many publishers, the fastest path to revenue growth is to look beyond their sites to find additional high-value inventory for their advertisers. By using their audience data as seed data, publishers can leverage predictive audiences to identify users beyond their own walls who are likely to behave like their known audiences. Working with external partners, a publisher can make these models and their resulting segments available for advertisers on demand as an extension of their audience. 

Growing Yield

Predictive audiences can also be leveraged to greatly help publishers make more from their inventory within their walls. By combining first-party data with contextual and engagement signals, publishers can fuel robust data models that predict which ads will perform best when served to a given audience. Such an approach tends to deliver far more relevant results than can be achieved with third-party data, enabling publishers to improve the yield on their inventory. Such models can also fuel ad personalization that drives better results for advertisers and higher premiums for publishers.

Growing Audience

Beyond direct revenue, publishers can also tap into predictive audiences to grow their user base. Such growth helps expand their first-party data assets and inventory, driving greater revenue downstream. The mechanisms for fueling audience growth are similar to those for driving more ad dollars: Publishers can model their data to help them predict the behavior of unknown users. By activating that data, they can drive interested audiences in hopes of converting them to loyal visitors. 

A bright future paved with predictions

The ability of these predictive audience strategies to drive publisher revenue has a lot to do with the level of first-party data the individual publisher brings. Of course, not all publishers are on equal footing when it comes to first-party data assets. Some have been capturing and building their first-party data practices for years, enabling them to fuel strong predictive models and broader identity graphs that can reach across their properties. Others—publishers that have not invested nearly as heavily in their first-party disciplines—are looking for off-the-shelf solutions that can help them take advantage of predictive audiences’s power all the same. 

The AI-driven future will favor publishers that prioritize robust first-party data practices, but the race is far from over. Regardless of where an individual publisher stands with its first-party data assets, there’s still time to build out the needed strategies that can fuel growth through predictive audiences. By doing so to capture the right data and signals to fuel the strongest models, publishers can chart a more sustainable (and monetizable) path forward.

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