Digital publishers are constantly exploring the behaviors that connect user experiences and digital revenue. They want to better understand what creates a good experience for their website visitors but understand that looking at traditional metrics does not always deliver the granularity required to understand what is actually affecting digital revenue. This is due to a phenomenon known as, Fake UX.
Understanding how authentic user engagement and ad revenue are correlated is critical for premium publishers that want to ensure that investments, changes, and strategies that they employ are beneficial to the long-term health of their web properties. Below, is a single case study that demonstrates a correlation we have recognized between Engagement Analytics and digital ad revenue
The website in this case study is a niche sporting website dedicated to a particular group of fans in a specific geolocation. They recently started using Ezoic in an attempt to enhance overall website speed, user experience, and ad revenue.
To measure their efforts, they choose to evaluate their progress by analyzing Navigation Bounces, Engagement Time, & Engaged Pageviews Per Visit, along with ad revenue per session. They were able to declare their efforts a success due to improvements in all four areas. In doing so, they demonstrated a trend between these particular Engagement Analytics and digital ad revenue.
After implementing automated multivariate testing, this publisher saw a 28% decrease in Navigation Bounces on their website. Navigation Bounces are essentially an internal page bounce. They reflect that a user may have accidentally navigated to the wrong page, found the content on the page they navigated to irrelevant, or been turned away by long load times or annoying ads.
Navigation bounces have been proven to be bad for ad rates; as they lower key advertiser performance metrics like Viewability. A reduction in Viewability has a negative impact on programmatic bids from advertisers that run campaigns based on Viewability.
In addition to a reduction in navigation bounces, this particular website saw a 120% increase in website Engagement Time. Engagement Time is the time that a user spends reading or engaging in the content. This excludes when users are waiting for things to load, in another tab, scrolling, or cycling through navigation features. This provides publishers with a more accurate understanding for when users are actually engaging in their content.
The Ezoic data science team recently uncovered some correlations between Engagement Time and improvements in both ad Viewability and Click-Through-Rate (CTR). This publisher was able to see the exact same correlations.
One of the interesting phenomenon’s of Fake UX is that pageviews can often be artificially high due to navigation bounces; resulting in lower ad rates. Advertisers start to bid less over time for ad space that offers poor campaign performance (i.e. are users engaging with the ads on this page and actually completing the advertiser’s desired action)?
This is the reason why publishers are starting to look at Engaged Pageviews Per visit. This offers insight into how many pageviews visitors are accumulating that have a minimum threshold of Engagement Time per pageview.
This publisher increased Engaged Pageviews Per Visit by 56% following the implementation of automated multivariate testing and was able to tie these improvements to increases in landing page ad rates.
Ultimately, these engagement metric improvements had a direct correlation to a 29% increase in session earnings, or EPMV (earnings per thousand visitors). This publisher calculated how much ad revenue they were generating on a per session basis to ultimately determine if the enhancements in visitor engagement actually correlated to more revenue from digital ads.
This provided a clear cut view of how the website was performing financially as these user experience metrics were improved. In particular, the direct correlation between Navigation Bounces and Engaged Pageviews Per Visit and Advertiser campaign KPI’s that directly relate to programmatic bidding, and how these improvements result in higher publisher EPMVs.
The primary driver for these improvements on this publisher’s web property was the implementation of automated website testing. This allowed them to deliver every user a personalized ad or layout experience based on look-a-like user behavior data. This ultimately resulted in better experiences for visitors; as they saw preferred layouts or ad combinations.
By delivering visitors preferred experiences, this publisher saw improvements in website engagement indicators and also digital ad revenue. Furthermore, it wasn’t just total revenue that was increasing. It was EPMV; which shows that the publisher was actually earning more from every session — providing a true north for if they were actually earning more revenue from visitors.
Use Ezoic to implement automated testing on your web property. Split traffic between your current website and the version testing with Ezoic. Measure how visitor engagement is affected and track your EPMV automatically using advanced analytics.