How to Optimize PMax Asset Groups for Better Results

Many Performance Max campaigns fail not because of bad products or small budgets, but because the asset groups are a mess. Audiences are vague, creatives are copied from standard search campaigns, and Google’s automation is left to “figure it out” with almost no guidance. Then the blame falls on PMax instead of the structure that fed it.

When asset groups are planned deliberately, though, Performance Max can become a powerful engine for testing, scaling, and creative experimentation. Advertisers that lean into AI and automation to generate and iterate creative at scale are already seeing faster testing cycles and stronger returns, as highlighted by EddieTech Solutions’ insights on advanced PMax strategies. The opportunity is real, but it depends on how well asset groups are designed and managed.

This guide breaks down how to structure, build, and optimize Performance Max asset groups so they stop burning budget and start driving consistent, measurable results.

Understand What Asset Groups Really Do in Performance Max

Asset groups are the brain and face of your PMax campaigns. They decide who sees your ads, what those people see, and how Google’s systems learn what “good performance” looks like for your business. Treating asset groups like simple ad groups usually leads to generic targeting and creatives that never quite match user intent.

Each asset group combines audience signals, creatives, product feeds (if you have them), and landing pages into one holistic package. Google then mixes and matches those assets across Search, Display, YouTube, Discover, Gmail, and Maps. That means every weak asset group has the potential to underperform everywhere, not just in a single channel. Tight alignment between audience, offering, message, and landing page is non‑negotiable.

Because Performance Max relies so heavily on machine learning, early signals coming from asset groups matter. Strong audience hints, clear value propositions, and highly relevant assets help the system exit the “data gathering” phase sooner. That results in faster optimization, more stable CPAs, and better ROAS over time. The more deliberate the asset group design, the less guesswork Google has to do.

Build Asset Groups Around Audience Signals, Not Just Products

One of the fastest ways to improve PMax results is to rethink how asset groups are organized. Many advertisers default to splitting by product category only-“shoes,” “jackets,” “accessories.” It feels logical, but it often ignores intent, lifecycle stage, and customer value. Grouping only by product tends to produce broad, unfocused messaging that speaks to “everyone” and converts almost no one well.

A better pattern is to anchor asset groups around audience signals and commercial intent, then layer product feeds and creatives on top. For example, separate groups for “high-intent searchers,” “cart abandoners,” and “category researchers” give Google much clearer starting points than a single “all products” cluster. This structure also lets budget flow more naturally to audiences that actually convert, rather than forcing every segment to fight inside one mixed group.

Audience signals are not just “nice to have.” A study by Optmyzr found that campaigns using audience signals achieved a 35% better CPA and an 89% better ROAS compared to those without audience signals. Those lifts come from giving the algorithm strong hints about who matters most, so it can steer impressions, bids, and budget in the right direction more quickly. Skipping audience signals essentially handicaps PMax during the most important part of its learning process.

Practical ways to structure audience-led asset groups

A simple starting framework is to map asset groups against both funnel stage and product intent. For example, create one set of groups for cold prospecting, another for remarketing and warm audiences, and a third for high-value or VIP customers. Within each level, align product categories to what those users are most likely to care about, not just what exists in your catalog.

For cold audiences, lean on broader themes and problem-focused messaging, paired with landing pages that educate and build trust. For warm audiences, highlight offers, urgency, or proof-reviews, case studies, social validation. For high-value segments, bring in exclusive bundles or loyalty-focused messages. Asset groups built around intent like this naturally produce more coherent search themes, placements, and channel mixes.

As performance data accrues, split top-performing audiences into their own asset groups with dedicated budgets and creatives. That way, high-intent segments are not dragged down by broad or experimental groups. This dynamic restructuring over time is where many PMax campaigns turn from “okay” to “consistently strong.”

Design Creatives and Asset Bundles That Match Each Asset Group

Once asset groups are anchored around audience intent, creative assets need to follow suit. Reusing one generic set of headlines, descriptions, and images across all groups is convenient, but it wastes the segmentation work already done. Each asset group deserves messaging that is specific to its audience, products, and funnel stage.

