Open Programmatic Revenues increase through user-level dynamic floor pricing

Since I joined Unidad Editorial in 2023, one of my key priorities has been improving programmatic revenues. In an increasingly competitive market where every impression counts, leveraging technology and rethinking traditional strategies have been essential. Over the past year, we’ve implemented significant changes to our open programmatic strategy, and the results speak for themselves: a 6% increase in revenue year-over-year, even while our peers faced a 7% decline.

One of the cornerstones of our success has been the adoption of user-level dynamic floor pricing, a shift that has allowed us to maximize the value of each impression by tailoring pricing in real time to user behavior, demand patterns, and contextual variables. This approach has led to notable improvements in key metrics: while our sold impressions fell 10%, this decline was smaller than our competitors' 12% drop, and more importantly, our CPMs grew by 20%, far outpacing the 5% growth achieved by peers.

Let me share how this transformation unfolded, the challenges we faced, and why this approach is the future of open programmatic advertising monetization for publishers.

The Inefficiencies of Traditional Floor Pricing

Floor pricing has always been a critical component of programmatic advertising, acting as the baseline price at which a publisher is willing to sell an impression. For years, many publishers relied on static or generalized floor pricing rules set within ad servers. These rules often applied uniform prices to broad audience segments or inventory categories.

The problem with this approach? Inefficiency. Static floor pricing doesn’t account for the nuanced value of each ad impression. For example, an ad request for a high-value user with strong engagement metrics might fail to sell because the floor price was set too high. On the flip side, impressions for low-value users could be sold below their true worth.

Every unsold impression due to an overly high floor price represents an opportunity cost for the publisher—a loss that publishers can no longer afford in today’s competitive landscape.

This inefficiency has been exacerbated by changes in the market. The shift from second-price to first-price auctions has stripped publishers of an important lever to optimize CPMs. In second-price auctions, advertisers would bid their maximum, but only pay slightly above the second-highest bid. With first-price auctions, advertisers now know the publisher’s floor price from the bid request, enabling them to bid strategically and often just meet the floor, reducing revenue potential.

To address these challenges, it became clear that a more dynamic, user-level approach to floor pricing was necessary.

The Case for User-Level Dynamic Floor Pricing

At Unidad Editorial, we recognized that the key to unlocking greater programmatic revenue lies in understanding the unique value of each user and impression. A one-size-fits-all approach was no longer viable. Instead, we’ve implemented a system that adapts floor prices in real time, tailored to each user’s attributes and the demand conditions of the market.

This system considers a wide range of factors, including:

• Viewability: Ads that are more likely to be seen by users carry higher value.
• User frequency: The number of times a user visits our websites directly influences their monetization potential. High-frequency users often hit ad frequency caps, reducing their value in the evening compared to the early hours of the morning.
• Time of day and day of the week: Prime time for websites differs from TV. For publishers, the most valuable time is often early in the morning when user ad exposure is low, while user value tends to decline later in the evening as frequency capping is reached.
• Historical demand data: By analyzing past demand patterns for each user, we can better predict and set optimal floor prices. This includes understanding demand holistically across Google, Header Bidding, and Amazon.

This granular, data-driven approach enables us to dynamically adapt floor prices for every ad request, maximizing the value of each impression while minimizing the risk of unsold inventory.

The Role of Technology in Real-Time Optimization

Technology has been the driving force behind this evolution. By investing in advanced algorithms and real-time data processing systems, we’ve developed a platform that can analyze vast amounts of data and adjust floor prices on the fly in a secure and privacy-compliant way.

One of the most impactful outcomes of this shift has been the introduction of real-time dashboards in our daily operations. These dashboards provide immediate insights into the performance of our strategies, allowing us to measure the impact of any changes within minutes. This real-time feedback loop has accelerated the pace of improvements and enabled us to optimize monetization faster than ever before.

For example, if a new floor pricing rule results in a dip in fill rates, we can quickly identify the issue and adjust the parameters, minimizing revenue loss. This agility has been critical in maintaining our competitive edge.

Results That Speak for Themselves

The implementation of user-level dynamic floor pricing has yielded remarkable results:

• Revenue growth: Our open programmatic revenues increased by 6% year-over-year, even as the market declined, giving us a 13% edge on our peers.
• CPM growth: Our CPMs rose by 20%, compared to just 5% growth among our peers.
• Smaller declines in impressions: While our sold impressions fell by 10%, this decline was less severe than the 12% drop experienced by competitors.

These results demonstrate the power of prioritizing high-value impressions, even at the expense of slightly lower fill rates. By focusing on quality over quantity, we’ve been able to achieve sustainable revenue growth and set ourselves ahead from the competition.

Looking Ahead

As the digital advertising landscape continues to evolve, publishers must adapt to stay ahead. The days of static floor pricing are over. The future lies in personalization, adaptability, and data-driven decision-making.

At Unidad Editorial, we’re already exploring the next frontier of programmatic innovation. By integrating additional contextual signals—such as page content and ad formats— as well as AI -essentially neural networks- into our pricing models, we aim to further enhance our ability to capture the full value of each impression and translate these enhancements into lower advertising pressure on each user, altogether removing dynamically unsold ads from the page.

A Call to Action for Publishers

To my fellow publishers: it’s time to rethink your approach to programmatic monetization. User-level dynamic floor pricing has the potential to transform your business, delivering sustainable revenue growth even in a challenging market.

Invest in the technology and talent needed to make this shift. And most importantly, embrace the power of data to unlock the true value of your inventory.

At Unidad Editorial, we're proving that this approach works. By focusing on innovation, adaptability, and user-level insights, we’ve not only increased our revenues but also positioned ourselves as leaders in the programmatic space.

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