Google is testing a new Performance Max channel setting that could give advertisers a direct way to tell the algorithm which channels they value more — a notable departure from PMax’s traditionally automated approach to channel allocation. The feature, currently described as being in alpha testing, includes adjustment controls for Search, YouTube, Display, Discover, Gmail and Maps. This development signals a potential shift in how Google balances automation with advertiser control, and it could reshape how paid media teams plan and optimize their cross-channel strategies.
What the new Performance Max channel prioritization controls actually do
The experimental “Channels” setting appears to let advertisers make positive or negative adjustments for individual Performance Max channels. A positive adjustment relaxes the cost-per-acquisition (CPA) the system is willing to accept for that channel, effectively signaling that the advertiser places greater value on conversions coming from it. A negative adjustment tightens the CPA, encouraging PMax to place less emphasis on that channel. Importantly, this isn’t the same as assigning a fixed percentage of budget to Search or YouTube. Instead, advertisers appear to be influencing the economics PMax uses when deciding where to pursue conversions.
This mechanism is subtle but powerful. Rather than commanding the algorithm to allocate 40% of budget to Search, an advertiser can say, “I’m willing to pay more for conversions that originate from YouTube,” and let the system decide how to balance budgets across channels to meet overall CPA and conversion goals. The controls are granular enough to be applied per campaign, giving advertisers the ability to fine-tune channel mix based on performance data and business priorities.
How the adjustment logic works in practice
When an advertiser applies a positive adjustment to a channel, PMax will accept a higher CPA for conversions attributed to that channel. This means the system may bid more aggressively to win impressions on that channel, potentially increasing spend and conversion volume there. Conversely, a negative adjustment constrains the CPA, making the algorithm more conservative on that channel. The result is a shift in channel mix without breaking the campaign’s overall performance guardrails.
It is important to note that these adjustments are not linear percentage increases or decreases of budget. They are relative input signals that interact with the algorithm’s real-time optimization. The exact math behind how PMax translates these signals into bidding and allocation decisions is not disclosed, but the practical effect is that advertisers gain a new lever to influence channel prioritization.
Why this is a significant shift in Performance Max’s design philosophy
Performance Max has historically given advertisers little direct control over how budgets are distributed between Google’s inventory. Advertisers could influence the system through assets, audience signals, search themes and conversion value data, but Google’s existing documentation says advertisers can’t directly control how PMax allocates budget by channel. If broadly released, this would represent a much more direct lever for influencing that mix.
The move addresses a long-standing frustration among advertisers: that PMax can be a black box, spending heavily on Display or Discovery when they would prefer more emphasis on Search or YouTube. Without channel controls, advertisers had limited recourse — either accept the allocation, or abandon PMax altogether for more transparent campaign types like Standard Shopping or Search campaigns. This test could provide a middle ground, allowing advertisers to keep the benefits of automated bidding and creative optimization while steering the system toward preferred channels.
From visibility to control: the logical progression
The test follows Google’s introduction of channel-level Performance Max reporting, which gave advertisers greater visibility into where campaigns were serving and spending. The new setting could provide the next piece of that puzzle: the ability to take what advertisers learn from channel reporting and use it to influence how PMax behaves. This two-step sequence — first reporting, then controls — mirrors Google’s pattern with other products, where transparency is often a precursor to granting more hands-on levers.
Channel-level reporting, rolled out in late 2025, allowed advertisers to see spend, impressions, clicks, and conversions broken down by Search, YouTube, Display, Discovery, Gmail, and Maps. With that data, many advertisers realized their PMax campaigns were over-indexing on certain channels relative to their strategic goals. The new controls would let them act on those insights without needing to restructure campaigns or resort to negative placement exclusions.
Attribution complicates the channel value equation
Channel-level performance isn’t necessarily the same thing as channel-level value. A user could first encounter an advertiser through a YouTube ad and later convert through Search. Looking only at the channel receiving conversion credit could therefore make YouTube appear less valuable than its actual contribution to the customer journey. Aggressively tightening a channel because its directly attributed CPA looks poor could potentially reduce demand or conversions elsewhere in the campaign.
This is a critical nuance that advertisers must understand before applying channel adjustments. The positive/negative adjustment influences the CPA the system accepts for conversions attributed to that channel, but Google’s attribution model (typically data-driven attribution) may already account for assist interactions. However, the adjustment is applied based on the reported attributed CPA, not the incremental value of the channel. Advertisers who react solely to last-touch or last-click metrics risk misallocating their influence.
For example, if YouTube consistently shows a high CPA in the “Channels” report, an advertiser might apply a negative adjustment. But if YouTube is playing a strong assist role for Search conversions, the tightening could reduce overall campaign efficiency. The feature requires advertisers to think holistically about channel contribution, not just direct conversion counts.
