Google is reportedly alpha-testing channel-level controls within Performance Max, which could give advertisers a new way to influence how Google values individual channels including Search, YouTube, Display, Discover, Gmail and Maps.
Google has not publicly confirmed the test. Search marketing advisor Heidi Sturrock was among the first to identify the functionality and share it on LinkedIn, so the details may still evolve before any broader rollout. But based on what has been shared so far, the controls appear to work in a similar way to conversion value rules.
The test appears to allow advertisers to adjust the relative value of individual Performance Max channels (including Search, YouTube, Display, Discover, Gmail and Maps) in a way that resembles conversion value rules, rather than providing advertisers with a simple percentage-based budget allocation across channels.
If the feature rolls out, that could give advertisers a useful new way to guide Performance Max. But it would also reinforce something that has become increasingly important across Google Ads: the quality of the data signals feeding its automation matters.
More Controls Require Better Measurement
The potential value of channel-level controls depends heavily on the quality of the signals feeding the account. Accurate conversion tracking, Consent Mode, enhanced conversions, store visit measurement and the effective use of first-party data all help Google understand which outcomes matter and how much value they create.
Advertisers also need to understand the role different channels play across the customer journey. A channel that looks expensive based on attributed CPA may still be helping customers move towards a later conversion. Display is a good example. It may rarely receive credit for the final action, but that does not mean the impressions it generated had no influence on the outcome.
That becomes more important when advertisers can tell Performance Max how much value to place on different channels. Those decisions should reflect how customers actually move towards a purchase, rather than relying on whichever channel appears most efficient in a report.
For advertisers with strong measurement in place, this could be powerful. If you can identify the journeys and interactions that tend to create more valuable customers, you have a much stronger basis for telling Performance Max where that value sits.
Where Channel-Level Controls Could Be Useful
If rolled out more broadly, channel-level value controls could be particularly valuable for businesses where different Google channels play very different roles in the path to conversion.
For a local business that relies heavily on physical visits, for example, visibility on Google Maps may have greater commercial value than it would for an ecommerce brand. A travel company may see customers discover a destination through YouTube, encounter the brand again through Display and eventually return through Search to make a booking. The attributed CPA shown in-platform may only reflect part of the value each of those interactions contributed along the way.
Channel-level controls could give those advertisers a way to reflect what they know about how their customers behave, particularly when their measurement shows that certain environments contribute more value than the final conversion data suggests.
There is also an interesting use case for advertisers running Performance Max alongside standalone Search campaigns. Overlap between the two has been a concern since Performance Max launched, and Google has gradually introduced more ways to manage it, including brand exclusions and negative keywords.
If a dedicated Search campaign is already capturing a particular area of high-intent demand, advertisers could potentially reduce the value they assign to Search within Performance Max. That would create another way to manage the relationship between the campaigns and could give advertisers more room to test where Performance Max adds value across the rest of Google’s inventory.
More broadly, channel-level controls would give advertisers another lever to test within Performance Max. Much of the optimisation work around PMax has focused on areas like bidding, creative and measurement. Being able to influence the value of individual channels would create another way to test how the campaign works for a particular business and customer journey.
The quality of the creative available for each channel also matters here. If an advertiser decides YouTube should carry more value, for example, they need video creative that can actually perform there. The same applies across Display, Discover and other visual environments. Stronger channel signals will be most useful when the campaign has the right assets to support them.
When More Control Could Work Against PMax
There is a risk that comes with giving advertisers more control over a campaign type built around automation.
Performance Max can use signals across Google’s ecosystem to make decisions that would be difficult for an advertiser to make manually at the same scale. If advertisers begin adjusting channel values based on an incomplete view of performance, they could end up steering the system away from activity that was contributing more than their reporting suggested.
Imagine Display appears to have a high CPA, so an advertiser reduces the value they assign to it. If Display was regularly introducing customers who later converted through Search, that decision would be based on only part of the journey. The advertiser now has more control, but the information behind the decision has made the system less effective.
This is why channel-level controls should be treated as a way to give Performance Max useful business context. Advertisers need a clear reason for changing how Google values a channel and enough evidence to support that decision.
The Case For Proper Experimentation
If Google rolls these controls out more widely, I hope they come with robust experimentation capabilities so advertisers can understand when they actually improve performance.
An advertiser might have good reason to believe that Maps is particularly valuable to its business, or that Search should play a smaller role within Performance Max because a standalone campaign already captures that demand. The next step is to test whether acting on that belief leads to better results.
A proper A/B testing framework would help advertisers compare Performance Max with and without those adjustments and measure the impact on incremental performance, efficiency and profitability. It would also help distinguish between assumptions that sound sensible and changes that genuinely improve the outcome.
I’m cautiously optimistic about what channel-level controls could add to Performance Max. For advertisers with complex customer journeys, they could provide a useful way to bring more business context into Google’s automation.
But having another lever to pull also raises the standard for when advertisers should pull it. The value of these controls will depend on how well advertisers understand the role each channel plays, how confidently they can measure that contribution and whether they test their assumptions before feeding them back into the system.
At the very least, this development offers an interesting reminder of a much broader principle in modern advertising:
AI is only as powerful as the data, strategy and judgement of the humans directing it.
