Understanding the intricate connection between user engagement and ad revenue is crucial for digital publishers striving to optimize their web properties. Traditional metrics often fall short in providing the detailed insights necessary to foster genuine user engagement and drive revenue. This article delves into the correlation between authentic user interactions and digital ad earnings through a detailed case study of a niche sporting website. By exploring key engagement metrics such as Navigation Bounces, Engagement Time, and Engaged Pageviews Per Visit, we'll demonstrate how improvements in these areas can significantly boost ad revenue. Join us as we uncover valuable insights and strategies to enhance both user experience and financial performance on your website.

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

Case Study Overview

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.

Reduction in Navigation Bounces

After implementing automated multivariate testing, the publisher experienced a 28% decrease in Navigation Bounces.  Navigation Bounces are internal page bounces that occur when users accidentally navigate to incorrect pages, find irrelevant content, or are deterred by long load times or intrusive ads. These bounces negatively impact ad rates by lowering advertiser performance metrics like Viewability, which affects programmatic bids based on Viewability.

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.

Improvements in Engagement Time

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.

Higher Engaged Pageviews Per Visit

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.

Impact on Revenue

Ultimately, enhancements in engagement metrics led to a 29% increase in session earnings (EPMV, or earnings per thousand visitors). The publisher measured ad revenue on a per-session basis to confirm that improvements in user engagement correlated with higher digital ad earnings. This clear financial performance metric demonstrated how metrics like Navigation Bounces and Engaged Pageviews Per Visit influenced programmatic bidding and publisher EPMVs.

Improving Engagement Metrics & Ad Revenue

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.

To optimize user engagement and ad revenue, consider implementing the following best practices:

1. Automated Multivariate Testing:
   • Implement automated website testing to deliver personalized ad or layout experiences to each user based on look-a-like user behavior data. This helps in providing visitors with preferred layouts or ad combinations, enhancing their overall experience.
2. Focus on Reducing Navigation Bounces:
   • Navigation bounces, where users accidentally navigate to the wrong page or find content irrelevant, negatively impact ad rates. Reducing these bounces can improve key advertiser performance metrics like Viewability, which in turn can lead to better programmatic bids from advertisers.
3. Increase Engagement Time:
   • Aim to improve the time users spend reading or engaging with your content. Higher Engagement Time is correlated with improvements in ad Viewability and Click-Through-Rate (CTR). Ensure that the content is engaging and that loading times are minimized to enhance user experience.
4. Monitor Engaged Pageviews Per Visit:
   • Pay attention to the number of pageviews with a minimum threshold of Engagement Time. Increasing Engaged Pageviews Per Visit can be tied to improved landing page ad rates and overall better campaign performance. Focus on providing valuable content that keeps users engaged on each page.
5. Track and Analyze Key Metrics:
   • Regularly measure and analyze metrics such as Navigation Bounces, Engagement Time, Engaged Pageviews Per Visit, and ad revenue per session. Use these metrics to determine if changes and enhancements are positively affecting user engagement and digital ad revenue.

By following these best practices, digital publishers can improve user engagement, enhance the visitor experience, and ultimately increase ad revenue.