Unveiling the Gray Areas of Google Ads: A Study on Banner Advertising

In the rapidly evolving world of digital marketing, Google Ads remains a cornerstone for advertisers aiming to boost their online presence. However, not all aspects of Google Ads are clear-cut. In this exploration, I delve into the less transparent facets of banner advertising through Google Ads, revealing the nuances and sometimes overlooked details that can significantly impact campaign performance.

The Experiment Setup

My investigation began by setting up a banner advertising campaign within the Google Display Network (GDN). The goal was simple: target all users in Estonia with a capping of one impression per user per 30 days to gauge the precision of Google's targeting and ad frequency settings.

Tools and Methodology

To obtain a clearer picture of the audience and ad delivery mechanisms, I employed a third-party Data Management Platform (DMP). This allowed me to track and analyze various parameters including user location, device usage, and audience overlap, which are often obscured within Google Ads’ own analytics.

Findings

1. Capping Discrepancies

  • Initial Observations: The campaign initially displayed a frequency of 3.7 to 4.2 impressions per unique user, contrary to the set limit of one impression per user. This discrepancy highlighted a significant overshoot of nearly 58% more impressions than intended.
  • Adjustment Phase: Over time, the frequency adjusted closer to the intended cap, stabilizing at about 1.7 impressions per unique user.

2. Geographical Accuracy

  • Initial Targeting Errors: Despite the campaign being set for Estonia, initial data showed ads being displayed to users in neighboring countries such as Finland, Latvia, Poland, Sweden, and Lithuania, with only 3-5% of impressions actually reaching the Estonian audience.
  • Gradual Correction: The targeting accuracy improved over the campaign period, with the Estonian audience share eventually rising to 65-70%. This suggests a time-lag in Google Ads’ algorithm when adjusting to the defined geographical targets.

3. Unwanted Ad Placements

  • Gaming Apps Issue: A considerable challenge was the inability to exclude certain apps, particularly gaming apps, from the ad display network. Ads in these apps often result in accidental clicks or are completely ignored by users focused on gaming, thus diluting the effectiveness of the campaign.

4. Audience Inclusion Practices

  • Automatic Inclusion: Google Ads tends to automatically include users who have visited the advertiser’s website into the campaign audience. This practice can be counterproductive when the objective is to attract new users, as it leads to unnecessary remarketing to uninterested parties.

Implications and Recommendations

This study underscores the importance of vigilance and continuous monitoring in managing Google Ads campaigns. Advertisers should:

  • Regularly audit campaign settings to ensure adherence to intended parameters.
  • Utilize third-party tools for deeper insights into campaign analytics.
  • Refine targeting settings to prevent wastage on unintended audiences.
  • Experiment with exclusions to optimize ad placements and reduce irrelevant impressions.

Conclusion

While Google Ads serves as a powerful tool for online advertising, the complexities behind its operation can sometimes obscure campaign inefficiencies. By understanding these gray areas and implementing strategic adjustments, advertisers can enhance their campaign effectiveness and achieve better ROI. This study not only highlights the need for greater transparency and control in digital advertising but also serves as a call to action for continuous improvement and adaptation in the face of technological advancements.

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