Performance Max was created to be the set-it-and-forget-it automation play Google dreamed up. But, five years in, the only way PMax works is when you actively guide it, and it literally drains budget when you treat it like a self-managing campaign.

The hybrid strategy, running Performance Max alongside Standard Shopping rather than replacing it, is proving to be the path forward and producing the most consistent results for DTC and ecommerce brands right now.

If your current setup is a single PMax campaign covering everything with a return on ad spend target you set 90 days ago, this is worth reading carefully.

Where PMax Actually Stands Right Now

A 2024 study by Optmyzr across 24,702 Performance Max campaigns found that 82% of advertisers were running PMax alongside other campaign types. And PMax consistently underperformed those other campaigns when they competed for the same traffic.

That tells you a lot about how the campaign type actually behaves in a real account versus how it is positioned.

PMax offers unmatched reach across all of Google’s inventory of Search, Shopping, YouTube, Display, Gmail, Discover, and Maps, from a single campaign. But, that reach comes with real tradeoffs in visibility and control that have frustrated ecommerce advertisers since it launched.

Google has made meaningful progress on the control side by providing campaign-level negative keywords (rolled out late 2024/early 2025), channel performance reporting now shows which properties drive conversions, and search theme inputs doubled from 25 to 50 per asset group.

The case that PMax is a black box is harder to make in 2026 than it was in 2022. But, it still requires real strategy to perform and active guidance.

Why The Hybrid Approach Works

The core insight behind the hybrid strategy is straightforward, where Standard Shopping gives you control and data visibility while Performance Max gives you reach and automated discovery.

Google updated its campaign priority rules at the end of 2024, moving from automatic PMax prioritization to an ad rank model. Meaning the campaign with the highest ad rank now wins the auction, regardless of campaign type.

Standard Shopping handles your core, known-intent traffic, whereas PMax handles full-funnel discovery across Search, YouTube, Display, Gmail, Discover, and Maps.

This hybrid approach gives you the most optimal approach.

The account structure we use that produces the best results for ecommerce clients has been:

• Standard Shopping campaigns covering your top-revenue SKUs and product categories with tROAS targets and manual bid management levers.
• A Performance Max campaign focused on new customer acquisition, with audience signals built around lookalike and in-market segments.
• Brand exclusions applied in PMax to prevent it from taking away branded search traffic that your branded Search campaign should handle.
• Campaign-level negative keywords filtering out low-intent queries like “free,” “cheap,” and competitor brand names, where cannibalization is not worth the impression cost.

This structure keeps conversion volume high in each campaign, which matters more than most advertisers realize. Spreading budget and conversions too thin across too many campaigns prevents the algorithm from learning effectively. The goal is enough segmentation to be strategic, not so much segmentation that the machine learning starves.”

The Feed Is Still The Biggest Lever

Most advertisers optimizing Performance Max are focused on campaign settings, but the bigger opportunity is usually in the product feed.

PMax pulls heavily from Merchant Center to serve Shopping placements, and feed quality directly shapes what the algorithm has to work with. Weak product titles, generic descriptions, and missing attributes produce weak output regardless of how the campaign is structured.

Strong product titles reflect the actual search terms buyers use, not internal naming conventions. Product descriptions should be what the product actually does, not a marketing tagline or a sentence pulled from the packaging. Keep it simple, no marketing jargon.

Margin management matters here, too.

Google’s algorithm naturally gravitates toward driving conversion volume and has no inherent preference for your profitable products over ones that drive volume. That means actively excluding low-margin SKUs from PMax or using product-level asset group segmentation to control where budget gets allocated.

For DTC brands with large catalogs, this is ongoing management, not a one-time setup.

Asset Groups: Where Most Campaigns Leave Performance On The Table

Thin asset groups are one of the most common underperformance patterns we see in PMax campaigns.

The algorithm assembles ads by combining headlines, descriptions, images, and video. When those inputs are limited or generic, the output reflects it.

