AdSense Integration

Content publishers have an important role on the web: They make information available to the world so that people know what is happening at any given time and place. They can take the form of large news portals, personal blogs, or anything in between, and they have different ways to monetize content—advertising, subscriptions, premium content, and others. Among the publishers that monetize their content through advertising, both small and big, there is a large number who use AdSense, a solution offered by Google to serve text, image, video, or other advertisements that are targeted to a site's content and its audience.

Because AdSense is so important to so many users, the Google Analytics team developed an integration between the tools that provide a wealth of information about the performance of ads served in a website, along with other behavioral data. This integration helps publishers understand the behavior of their readers by identifying which traffic sources, geographies, pages, and other segments bring the highest-value users to their websites. It empowers publishers to understand who clicks (or not) on an ad, enabling a data-driven approach to optimizing content for AdSense revenue.

In this chapter, you learn how to link AdSense accounts to Google Analytics properties and how to analyze the reports that come with the integration. You also learn tips for advanced analyses of AdSense performance using Google Analytics standard features.

Integrating AdSense and Google Analytics

In this section, you learn about the process of linking, unlinking, and managing access to AdSense data within Google Analytics. Next, you learn what can potentially cause data discrepancies between the stats returned from each tool.

Linking Analytics to AdSense

Before you link the accounts, it is important to understand what will and what will not be seen in your Google Analytics reports. Google Analytics shows clicks, impressions, and earnings for ad units shown through AdSense for content. However, it will not show link units, search boxes, mobile ads, or any other AdSense product.

Step 1: Make Sure You Have the Necessary Access Levels

When it comes to user access, the integration can be accomplished only if you have Edit rights on Google Analytics and are an Administrator on AdSense. Here are links to the relevant Help Center articles for information on how to grant the right access levels:

• Google Analytics: http://goo.gl/bxyNkC
• AdSense: http://goo.gl/JlQBSO

Step 2: Find the Product Linking Section

In order to link your Google Analytics and AdSense, log in to your Google Analytics account and click Admin at the top of your screen. Then, choose the property you want to link to your AdSense account and look for a menu item named AdSense Linking or All Products.

If you have no AdSense accounts linked, you will see a table similar to Figure 3-1.

Figure 3-1: AdSense linking table

Step 3: Choose the AdSense Account You Want to Link

Click on the + New AdSense Link button (top-left of the table in Figure 3-1) in order to start the linking process. You will see a list of all the AdSense accounts you are the Administrator for. Check which AdSense Publisher ID you would like to link to and then click on the radio button to choose which AdSense property from that account you want to link to. In Figure 3-2, you can see a Google Analytics user with access to only one publisher ID (pub-5054206726270162) and one AdSense product (AdSense for Content).

Step 4: Choose Which Google Analytics Views Will Report AdSense Data

After you choose the AdSense account and property to be linked to, you will be asked which views should include this data (see Figure 3-3). This is an important step, as in some companies not every person who has access to Google Analytics data should have access to AdSense data. Either some employees should not have access to revenue data (but still have access to behavior data) or the company works with service providers who should not have access to this data.

Figure 3-2: Choosing an AdSense property to link to Google Analytics

Figure 3-3: Choosing which Google Analytics views will report AdSense data

In cases where access to AdSense is not open to every Google Analytics user, I recommend that you create a separate Google Analytics view (see the guide at http://goo.gl/MSVGW6) where you have all the necessary settings discussed in Chapter 1, “Implementation Best Practices,” excluding the AdSense data. This will help you manage who has access to your AdSense revenue data.

Once you choose which views will report on AdSense data, click on Enable Link and you are done! Figure 3-4 shows the summary page when you finish the linking process.

Figure 3-4: AdSense linking summary

Linking Multiple AdSense Accounts and/or Google Analytics Properties

If you have multiple AdSense accounts, you can link all of them to one Google Analytics property; in this case, you would see a sum of the revenue brought by all accounts. For example, if one AdSense account brought $2 in a specific page and another brought $1 to the same page, you would see $3 revenue originating from that page reported on Google Analytics, but you wouldn't be able to determine from which AdSense account the revenue was generated in the Google Analytics interface. For that you need to check your AdSense reports at www.google.com/adsense.

