Publishers utilize ad platforms and ad networks to serve ads as an important revenue source. Although these platforms and networks have significant potential for generating ad revenue, the effectiveness of this revenue can be compromised if the ad-serving technologies are poorly implemented, as they can negatively affect user experience and page performance. The key is to strike a balance between monetization and performance.
Why publishers should care about Core Web Vitals
Core Web Vitals help publishers measure a page's user experience and page performance. The Core Web Vitals are three metrics designed to assess real-world user experiences in terms of loading, interactivity, and visual stability:
- Largest Contentful Paint (LCP) measures perceived loading speed: How much time it takes for the largest contentful element—including ad slots—to appear after a page began loading.
- Interaction to Next Paint (INP) measures interactivity: How quickly the page responds to user interactions. Heavy loading ads can negatively affect INP.
- Cumulative Layout Shift (CLS) measures visual stability: How much the page layout shifts, which makes the page feel unstable and unpredictable to the user. Layout instability can be caused by ads if publishers don't reserve sufficient space for the ads slots.
Different case studies have shown that Core Web Vitals have a direct business impact. This connection is crucial for publishers, as it underscores the importance of optimizing these metrics. Key questions that concern publishers include:
- Does improving Core Web Vitals metrics positively affect ad impressions and ad revenue?
- How do top sites in terms of ad impressions or ad revenue perform in relation to Core Web Vitals?
Publishers using Google Ad Manager as an ad platform and Google AdSense for Content as an ad network, along with Google Analytics 4 (GA4) to analyze user behavior, can establish correlations between Core Web Vitals and ad revenue using these Google tools. Poor Core Web Vitals indicate that a site is slow, causing elements and ads to load slowly. If ads don't finish loading before the user leaves the page, it can lead to missed impressions, and publishers may not get paid. By using these platforms, publishers can gain insights into how improving Core Web Vitals can potentially lead to increased ad impressions and higher ad revenue.
Monitor Core Web Vitals field data with ad metrics
Publishers should ideally rely on field data when monitoring Core Web Vitals. For publishers who haven't implemented a Real User Monitoring (RUM) solution, the Chrome User Experience Report (CrUX) is a valuable resource for analyzing historical field data. CrUX provides immediate insight into Core Web Vitals for eligible websites, but it shouldn't be considered a replacement for a dedicated RUM solution, which can offer more detailed data.
Publishers can use Google Analytics 4 (GA4) as a central hub to link Core Web Vitals field data with ad performance metrics from Ad Manager and AdSense. This is how it works:
- Publishers implement Real User Monitoring (RUM) by sending Core Web Vitals field data to their GA4 property.
- Data from Google Ad Manager or Google AdSense is pushed to GA4.
- Once the necessary data has been stored in GA4, it can be visualized later using a Looker Studio dashboard to correlate Core Web Vitals with ad revenue.
For detailed instructions on how to set this up, follow this codelab. The following figure is an overview of the implementation steps:
Sending Core Web Vitals field data to GA4
The process starts with collecting field data from your website's visitors. Google's web-vitals JavaScript library will help you gather information for all Core Web Vitals. Based on this, data can be sent to GA4 in different ways:
- If you're using the Google tag code snippet directly on your site, you can use the web-vitals library to send field data through the
gtag()
function. - If you're using Google Tag Manager, you can use this Web Vitals template to get you going. The tag template takes care of providing the web-vitals library and collecting field data. In addition, the template can also be individually configured—for example, by loading the attribution build. For instructions on how to use and install the tag template, follow this codelab.
Get Google Ad Manager and Google AdSense data to GA4
The second step is to send ad performance data from Google Ad Manager and Google AdSense to GA4. Fortunately, GA4 offers integrations with these advertising solutions. This lets Ad Manager and AdSense communicate with Google Analytics. Once you've set up the integration, you'll be able to see your ad-related metrics and dimensions in your GA4 property.
Data visualization with Looker Studio
Once the first two steps have been completed, a Looker Studio dashboard template can be used to visualize the data from both sources—Core Web Vitals field data and ad-related data—through Looker Studio's GA4 connector.
The following steps are necessary to use the dashboard:
- Open this Looker Studio Dashboard (select date range 24th August 2024 - 31st August 2024 to get some sample data).
- Copy the dashboard.
- Update the data source by selecting your GA4 property.
Note that, in order for the dashboard template to work, the Core Web Vitals events must be sent to GA4 using a specific syntax and naming convention. Using the Google Tag Manager template guide from GitHub covers this requirement. Alternatively, you can customize the dashboard to suit your needs.
Analyze the business impact of Core Web Vitals
The Looker Studio dashboard provides three pages based on the GA4 data. Additionally, it includes two configuration controls: a date selector and a device category filter. This lets you analyze a website's Core Web Vitals by comparing desktop and mobile performance.
Page 1: Core Web Vitals overview
The first page focuses on Core Web Vitals at a high level. Each of the cards in the Dashboard represents a single Core Web Vital metric. In addition to the overall score for the selected date range, the bar chart shows the daily distribution based on historical data. A blue horizontal line indicates the 75th percentile score.
This page helps answer several questions, including:
- What rating does my site receive for the LCP, INP and CLS metrics?
- How has my site historically performed in terms of Core Web Vitals?
- What is the Core Web Vitals rating for desktop compared to mobile?
Page 2: Core Web Vitals and ad revenue
The second page incorporates data from the Google Ad Manager and Google AdSense integration with GA4:
- The blue line represents the Core Web Vitals metric rating, while the gray bars indicate the ad revenue provided by the advertising solutions.
- If the blue line is above the red horizontal line, the Core Web Vitals rating is "poor."
- If the blue line is below the green horizontal line, the Core Web Vitals rating is "good."
- If the blue line is between the red and green line, the Core Web Vitals rating "needs improvement."
This page helps answer the question: Is there a correlation between Core Web Vitals ratings and ad revenue?
Page 3: Core Web Vitals page detail report
The third page lets you analyze performance at the URL level. You can view Core Web Vitals data for the top pages based on page views, ad impressions, ad revenue, or even RPMs. This lets you quickly identify pages with high ad revenue, but a poor Core Web Vitals rating.
How to improve your Core Web Vitals rating?
Using the Google tools mentioned earlier, you can compare Core Web Vitals and ad-related metrics. These insights will also help you to focus on the most important pages. To demonstrate the business impact, there are various general and ad-specific measures available for publishers to improve their Core Web Vitals ratings. The following is a list of resources of guides to optimize each Core Web Vital metric, as well as optimizations specific to ads:
- Optimize LCP
- Optimize INP
- Optimize CLS
- Effectively loading ads without impacting page speed
- General best practices for Google Publisher Tags
- Minimize layout shift when working with Google Publisher Tags
Conclusion
This post shows the importance of having Core Web Vitals field data and ad-related metrics in the same system—GA4. By combining different Google tools, you can effectively load and correlate Core Web Vitals data with ad-related metrics. This helps publishers to understand the rating of their site for LCP, INP, CLS and how these metrics affect ad revenue. Visualizing this data provides valuable insights and enables more informed data-driven decisions that can enhance both user experience and ad revenue.