Go beyond viewability to understand the true value of your readers
At first glance, the looming loss of third-party cookies in 2023 seems like a devastating blow to publishers and advertisers alike. Today’s programmatic ecosystem runs on third-party data, so without cookies there isn’t a universal way to identify and authenticate users across the internet. Industry reports predict billions of dollars in lost advertising revenue and huge revenue declines for publishers.
But there’s another side to the story. In the current ad marketplace, ad buyers hold all the cards when it comes to ad pricing. But without third-party cookie IDs, publishers will no longer be forced to sell to the highest bidder. Instead, they will be uniquely positioned to identify, target, and sell highly desirable audience segments hosted on their own sites. For those who can get out ahead of the coming changes, there is a real possibility that the balance of power in the advertising marketplace can be shifted back to publishers.
This idea is foundational to our new ebook, Capturing the Signals: How Reader Attention Can Drive More Revenue. Here’s a quick preview of what you’ll learn.
How publishers can take back control
For years, viewability has been the industry standard for predicting ad performance. This metric is intended to measure the likelihood that an ad will be seen by users, based on whether it is visible on the page. The problem is, viewability fails to consider whether the ad is actually seen or noticed by the reader.
Metrics like viewability and viewable time don’t provide deep insights on audience engagement, so Sovrn has devised a new measure of attention called “engaged time,” which empowers publishers to leverage deep, proprietary insights about their readers. With these insights, you can better broadcast the value of your audiences to advertisers and drive more revenue from your ad inventory.
To take advantage of this opportunity, however, you will need the tools to identify, target, and broadcast your high-value audience segments. The right tool will give you the power to understand three things:
- How engaged audiences are with your content
- How much time they spend with your content
- The type of content they engage with
3 ways to tap into engagement signals
The most valuable audience segments are those paying the most attention. Now you can convert that value into earnings with Sovrn Signal, an easy-to-use publisher data tool.
With just a single line of code, Signal lets you measure, compare, and monetize your engaged reader base — ultimately driving greater ad value. Here’s how:
1. Measure and benchmark ad performance
It can be challenging to get a holistic view of your ad inventory performance. Signal provides a granular breakdown of the metrics buyers use to evaluate your ad inventory, and lets you compare your ad performance against both your peer group and the market as a whole.
2. Predict performance to optimize pricing
Publishers seldom have access to the same types of data ad buyers use to predict ad performance. With Signal, you can automate inventory segmentation; generate granular predictions using KPIs like viewability, engagement, and click-through rate; and accurately price your most valuable ad properties.
3. Increase revenue from engaged users
Publishers who create rich, unique user experiences should reap the benefits of audience attention, but the current ad ecosystem isn’t structured that way. As engaged readers view your content for longer periods of time, Signal’s market-leading reload solution unlocks new revenue by generating additional incremental impressions per ad unit.
Get the ebook to learn more
We’ll dig deeper into how Signal works — and what you can do to get started — in a future blog post. You can also download the complete ebook, Capturing the Signals: How Reader Attention Can Drive More Revenue, for more information about how Signal can help you maximize the value of your engaged audience.
Ready to see Signal in action? Contact us at email@example.com and our team will be happy to provide a demo.