If you have multiple Google Analytics properties implemented in one website, you can also link all of them to one AdSense account. In this case you would see the data attributed across all Google Analytics properties as reported on AdSense. For example, if you have two Google Analytics properties implemented in a specific page that generated $2 of revenue in a specific time range, you would see $2 attributed to it in both Google Analytics property reports.

It is also important to note that once you link the accounts, you will still be able to access each product separately and provide access to data only to the people that need it. For example, if you want people to have access to Google Analytics only, you can still do that (check Step 4) or you can provide access only to AdSense through its interface as well.

Unlinking and Managing Access to Data

In order to manage or unlink AdSense from Google Analytics, follow the steps described in Step 2 to reach the Product Linking section. You will reach a page similar to Figure 3-5.

Figure 3-5: Linked AdSense accounts to a Google Analytics property

When you click on the AdSense Publisher ID, you will reach a page similar to Figure 3-4. From there, you can edit your link configuration both by choosing a different Publisher ID linked to your user or by changing which views have access to your AdSense data.

In addition, if you want to delete the link between the accounts, you will see a link on this page to Delete Link. Click the link and you will receive a popup to confirm if you would like to unlink the accounts. Note that if you decide to delete the link, Google Analytics will stop receiving data from AdSense, but data up until the time you unlink the property will still be available. It is not possible to delete data that was already collected.

Data Discrepancies Between Google Analytics and AdSense

If you performed the process just described, you should have your reports populated with accurate AdSense data. However, sometimes stats might differ between the two platforms. This list describes the top five reasons for discrepancies in the data. Please take a few minutes to go over it to minimize the chances that your data will be inaccurate.

• Missing code: The Google Analytics tracking code or the AdSense tag may not be implemented in all website pages. This can result in large differences between the two tools. In order to check whether there is a difference in the number of pages with AdSense and Google Analytics implemented, you can use the Web Analytics Solution Provider crawler available at the Chrome Store at http://goo.gl/UbcJXa.
• View filters: As suggested in Chapter 1, a common technique used on Google Analytics to segment users is to create different reporting views. These views are filtered to exclude specific data to customize your reports. AdSense data associated with sessions that are filtered out of a Google Analytics view are also excluded from all Google Analytics reports in that view. Learn more about view filters at http://goo.gl/Egc6QE.
• Browser support and configuration: AdSense uses an iframe to serve ads, so there might be issues with browsers that do not support iframes. This can be a common issue in mobile browsers. In addition, users might have technology installed in their browsers that blocks AdSense ads (such as extensions and firewalls). In both cases, you would see more pageviews on Google Analytics than page impressions on AdSense.
• Time zones and sync: The AdSense team updates its reports more often than it sends data to Google Analytics reports, so AdSense data will always be fresher when it comes to its own metrics. Also, it will take 24 hours from the moment you link the accounts for data to start being populated in Google Analytics. Last, if your time zones are set differently for each product, the data will be aggregated differently, resulting in discrepancies in the data.
• Non-supported AdSense products: As mentioned, the integration is valid only for AdSense for content, so if you are also using AdSense to monetize search boxes, mobile units, or any other product, be sure to compare only the content ad units.

Analyzing AdSense Effectiveness Using Google Analytics

In this section, you learn about the default reports you get as a result of the integration; you also learn advanced techniques to use standard Google Analytics features to analyze your AdSense performance. But before diving into the reports, let's look at the metrics that will be available on Google Analytics after the integration:

• AdSense Revenue*: Revenue generated by AdSense ads.
• Ads Clicked*: The number of times AdSense ads were clicked.
• AdSense CTR (click-through rate): The percentage of page impressions that resulted in a click on an ad.
• AdSense eCPM: The estimated cost per thousand page impressions; it is your AdSense Revenue per 1,000 page impressions.
• AdSense Page Impressions*: The number of pageviews during which an ad was displayed (a page impression can have multiple ad units).
• AdSense Ad Units Viewed*: Number of ad units viewed (an ad unit is a set of ads displayed as a result of one piece of the AdSense ad code).
• AdSense Impressions*: Number of ads viewed (multiple ads can be displayed in an ad unit).
• AdSense Exits*: The number of sessions that ended due to a user clicking on an AdSense ad.
• AdSense Viewable Impressions Percent: The percentage of viewable impressions.
• AdSense Coverage: The percentage of ad requests that returned at least one ad.

