Escaping the PMax Efficiency Trap with Demand Gen

For the last two years, Performance Max (PMax) has been the default answer for ecommerce growth. It promised automated efficiency, finding conversions across Google’s entire inventory with minimal manual input. For many founders and media buyers, it delivered—until it didn’t.

We are seeing a definitive plateau in accounts that rely exclusively on PMax. The algorithm is ruthless at harvesting existing demand, often cannibalizing branded search and retargeting pools to inflate ROAS, but it struggles to generate net-new demand at scale. The efficiency trap is real: your metrics look good, but your top-line revenue stops growing.

The strategic shift for 2026 is not about abandoning PMax, but fueling it. The integration of Demand Gen campaigns alongside PMax has moved from an experimental tactic to a necessary architecture for scaling. If you are managing significant ad spend, understanding the interplay between these two campaign types is no longer optional—it is the difference between stagnation and incremental growth.

The Mechanics of the Hybrid Strategy

The core issue with a PMax-only structure is its "black box" nature. PMax prioritizes the path of least resistance. It will relentlessly bid on users who are already close to converting, effectively taking credit for sales that might have happened anyway. While efficient, this does not fill the top of the funnel.

Demand Gen operates differently. By leveraging Google’s most visual and immersive surfaces—YouTube Shorts, Discover, and Gmail—it allows advertisers to push demand rather than just capturing it. The recent inclusion of product feeds into Demand Gen campaigns was the technical bridge that made this viable for ecommerce. It allows for a shoppable experience in upper-funnel placements, warming up audiences that PMax can subsequently convert.

This combination creates a closed loop. Demand Gen acts as the feeder system, identifying and engaging cold audiences based on lookalikes and interest signals. Once those users engage, they enter the PMax ecosystem, where Google’s machine learning is best suited to close the sale. Without the feeder, PMax eventually runs out of high-intent users and begins to overspend on low-quality inventory or over-index on branded terms.

Commercial Implications for Growth Leaders

For decision-makers, this shift requires a change in how we evaluate success. The traditional method of judging every campaign by immediate ROAS will kill your Demand Gen efforts before they yield results. Demand Gen is distinct from Search or Shopping; it is a disruption channel, not an intent channel.

If you judge Demand Gen solely on last-click attribution, it will appear inefficient. However, the commercial value lies in the lift it provides to the entire account. Data consistently shows that running Demand Gen alongside PMax lowers the overall CPA of the account over time by expanding the retargeting pool and increasing search volume for brand terms.

This benefits brands with strong creative assets. PMax can survive on mediocre assets because it leans heavily on product feeds and text. Demand Gen fails without compelling video and imagery. This shifts the competitive advantage back to brands that invest in creative strategy, penalizing dropshippers and arbitrage players who rely solely on algorithmic loopholes.

Aragil POV: Strategic Implementation

If we were auditing an ecommerce ad account today that had hit a revenue ceiling, our first move would be to analyze the dependency on PMax. If PMax constitutes more than 80% of the Google Ads spend and new customer acquisition is flat, the diagnosis is clear: the account is over-harvesting.

We would implement Demand Gen not as a "brand awareness" play, but as a structured acquisition layer. We would exclude current customers and site visitors from these campaigns to ensure every dollar is spent on cold traffic. The goal is to force the algorithm to find people who do not know the brand exists.

The mistake most teams make is restricting Demand Gen with tight ROAS targets immediately. This strangles the campaign. Instead, we monitor leading indicators: a rise in branded search volume, an increase in direct traffic, and an improvement in PMax click-through rates. These signals indicate that the upper funnel is working.

Furthermore, we would aggressively use "Brand Exclusions" in the PMax campaigns. By forcing PMax to stop bidding on the brand name, we reveal its true performance. This often looks ugly initially, but it is necessary to understand if the algorithm is actually generating value or just tax-collecting on loyal customers. Demand Gen fills the gap created by this exclusion.

Conclusion

The era of "set it and forget it" automation is evolving. While AI handles the bidding, the strategist must handle the architecture. PMax is an engine, not a driver. It requires fuel.

Relying solely on PMax in 2026 is a defensive strategy that protects efficiency at the cost of market share. To scale, you must introduce friction and cost at the top of the funnel to create ease and profit at the bottom. Demand Gen is currently the most effective tool in the Google ecosystem to achieve that balance.