Understanding the Impact of Multiple Ads

• How multiple ads affect Google Ads data
• How multiple ads affect Adthena metrics
• MyAnalytics Dashboard
• Planned Future Updates

How multiple ads affect Google Ads data

Google’s double serving ads: What’s the impact for advertisers?

How multiple ads affect Adthena metrics

Scenario

• Advertiser 1 appears on every SERP, every day, for a specific search term over a 10-day period.
• Advertiser 2 appears with two ads on half of those SERPs for the same search term.

In this scenario, both advertisers would have the same number of impressions if impressions are defined as the number of times an advertiser’s domain is visible to a user on the SERP.

Now lets look at how Adthena data currently represents these scenarios. 

Share of Impressions

Both advertisers will have a 100% share of impressions.

We are going to implement the same method as Google Shopping where if you have multiple ads on a page then only count one impression. This will result in Advertiser 2 having 50% of impressions. 

We will then come up with another metric so that we can represent multiple appearances on the search by the same domain in another metric. For now, the priority is to represent the share of impressions as above, so that Advertiser Two has 50%. 

For reference: Google’s definition of Impression Share

Learn more about how Google calculates impression share and what it means for your visibility in the auction: Google Ads Help – Impression Share

Note: For any ad type, we cap the maximum of 100% share of impressions.

Estimated Impressions

In this example, both Advertiser 1 and Advertiser 2 will have the same total number of estimated impressions. For cases where an advertiser appears with multiple ads on the same SERP, each ad is counted individually — meaning both ads contribute separately to the impression count.

CTR

Advertisers 1 and 2 will have different average CTRs based on their ad positions and ranks across the /same search term. 

We count every position. So for example, if advertiser 1 is in position 1 every time, they would have an average position of 1, and a high CTR. 

If advertisers had multiple ads in position 1 and 3, their average would be 2, and therefore a lower CTR.

Estimated Clicks

Advertiser 2, with multiple Ads will have lower estimated clicks in this example. So both advertisers have the same number of impressions, but as described above, advertiser 2 will have a lower CTR.

Share of Clicks/Spend

In this example, Advertiser 2 (who has multiple ads) could actually end up with a higher share of clicks/spend or lower share. This is because although as we have described above an advertiser with multiple ads will have twice as many impressions than if they appeared once, their CTR will be lower than if they appeared only once.

So, whether the share goes up or down, depends on how the CTR acts up the double impressions. 

If I had 1000 impressions, and a CTR of 0.5, then I get 500 clicks. 

If I have 2000 impressions, but my CTR is pulled down to 0.1, for example if my second ad was in bottom position 6, then my clicks would be 200.

Average Position

We currently calculate average position as a weighted average across all observed ranks for each advertiser. Every ad appearance is included, regardless of where it appeared on the SERP.

• Advertiser 1 always appears in position 2 so Average Position = 2.0
• Advertiser 2 has two ads:
  • One in position 3
  • One in position 9
  • Average Position = (3 + 9) / 2 = 6.0

Despite having a presence in top positions, Advertiser 2’s average rank may appear worse due to the influence of the lower-positioned ad pulling the overall average down. Conversely, if Advertiser 2 began appearing with multiple ads only in lower positions, the introduction of an additional ad in a higher slot could pull the average position up.

MyAnalytics Dashboard

In response, we developed the Multiple SERP text ads MyAnalytics dashboard to surface instances where the same advertiser appears multiple times in a single search result, highlighting key competitive behaviors and enforcement opportunities.

The dashboard offers insight into how often domains double serve across selected search term groups. This article outlines the three available views and explains how each metric is calculated. All views reflect data from a rolling 90-day window, enabling trend analysis while maintaining statistical significance.

1. Double Serving Rate (All Competitors)

This view calculates how often any competitor is observed double serving across the selected search term groups. 

• Calculation:

• Example: If 44 of 100 results had any instance of double serving, the rate is 44%.
• Note: If two or more competitors double serve in the same result, it’s counted once.

2. Double Serving Rate by Domain

This view focuses on how frequently a specific domain double serves across different search term groups.

• Calculation:

• Example: If a domain appears in 100 search results and double serves in 30, the rate is 30%.

3. Double Serving by Domain and Search Term

This is the most granular view, showing how often a selected domain double serves across each search term within the selected search term group(s).

• Calculation: Same as above, but scoped per individual term.

Planned Future Updates

Step 1: Prioritize Top Ad Position

We will begin by counting only the top appearance of a domain when multiple ads from the same advertiser are shown. This adjustment should improve consistency and predictability across calculations. 

Step 2: Introduce New Metrics

We will develop new metrics that provide clearer visibility into when and how often multiple ads from the same advertiser appear.