In the following sections, you learn about the reports and analyses that can be performed using the integration between Google Analytics and AdSense, starting from the default AdSense reports and proceeding to more advanced ways to analyze data using Google Analytics features.

AdSense Overview

This report provides a bird's-eye view, including all AdSense metrics available in Google Analytics. You can reach the report by visiting http://goo.gl/dEZa22 or on Google Analytics's left sidebar under the Behavior section. By default, the line chart displays the total daily AdSense revenue for your site, but you can graph any two metrics by choosing them on the top-left drop-down above the graph.

In addition, the overview report can be segmented using the Segment Builder, which is an effective way to compare two to four different groups of users (learn more about it at http://goo.gl/Us97e8). In Figure 3-6, you can see such a comparison, where each line represents a different age group—18–34, 35–54, and 55+. As you can see, it is possible to understand the trends for each segment at a glimpse.

Figure 3-6: AdSense overview report with segments

If you want to perform the same analysis, you can import those three segments into your Google Analytics account by following these links:

• Age 18–34: http://goo.gl/jY8D0F
• Age 35–54: http://goo.gl/2s3UjE
• Age 55+: http://goo.gl/Xtt3K8

AdSense Pages

This report provides information about the pages that contributed most to AdSense revenue. It will show each of the pages on the website and how well they performed in terms of AdSense.

As you can see in Figure 3-7, for each page in the website that contains an AdSense unit, you can analyze the following metrics: AdSense revenue, AdSense ads clicked, AdSense CTR, AdSense eCPM, AdSense impressions, and AdSense page impressions. If you want to have all AdSense metrics in one single table, you can import such a custom report by following this link: http://goo.gl/rHneN6. This might be useful if you are interested in downloading or emailing your AdSense report.

Figure 3-7: AdSense pages report

Note that in the top-left corner of the table in Figure 3-7, you will find a drop-down where you can choose a secondary dimension. This will allow you to add an extra dimension that can be used to segment the primary dimension shown in the table.

So, for example, if you are interested in seeing, for each page, if there is a difference in performance based on gender, you would choose Gender as the secondary dimension. Figure 3-8 shows how the resulting table would look for such an analysis. This example uncovers that while female sessions result in less revenue for this specific article, this happens because the female audience is smaller. Females actually have both a higher CTR and a higher eCPM.

Figure 3-8: AdSense Pages report segmented by gender

This report provides an interesting view of which page performed best, and it can be used to optimize website content. For example, if you find that posts about celebrities generate more revenue than posts about football, you might consider writing more about celebrities (if your main objective is making money through AdSense).

However, using Content Grouping is a more scalable approach to optimize AdSense placements and content categories to generate more revenue. Content Grouping is a Google Analytics feature that lets you group content into a logical structure that reflects your business needs. Once you define Content Groupings, you will be able to compare aggregated metrics by group name. Most websites work with templates and each template may have different AdSense placements. This means that an important analysis would be to compare performance by template (or by category) rather than by page.

In order to analyze template performance, you need to create a Content Grouping for it. There are three ways to do so:

• Modify the tracking code on each page you want to group
• Extract pages with regex capture groups
• Create rules to include pages in a group

This example uses the third option, but you can learn more about the other options at http://goo.gl/yXMscZ. Suppose your website has the following page templates:

• Article pages with URLs including /analytics/ or /testing/
• Video pages with URLs including /videos/
• Cartoon pages with URLs including /cartoons/
• Homepage with the URL /

In this case, click on Admin on the top of the Google Analytics reporting interface and search for Content Grouping below the view you want to create the group for. Click on it and then click on + New Content Grouping, and name it in a way that will make sense when analyzing your data. Figure 3-9 shows the configuration for this example.