A few things that consistently move results:

• Separate asset groups by product category or audience segment. One asset group per campaign is usually not enough segmentation.
• Include at least one video asset. Google’s algorithm favors campaigns with video, and Google’s Asset Studio now generates video inside Google Ads using Imagen 4 and Veo 3, which removes the production barrier for most brands.
• Lifestyle imagery that shows the product in real use consistently outperforms plain product photography in upper-funnel placements like YouTube and Discover.
• Headlines should cover both functional benefits and emotional payoffs, not just product specifications.

Channel context matters inside PMax, and a single creative won’t work for all placements. What works on YouTube pre-roll isn’t what works in a Gmail ad or a Discover placement; use some common sense. Google’s PMax algorithm will handle distribution, but the quality of what you feed it determines the ceiling.

Audience Signals Are Guidance, Not Targeting

Audience signals in PMax are one of the most misunderstood parts of the campaign type. Most advertisers set up audience signals in PMax and move on without really understanding what they do.

Signals are guidance.

You are telling Google what a great customer looks like, so it can go find more of them. The algorithm isn’t limited to that audience; it is using it as a starting point.

So, the goal when building signals isn’t to constrain reach, rather it’s to give Google the best possible examples of your highest-value customers.

For ecommerce, that means prioritizing your customer match list of past purchasers first, then layering in website visitors with meaningful engagement, and filling out the rest with in-market audiences. In-market adds breadth, but it is less precise on its own, so it works better as a complement than a foundation.

Do not tighten your ROAS target too soon! Setting aggressive ROAS targets before the algorithm has enough data can reduce total conversion volume dramatically; we’ve seen this happen up to 50%.

Give the signals room to work before you start pulling the levers.

Reading The Reports

Performance Max reporting has improved significantly, but it still requires some interpretation. As mentioned before, gone are the black-box days of PMax reporting, but there is still room for improvement.

1. Search Terms Report: The search terms report now lives at the campaign level instead of the asset group level, which gives you access to a lot more data. The catch is that search and Shopping traffic are blended together, so a single search term might be reflecting performance from both formats at once.
2. Channel Performance Reporting: If the majority of your PMax spend is going toward Display with very little coming from Shopping, that is a signal that something is off with your feed or your asset groups, and it is worth digging into.
3. Asset Group Segmentation: This is where you figure out which creative combinations are actually driving conversion value. Once you know that, it is pretty straightforward to lean into what is working and update what is not.

Protip: If you have not run an Uplift experiment yet, it is worth putting on the calendar. Uplift experiments test the actual incremental contribution of your PMax campaigns against everything else running in the account. This is where you can get real answers about whether PMax is actually working.

When PMax Is The Wrong Answer

In my experience, Performance Max needs a minimum of 30 conversions in the last 30 days to optimize effectively.

Below that threshold, the algorithm doesn’t have enough signal, and the results are inconsistent. If your account is not at that volume yet, Standard Shopping with tROAS is the more predictable path. Build conversion history first and layer in PMax once the data density supports it.

Google’s own documentation recommends Maximize Conversion Value with a target ROAS if you’re tracking values and want to drive as much value as possible. This is especially true for ecommerce, and revenue-first bidding tends to produce better outcomes than pure conversion volume.

For brands with niche products where query-level visibility is critical, or where creative control is tightly managed, Standard Shopping still produces more reliable and interpretable data. The hybrid approach only works well when both campaigns are actively managed.

What To Do Now

The advertisers getting the most out of Performance Max in 2026 aren’t treating it as automation that runs itself. In fact, there isn’t a single advertising channel or campaign where we let the automation run itself. They are inefficient and frankly damaging to your campaign and overall efficiency.

PMax amplifies whatever you feed it. Good strategy in, strong results out. Weak inputs, no structure, and the budget will find its way to impressions that don’t convert.

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Featured Image: Jozef Micic/Shutterstock