Google's AI Max promises marketers the ability to “set-and-scale” campaign goals, assets, budgets and more. But you’d be right to stop and question whether that’s actually a promise that can be delivered on, especially during peak sales periods, like Black Friday and Cyber Weekend.
There’s no doubt, the system is powerful, but it’s also inflexible. While it’s marketed as a machine learning-driven system, it relies on patterns from historical performance data rather than real-time awareness. Learning and optimization cycles can take quite a bit of time after significant changes. In other words, it doesn’t notice key variables and updates as they happen, like a promo changing at noon, or a hero product that sold out at 3 p.m.
That’s only one part of the story, though. To truly outperform during peak sales periods, marketers need to be aware where AI Max can fall short, and importantly, how to turn those limitations into opportunities. We take a closer look at three common pitfalls, and share insights on how to regain control, improve performance, and maximize every sales hour.
Risk: Stale promo copy
Text Customization keeps surfacing outdated discounts after your offer ends.
Why it's worse at peak: Copy–to-landing page mismatches (for instance, a “30% off” ad that goes to a “50% off” page) kill the user experience and CVR at scale.
Fix: Turn off Text Customization during periods of frequent promo changes. Or, if you have access to the Text Guidelines beta, proactively exclude expired promos when offers change. Always remember to remove exclusions before your next promotional period.
Risk: Landing page wastage
With Final URL Expansion (FUE) on, AI Max may route to any “relevant” URL, including non-promo or sold-out pages.
Why it's worse at peak: Your new sale landing page, or the category page that’s now stacked with promos, may not have the high-performing historical data needed for AI Max to route traffic there. Meanwhile, pricing and stock move hourly, so if for instance, a hero SKU or variant goes out of stock, it will be removed from Shopping/PMax, but AI Max can still drive traffic there.
Fix: If you need hard control, turn FUE off and use a curated inclusion list so traffic is limited to those URLs (page feeds are guidance unless FUE is off). It’s great for day-to-day scaling but risky during fast-changing promos.
Alternatively, if you want to go hard for scale, work closely with the web and trading teams to make sure all bot-discoverable landing pages have sale messaging, and that any low- or no-stock SKU pages are circulated with marketing each morning so they can be excluded before volume picks up.
Risk: Budget throttling
Early budget caps or yo-yo ROAS targets restrict exploration and kill evening surges, leaving revenue on the table at the most lucrative time of year.
Why it's worse at peak: Demand is time-boxed; once the window closes, you can’t “catch up,” and a big spike in volume can cause your campaigns to unexpectedly cap out on the biggest days of the year.
Fix: If using tROAS or tCPA to control spend, open up your budgets well above the forecasted amount. Campaigns can spend up to double the budget on a single day, but leave plenty of headroom and don’t take any chances.
If you’re using daily or shared budgets to control spend, you might want to rethink your approach, they’re inefficient. If you have no option but to use them, however, ensure that you’re monitoring spend closely. If you’re overpacing, increase your ROAS target to spread your budget over as many clicks as possible. In either case, check % impression share lost to budget every day. If it’s more than zero, your caps are too low.
Make the most of your peak period
So again, it’s not that AI Max is the enemy; it’s just that it’s not built for the precision and pace that peak sales periods demand. Left unchecked, there is a real risk of serving outdated ads, pushing traffic to the wrong places, and reaching your cap without accounting for live trading conditions and scenarios.
Outperforming during peak requires a hands-on approach where it matters most: promo timing, landing page integrity, and budget pacing. That balance of human input and machine efficiency is where performance really compounds, and brands are able to truly outperform.