Have you ever noticed your text ad looking a bit different on the Google search results page, or wondered about new features like the button to hide sponsored results? With the rise of AI-driven experiences like AI Overviews, the way ads appear on Search is changing, which can leave advertisers feeling a bit out of sync. This post pulls back the curtain on how Google designs and tests these new ad experiences, focusing on the balance between user trust and advertiser value.
Key Takeaways
- AI is simplifying information and ad experiences, helping users find value faster.
- A "five in the box" approach ensures collaboration across product, design, research, and engineering for hypothesis-driven ad updates.
- A balance between user and advertiser experience is key to building long-term trust.
- Consistency across the entire search results page is a guiding principle for ad design.
- Providing a wide variety of high-quality assets gives the system more flexibility to create tailored ad experiences.
Understanding The Design And Testing Process
Abby Butler, Product Manager on the Ads UI team, and Adam Bullock, UX Lead for Search Ads, shared insights into their work. Their teams are responsible for how ads appear on the search results page, aiming to create optimal experiences for both users and advertisers. This involves a close collaboration with UX researchers to understand user behaviour and evolving search trends.
How Consumer Behaviour Informs Search Ads
Google constantly monitors how people search and what they look for. As user behaviour changes, especially with the influence of AI, Google needs to adapt its search experience and, consequently, its ad formats. AI, for instance, is changing user expectations by simplifying information and making it easier to find what they need quickly. This means ad experiences need to focus on synthesising information and highlighting key advertiser attributes efficiently.
AI’s Impact On Ad Experiences
AI has opened up new possibilities for ad formats. The focus is on simplifying information and making it easier for users to grasp the value advertisers offer. This can lead to new ad formats that present information in more digestible ways. Personalisation is also a key area, with teams working to understand user intent better to help them refine their searches more easily.
Determining Value In Text Ads
Google looks at the entire ecosystem when deciding if text ads are adding value. This involves balancing the needs of users and advertisers. For users, relevance is paramount. For advertisers, it’s about connecting them with the right audience. The goal is to ensure that users are satisfied with the ads they see and that advertisers are satisfied with the users they attract. Leaning too heavily on advertiser value can erode user trust in the long run, which ultimately harms advertisers too.
The Role Of Organic Search In Ad Design
The organic search experience plays a significant role in ad design. The aim is to maintain consistency across the entire search results page, treating it as one unified experience. This ensures that ads feel integrated and don’t disrupt the user’s journey.
Recent Updates To Ad Formats
Recent changes have focused on how assets, like headlines and sitelinks, can appear in ads. The main goal is to maximise relevance at scale. For example, headlines might be shown alongside sitelinks, or only one headline might be displayed if it’s predicted to improve performance. This flexibility allows advertisers to show their ads in more relevant ways across different queries.
The Importance Of Asset Breadth
Providing a wide range of assets is crucial. The more assets advertisers supply, the more opportunities the system has to display them in various formats. Even assets that don’t get many impressions on their own can be valuable because they enable the system to show up for more relevant searches. Advertisers are encouraged to keep providing diverse, high-quality assets, as these are like "buckets of paint" for the design team to create compelling ad experiences.
What "Predicted To Improve Performance" Means
When an ad update is described as "predicted to improve performance," it means that Google’s systems, using extensive data and models, expect the change to drive better results for both users and advertisers. This isn’t just about more clicks; it’s about driving high-quality clicks and conversions, based on the specific context of the query and how the ad format compares to other eligible options.
The "Hide Sponsored Results" Feature
The option to hide sponsored results was inspired by the design of organic search results. It gives users more control and agency over their search experience. While it might seem counterintuitive for advertisers, giving users control builds trust. Interestingly, many users who have the option to hide ads don’t end up doing so, suggesting the content is often valuable to them. The feedback from this feature also helps Google further improve the overall search experience.
Surprising Test Outcomes
While many tests are successful, there have been surprising outcomes. One example was an "answer-seeking" ad format that used AI to generate an answer to a user’s question. Although the format looked good and the content was high quality, it didn’t compete well with existing formats and was eventually shelved. This highlights that even innovative ideas need to perform within the current ecosystem.
The Testing Process: Rigour And Collaboration
Google’s testing process is highly collaborative and hypothesis-driven. Teams from product, design, research, and engineering work together to vet ideas. They rely on data, user research, and intuition to form hypotheses. Experiments often start small and are rigorously measured. The goal is to ensure that every change delivers value, is understood, and communicated effectively.
AI Mode And AI Overviews Informing Text Ads
Newer experiences like AI Overviews and AI Mode are significantly influencing the future of text ads. The focus is on how users consume information in these new formats and how to simplify and organise content to make it easier for users to find what they need faster. The insights gained from these AI experiences are expected to bridge back into the traditional Search results page (SERP).
Thinking About Text Ads In 2026 And Beyond
Looking ahead, advertisers should focus on relevance and intent. As search becomes more conversational, having a broad range of assets will be key. Advertisers need to provide more tools and information to help answer complex queries efficiently. Flexibility in how assets are displayed, while respecting brand guidelines, will also be important for creating unique and relevant experiences.
Community Q&A
Direct Offers And Incrementality
Direct Offers, a pilot program allowing advertisers to present exclusive offers in AI mode, aims to help merchants close sales with high-intent consumers who might not have purchased otherwise. For example, a merchant selling a specific pair of headphones could offer a discount to a user who has shown interest in that product but hasn’t yet chosen a seller.
Advertiser Control Over Direct Offers
Advertisers have control over the offers they present. They can set up specific discounts and unique coupon codes in their merchant centre accounts. Google’s AI then determines when an offer is relevant to display. While the pilot currently focuses on discounts, it’s expected to expand to include other offer types like bundles and free shipping in the future. This feature is currently in testing in the US with a small group of advertisers.