What advertisers should consider before using channel controls
Before making adjustments, marketers should:
- Analyze path-to-conversion data, either from Google Ads’ attribution reports or from third-party analytics, to understand the assist value of each channel.
- Run controlled experiments with small adjustments to measure the impact on overall campaign performance, not just channel-level metrics.
- Use the positive adjustment sparingly — it can increase CPA if over-applied, potentially breaking budget constraints.
- Monitor changes in channel mix over weeks, not days, because PMax learns and adapts over time.
- Combine channel controls with audience signals and search themes to provide a coherent set of optimization signals.
How this compares to existing ways of influencing PMax channel allocation
Before this test, advertisers had only indirect methods to influence channel mix within PMax:
- Asset groups: By creating separate asset groups for different channels (e.g., one for Search-focused assets, one for YouTube video), advertisers could theoretically steer PMax, but the system could still decide to serve assets from any group on any channel.
- Audience signals: Adding or removing audience segments could affect which channels perform best, but the effect was hard to predict and control.
- Conversion value rules: Adjusting conversion values for different actions could influence bidding, but not channel allocation directly.
- Negative placements: Excluding certain placements could reduce spend on specific channels, but this was a blunt instrument and often led to reduced reach.
- Campaign structure: Some advertisers created separate PMax campaigns for different channels (e.g., one for Search, one for YouTube), but this defeated the purpose of an integrated campaign and could hurt performance by fragmenting data.
The new channel controls are more direct, precise, and compatible with the automated nature of PMax. They allow advertisers to keep a single campaign structure while fine-tuning channel emphasis.
Why we care: the practical implications for advertisers
Advertisers have spent years asking for more control over Performance Max, and this test could be one of the most consequential controls Google has introduced. It could help advertisers correct unwanted channel allocation without abandoning PMax altogether. For example, a retailer that sees PMax overspending on Display while underperforming on Search could apply a positive adjustment to Search and a negative adjustment to Display, potentially rebalancing the campaign without losing the efficiency gains from automation.
But it also creates another optimization decision: marketers will need to understand the role each channel plays beyond last-touch performance before telling Google’s algorithm where to pull back. The feature adds a layer of strategic complexity that requires robust attribution analysis and testing discipline. Agencies and in-house teams will need to develop new frameworks for how to set channel adjustments based on their specific business goals, whether those are brand awareness, lead generation, or direct response.
Potential risks and pitfalls
Misusing channel controls could harm performance. Over-tightening a channel that provides valuable assist traffic could reduce overall conversion volume. Over-relaxing a channel that is already efficient could increase CPA without proportional benefit. Additionally, the controls are relative — adjusting one channel up or down affects the budget available for others, so changes must be made holistically.
Another risk is that Google may change how the controls work or remove them after testing, as it has done with other experimental features. Advertisers who build their strategy around this feature should have contingency plans. The alpha testing phase means the feature is not yet widely available, and its final form could differ from the current implementation.
First spotted and industry reaction
This update was spotted by Search Marketing Advisor Heidi Sturrock, who shared it on LinkedIn. The post quickly generated discussion among paid media professionals, many of whom expressed cautious optimism. The sentiment reflects a general desire for more control over PMax, tempered by awareness that Google’s automation often yields better results when left to its own devices. The feature is still in alpha, so it may be months before it reaches general availability, if at all.
Search Engine Land’s own reporting on the feature noted that the controls are part of a broader trend toward providing advertisers with more granularity and flexibility within automated campaigns. Google has been gradually adding levers to PMax since its launch, including asset reporting, channel-level reporting, and now channel controls. The trajectory suggests Google is listening to advertiser feedback, even if it is moving cautiously.
Bottom line: a significant step toward advertiser-steered automation
Google appears to be testing a significant shift in Performance Max: giving advertisers a direct lever to influence which channels its algorithm prioritizes. After giving marketers greater visibility into channel performance, Google may now be starting to give them more control over what happens next. The feature is not a silver bullet — it requires careful consideration of attribution, testing, and strategic alignment — but it represents a meaningful evolution in the relationship between advertisers and Google’s automated campaign system.
For advertisers who have been struggling with PMax’s channel allocation, this test offers a potential path forward. The key will be using the controls judiciously, informed by solid data, and remaining flexible as the product evolves. As with any Google Ads beta, the smartest approach is to experiment on a small scale, measure the impact, and adjust before rolling out broadly. The era of completely hands-off Performance Max may be giving way to a more collaborative model where advertisers and algorithms share the steering wheel.