Figure 3-9: Creating Content Grouping for AdSense analysis

After creating the Content Grouping based on your website structure (such as content type, content category, content authors, and so on), you will be able to choose them in many reports. However, it might be a better approach to create a custom report, where you can choose the metrics and dimensions you want to analyze alongside your AdSense performance. An example of how to configure such a custom report is shown in Figure 3-10. To reach the configuration page, visit http://goo.gl/q4dxOn and click on + New Custom Report (note that you can return to the previous URL in the future to find all your custom reports).

The configuration shown in Figure 3-10 will create a custom report where the primary dimension is the Content Grouping defined in Figure 3-9 (named Content Type). In addition, by clicking on a group you can drill down to the specific pages inside that group and see how they performed for the same metrics.

Figure 3-10: Custom report with Content Grouping and AdSense

Figure 3-11 shows the final table, where you see the main AdSense metrics per Content Type (the Content Group defined in Figure 3-9). This table serves as a bird's eye view to how content performs on the website when it comes to AdSense (you might also want to add metrics to broaden the scope of the table).

In Figure 3-11 you can see, for example, that while the Analytics section has higher revenue, this is a consequence of a significantly higher number of impressions. When you analyze the table further, you see that the Videos section has the greatest potential, with a higher CTR (more than 50%) and AdSense eCPM. Based on these metrics, you can understand which templates or types of content are the most effective.

Figure 3-11: Analyzing AdSense performance with Content Grouping

AdSense Referrers

This report provides information about the performance of referral traffic that brought users to the website when it comes to AdSense revenue (direct link: http://goo.gl/xkMPbo). This information is extremely valuable; however, I suggest using a different report, which is part of the standard reports and provides more in-depth information about acquisition performance. Visit the All Traffic report at http://goo.gl/otYhAr and click on AdSense in the Metric group selector, as shown in Figure 3-12.

Figure 3-12: All Traffic report with AdSense metrics

From this report, you can analyze the sources, mediums, campaigns, or any other dimension on Google Analytics (such as browser, country, landing pages, and so on) that are driving revenue on AdSense; this can be done through the Primary Dimension selector. Here is an example of one interesting way to analyze this data.

1. Choose a primary dimension: This is the dimension used to analyze the metrics, the first column of the table. You can choose almost any dimension existent on Google Analytics, but some are especially interesting, such as:
   • Source/Medium: Shows which traffic sources are the most profitable.
   • Keyword: Shows paid keywords generating revenue; can be an important metric when building a PPC strategy.
   • Landing Page: Shows through which landing page visitors that clicked on AdSense entered the website.
   • Country: Provides insight into optimization based on country; for example, countries with languages from right-to-left (like Hebrew) might show a significantly different click behavior on AdSense.
   • Visitor Type: Shows whether visitors who clicked on an ad are new or returning visitors. This can show if AdSense should be more prominent to new or returning visitors.
2. Choose a secondary dimension: The secondary dimension allows you to view the primary dimension drilled down by another dimension within the same table. It basically adds another level of detail to the report.
3. Choose a visualization type: The visualization will be essential in order to understand the data; it can be a table, a pie chart, a bar chart, a comparison chart, a cloud, or a pivot table.

Figure 3-13 shows an interesting visualization to analyze AdSense performance by GEO location (the letters A, B, and C show the steps explained previously). You can see, for example, that in the United States returning visitors are more likely to click through than new visitors in the same country. You can also see that while the United States has a higher overall revenue, Australia's new visitors might be a good opportunity, with a CTR 83% higher than the website average.

Figure 3-13: GEO location performance by AdSense metrics

Google Analytics Dashboard to Monitor AdSense Performance

Dashboards are a comfortable and sometimes effective way to monitor the performance of a website. A good dashboard aggregates all the necessary information in one place for quick access. And since Google Analytics offers the capability to create and share dashboards, I created the one in Figure 3-14 to help you monitor your AdSense performance.

