In the evolving landscape of digital advertising, the tug-of-war between machine-led automation and human control remains a central theme for search engine marketers. For years, Google has nudged advertisers toward fully automated campaign types, promising better performance through machine learning while simultaneously reducing manual levers. However, a newly spotted test suggests that Google may be preparing to hand back a crucial piece of control to advertisers using its highly automated campaigns.
Paid search specialist Thomas Eccel recently spotted an unannounced update inside Google Ads and shared his findings on LinkedIn. Google appears to be testing a new “Branded Searches” control setting specifically designed for AI Max campaigns. This feature aims to address one of the most persistent and vocal complaints from the advertising community: the tendency of automated campaigns to cannibalize organic and paid branded traffic.
If rolled out globally, this feature could redefine how marketers approach prospecting, budget allocation, and campaign attribution within Google’s AI-driven advertising ecosystem.
Understanding the AI Max Ecosystem and the Search for Balance
To understand why this test is generating significant buzz among PPC professionals, it is helpful to look at the broader context of Google’s push into automated campaign types. AI Max represents the next iteration of Google’s AI-first advertising strategy. Designed to maximize conversion volume and value across Google’s vast array of networks—including Search, YouTube, Display, Discover, Gmail, and Maps—AI Max relies heavily on machine learning algorithms to determine where, when, and to whom ads are shown.
While the promise of AI Max is to uncover hidden pockets of demand that manual targeting might miss, its implementation has not been without friction. When Google first began pitching these highly automated structures to brands, marketers expressed concern over the “black box” nature of the campaigns. You can read more about the initial reception and strategy in the detailed coverage of the Google AI Max pitch to advertisers.
The core issue is transparency. When a machine learning model is given free rein to optimize for conversions, it naturally seeks out the path of least resistance. Often, that path leads directly to users who are already searching for the advertiser’s brand name. Bidding on these high-intent, branded search queries almost guarantees a high conversion rate and a seemingly stellar Return on Ad Spend (ROAS). However, this often fails to generate true incremental business, leading to inflated performance metrics that mask the campaign’s actual contribution to growth.
The Newly Spotted Branded Search Controls: A Closer Look
According to the screenshots and details shared by Eccel, the new “Branded Searches” setting is located directly within the AI Max campaign settings panel. This native control offers advertisers three distinct pathways to manage how their campaigns interact with brand-specific search queries:
1. Show ads on all relevant searches (Default)
This setting maintains the status quo. Under this default behavior, the AI Max algorithm has full permission to serve ads on any queries it deems relevant, including the advertiser’s own branded terms, competitor brand names, and generic search queries. While this maximizes the volume of data the AI can work with, it leaves the door open for brand cannibalization.
2. Control branded searches using brand inclusions and exclusions
This hybrid option allows advertisers to guide the AI by applying pre-defined brand lists. Marketers can specify which brand terms the campaign should actively target (inclusions) or avoid (exclusions). While brand lists have existed at the account level for some time, integrating this directly into the campaign creation and management workflow within AI Max simplifies the process significantly.
3. Show ads only on unbranded searches
This is the option that has caught the attention of performance marketers worldwide. By selecting this setting, advertisers can explicitly instruct the AI Max campaign to completely ignore queries containing their brand name. This forces the algorithm to focus exclusively on prospecting, generic category terms, and discovering net-new customers who may not yet be familiar with the brand.
Why the “Unbranded Only” Option is a Game-Changer
For search marketers, the ability to cleanly isolate branded traffic from non-branded traffic is not just a matter of preference—it is a fundamental requirement for accurate performance measurement and budget efficiency. The introduction of an “unbranded only” toggle addresses several critical pain points:
Eliminating Brand Cannibalization
When an automated campaign bids on your brand terms, it often wins clicks that would have otherwise gone to your organic search listings or your dedicated, lower-cost brand search campaigns. This cannibalization drives up overall marketing costs without delivering a corresponding lift in actual sales. By restricting AI Max to unbranded queries, brands can protect their marketing budgets from being spent on users who were already on their way to make a purchase.
Improving Attribution and Reporting Clarity
One of the biggest headaches associated with automated campaigns like AI Max is attribution skew. If an AI Max campaign mixes branded and unbranded conversions together, the overall campaign metrics look incredibly strong. However, when you strip away the branded conversions, you often find that the cost-per-acquisition (CPA) for new, generic customers is unsustainably high. Isolating unbranded traffic allows marketers to see the true, unvarnished cost of acquisition for prospecting efforts.
Ensuring True Incrementality
Incrementality is the holy grail of modern digital marketing. It answers the question: “Would this conversion have happened without this ad spend?” Branded searches have very low incrementality because the user search intent is already highly focused on the brand. Unbranded searches, on the other hand, represent high incrementality. A native setting that restricts AI Max to unbranded searches ensures that every dollar spent is actively working to capture new market share rather than simply claiming credit for existing demand.
The Shift from “Black Box” to Guided Automation
The testing of these branded search controls is part of a broader, highly visible trend in Google’s product development. When automated campaign types like Performance Max were first introduced, Google took a rigid stance on manual controls, arguing that the machine learning models performed best when given maximum freedom.
However, the industry pushed back. Agencies, enterprise brands, and independent consultants argued that total automation without guardrails introduces unacceptable risks, particularly regarding brand safety, margin protection, and budget waste. Over time, Google has listened, gradually introducing features like account-level negative keywords, brand exclusion lists, and asset group scheduling.
The appearance of campaign-level branded search controls in AI Max campaigns is another step toward a compromise: guided automation. This approach allows advertisers to set strategic boundaries—such as defining the target audience type or isolating brand intent—while leaving the tactical execution, bidding, and creative optimization to Google’s artificial intelligence.
What Search Marketers Should Do Next
Because this feature is currently in a testing phase, it may not yet be visible in all Google Ads accounts. However, proactive marketers should take several steps to prepare for its potential widespread rollout:
- Audit Current Campaigns: Review your active AI Max and Performance Max campaigns to see how much of their conversion volume is currently driven by branded search queries. Look at your search term insights to evaluate whether cannibalization is occurring.
- Check Account Settings: Regularly monitor your campaign settings tabs for the appearance of the “Branded Searches” control module. If your account is part of the test group, consider running a split test to compare the performance of an “unbranded only” AI Max campaign against your baseline.
- Refine Brand Lists: Take the time to build and clean your brand exclusion lists at the account level. Having these lists properly configured ensures that if and when the campaign-level controls become available, you can implement them smoothly and accurately.
- Re-evaluate Budget Allocation: Think about how your budgeting strategy might change if you could guarantee your AI Max campaign was only prospecting. You may want to shift budget out of generic search campaigns and into an “unbranded only” AI Max campaign, or conversely, allocate a dedicated budget to a highly controlled, manual brand campaign to capture high-intent traffic safely.
As search engines continue to integrate generative AI and complex automated bidding strategies deeper into their core products, the role of the search marketer is shifting from manual operator to strategic orchestrator. Features like the branded search controls currently being tested in AI Max campaigns provide the exact type of leverage marketers need to steer AI toward profitable, incremental growth.