Anastasia Braitsik stands at the forefront of the evolving search landscape, bringing a wealth of experience in navigating the shift from manual keyword management to intent-based automation. As a global leader in SEO and performance marketing, she has spent years dissecting the mechanics of data analytics to help brands maintain efficiency amidst platform-wide changes. With Google’s aggressive push toward AI Max, Anastasia’s insights serve as a vital compass for advertisers trying to balance the allure of massive revenue growth with the cold reality of rising acquisition costs.
While AI Max can drive a median revenue increase of 13%, it often results in a 16% rise in CPA. How do you decide if this tradeoff is acceptable for a specific brand, and what metrics indicate that the growth is truly incremental rather than just expensive?
The decision to accept a higher Cost Per Acquisition hinges entirely on a brand’s current lifecycle stage and their specific margins. If a business is in a hyper-growth phase where capturing market share is the priority, a 13% revenue bump might justify that 16% jump in CPA, but for high-volume retailers with razor-thin margins, that trade-off can be devastating. I look closely at the ROAS fluctuations, which we’ve seen swing wildly from a 42% increase to a 35% decrease depending on the account structure. To determine if growth is truly incremental, you have to look past the top-line revenue and analyze whether these conversions are coming from new intent or simply cannibalizing your existing exact match terms. If your conversion value is rising by 14% to 27% while maintaining a stable ROAS, you’ve likely found a sweet spot, but anything less suggests you’re just paying more for the same customers.
Automation sometimes cannibalizes over 60% of existing keyword coverage or scales too aggressively into competitor brand terms. How should advertisers audit their search term reports to identify these overlaps, and what manual overrides are necessary to prevent a budget blowout on low-intent competitor queries?
It is a sobering reality that AI Max can recycle existing coverage up to 63% of the time instead of finding new, untapped queries. This creates a “double-dipping” effect where you pay a premium for traffic you already owned through standard campaigns. I have seen instances where the system gets so aggressive that competitor brand terms consume a staggering 69% of total Search impressions, which is a recipe for a budget blowout. To combat this, advertisers must relentlessly audit their search term reports, specifically looking for high-volume competitor names that don’t convert at your target rates. You must implement aggressive negative keyword lists and brand exclusions to prevent the AI from “hijacking” your budget to chase low-intent or high-cost competitor traffic.
Some campaigns experience massive impression spikes on the Search Partner Network with conversion rates as low as 0.07%. Given that reporting can generate tens of thousands of rows, what specific automation or filtering processes do you recommend to catch these efficiency leaks before they drain the budget?
The disparity between standard Google Search and the Search Partner Network (SPN) can be shocking, with conversion rates dropping from a healthy 3.04% down to a dismal 0.07% in some cases. When you are dealing with reports that run to tens of thousands of rows, manual scrolling is no longer a viable strategy for an expert. I recommend setting up automated alerts and scripts that flag any segment where impressions cross a certain threshold—like half a million monthly views—while the conversion rate remains under 1%. By isolating SPN performance in a separate data layer, you can see if the network is just a “black hole” for your budget and make the executive decision to opt out. Efficiency leaks are often buried in the sheer volume of data, so you need to filter for “outlier spend” to see where your money is actually going.
With Dynamic Search Ads slated for deprecation, the current recommendation is to integrate keywordless features into existing Search campaigns rather than migrating to Performance Max. What is your step-by-step strategy for winding down DSAs, and what technical hurdles should teams prepare for during this transition?
The transition away from DSAs requires a surgical approach rather than a “rip and replace” mentality. My strategy involves activating the AI Max keywordless features—specifically broad match expansion and final URL expansion—within your established Search campaigns first. This allows the algorithm to learn from your existing conversion data before you start dialing back the original DSA ad groups. The biggest technical hurdle is the shift toward “pure intent matching” over keyword syntax, which can lead to unpredictable landing page selections. You must monitor your Final URL Expansion reports daily during the first month to ensure the AI isn’t sending traffic to irrelevant pages like your Privacy Policy or blog archives instead of product pages.
Since official performance statistics often exclude the retail sector, ecommerce advertisers face unique risks with broad match expansion and automated landing page selection. How should retail-specific accounts structure their initial tests, and what “red flags” in the data should trigger an immediate return to traditional settings?
It is highly significant that Google’s 14% uplift statistics conspicuously exclude the retail sector, which tells me that ecommerce advertisers are playing a different game with higher stakes. For retail accounts, I suggest structuring initial tests as isolated experiments on a small subset of product categories rather than an all-in account change. A major “red flag” is a sudden drop in ROAS accompanied by a spike in “General” or “Informational” search terms that don’t lead to a shopping cart. If you see your Final URL Expansion driving high bounce rates on high-margin products, or if the automation is purely cannibalizing your brand terms to pad its stats, you should immediately revert to your traditional, manual settings.
What is your forecast for AI Max?
I believe AI Max is essentially a “coin toss” for advertisers right now, and while it represents the future of Google’s intent-based ecosystem, it is currently in a volatile experimental phase. We will likely see Google refine the reporting tools to help us manage the tens of thousands of data rows more effectively, but for the next year, adoption will remain cautious with only about 16% of advertisers going deep into the feature. My forecast is that AI Max will eventually become the mandatory standard as DSAs vanish, but the advertisers who succeed will be those who refuse to let “FOMO” drive their strategy and instead lean into aggressive, manual auditing. The goal isn’t just to turn the AI on; it’s to stay in the driver’s seat and ensure that 13% revenue growth doesn’t come at the cost of your brand’s long-term profitability.