The dashboard in Figure 3-14 can be used to measure your most profitable channels, pages, and demographics when it comes to AdSense revenue. You can add the dashboard to your Google Analytics account by following http://goo.gl/c031f8 (make sure you are signed in to your Google Analytics account before clicking).

Each column of the dashboard in Figure 3-14 has a theme. The first column shows overall performance metrics over time (widgets 1–4); the second focuses on demographics (widgets 5–7); and the third shows important information on behavior and acquisition (widgets 8–10). You will learn more about each widget in the next sections.

Figure 3-14: Google Analytics dashboard for monitoring AdSense performance

Overall Performance Trends (Widgets 1–4)

Widgets 1–4 are visualized in the first column of Figure 3-14 using line charts; this data visualization type is most effective when visualizing trends and small changes in data, which makes sense when looking at performance trends over time. Following is an explanation of each of the widgets:

• Widget 1: AdSense Revenue vs. Total Sessions: Shows the overall performance of the website. If you see diverging trends on the lines, it means that something worth checking is happening. Drill down into it.
• Widget 2. Ads Clicked vs. Ads Viewed: Shows a trend of the absolute number of ads people are viewing on the website and how many of them are being clicked.
• Widget 3. AdSense CTR: Summarizes widget 2. The click-through rate (CTR) is the percentage of page impressions that resulted in a click on an ad. You definitely want to see an upward trend.
• Widget 4. AdSense eCPM: The AdSense eCPM is the estimated cost per thousand page impressions. It is your AdSense revenue per 1,000 page impressions, which is a great performance metric.

Demographic Segments (Widgets 5–7)

Widgets 5–7 are visualized in the second column of Figure 3-14 using bar charts; this data visualization type is most effective when showing comparisons among categories, which makes it a good option to visualize the differences between segments of users. Following is an explanation of each of the widgets:

• Widget 5. AdSense Revenue by Country [Male vs. Female]: This stacked bar chart shows the AdSense revenue per country, and each bar is divided between Males (blue) and Females (green). As you can see in this example, Australia and Germany are heavily biased toward men, so a good tactic might be to find content that is particularly appealing to women and promote it on the homepage of those countries.
• Widget 6. AdSense Revenue by Age [Male vs. Female]: This stacked bar chart shows AdSense revenue per age group, and each bar is divided between Males (blue) and Females (green). In the example, you can see that very old and very young visitors are heavily biased toward men, but all other age groups are biased toward females, especially 55–64. Again, it might be interesting to run a content analysis and adjust content strategy based on that.
• Widget 7. AdSense Revenue by Affinity Category: This bar chart shows the AdSense revenue per affinity category. This information might help you understand which groups are the most interesting in terms of revenue, and might help drive the content strategy for the website.

Behavior and Acquisition (Widgets 8–10)

Widgets 8–10 are visualized in the third column of Figure 3-14 using tables, the most effective way to present detailed data on dimensions and metrics; tables make a good option to visualize acquisition channels and content consumption. Following is an explanation of each of the widgets:

• Widget 8. Revenue and Ads Clicked by Device: We live on a mobile planet, so it is important to check if your ads are being clicked and are generating revenue on all devices at a similar rate.
• Widget 9. AdSense Revenue by Page: This table is a great indicator of which content is performing well and how much time you should invest in each topic.
• Widget 10. AdSense Revenue by Channel: This table shows which acquisition channel is bringing the most profitable visitors.

Summary

In this chapter you learned about the integration between Google Analytics and AdSense. This integration is very helpful as it enables publishers to use advanced Google Analytics features in order to understand and optimize AdSense performance for a website.

A few recommendations:

• Understand which content type and subject generates the highest revenue and create content based on this data.
• Understand which page templates bring the best results by segmenting your data with both Content Grouping and the Segments feature.
• Analyze AdSense performance to learn which segments have a good CTR; this might bring insight into which audience to target.