Ad copy and creatives should echo the way people describe their problems and desires at that stage. Search-intent groups should borrow language from real queries and internal site search. Remarketing groups should reference past engagement-recent views, carts, or trials. High-value groups can lean harder on premium positioning and lifetime benefits. This doesn’t require dozens of brand-new concepts, but it does require thoughtful tailoring by segment.

Category-specific creative is especially powerful. A report from Adzilla found that category-specific asset bundles in Performance Max campaigns generated a 12% higher ROAS than generic asset groups. Tailoring imagery, headlines, and offers to a specific product category or use case makes it easier for the algorithm to match the right message to the right user, and it usually improves conversion rate because people feel “seen” by the ad.

Creative components every strong asset group should include

High-performing asset groups usually share a similar creative backbone. They have multiple angles of value propositions (price, speed, quality, risk reduction), strong benefit-focused headlines, and at least one social proof element such as reviews or testimonials. Images and video focus on real usage or outcomes, not just product-only glamour shots.

They also use consistent landing page experiences that mirror ad messaging. If a headline promises a specific offer or benefit, the first screen of the landing page should repeat that promise in nearly the same language. This congruence reduces friction and helps both users and Google’s systems recognize a good match between ad and page, which ultimately influences performance.

Finally, every asset group benefits from having enough creative variety to enable testing without chaos. That might mean several distinct headline themes, two or three description angles, and a small but diverse set of images or videos. Too few assets limit discovery; too many unfocused assets spread learning thin. The sweet spot is deliberate variety tied to a clear strategic angle for that group.

Use AI and Automation Without Losing Control

Performance Max is built on automation, and asset groups are where that automation either shines or spins out of control. Many advertisers worry that leaning into AI-generated assets or auto-generated asset groups will dilute brand voice or produce off-target ads. The reality is that AI can dramatically speed up ideation and testing, as long as humans define the guardrails.

AI-driven asset-group generation can rapidly produce clusters of headlines, descriptions, and image concepts aligned with different personas or value propositions. Market research from Guru Startups Market Intelligence reports that using tools like ChatGPT to help generate PMax asset groups leads to accelerated creative experimentation, shorter time-to-market, and measurable lifts in key metrics such as ROAS and CPL when implemented thoughtfully. The key word is “thoughtfully”-automation should be a force multiplier for strategy, not a replacement for it.

To stay in control, define strict creative guidelines and approval flows. Use AI for drafts, then refine them to align with positioning, compliance requirements, and tone. Lean on AI to suggest new testing angles-new benefits, objections to handle, seasonal hooks-but maintain human oversight for final selections. This combination of machine speed and human judgment tends to outperform either approach alone.

Where automation should and should not make decisions

Automation is a great fit for bidding, budget allocation across asset groups, channel selection, and rotation of creative variants within the rules set by advertisers. These are areas where algorithms can respond faster to micro-signals than any team watching dashboards by hand. Let Google’s systems handle those moving parts, especially once strong guardrails are in place.

Strategic decisions should remain human-led. That includes defining audiences, selecting which products to promote together, determining offer strategy, and deciding when to split or merge asset groups. It also includes setting brand boundaries, such as what kind of messaging or visuals are off-limits. Asset groups work best when humans decide the “why” and “who,” and machines optimize the “how” and “where.”

Over time, monitor what AI-driven experiments actually win. Promote winning concepts into “core” assets used across more asset groups, and retire ideas that repeatedly underperform. Treat the entire creative system as a loop: hypothesis, AI-assisted generation, human curation, live test, learn, and refine.

Leverage New PMax Controls and Customer Value Features

Performance Max used to feel like a black box. That’s changing. Google has rolled out more granular controls that give advertisers greater command over where and how asset groups show ads. Recent updates include campaign-level negative keyword lists and expanded search theme limits, which make it easier to keep spend away from irrelevant queries while still benefiting from broad, intent-led coverage as confirmed by reporting from Search Engine Land on the latest PMax controls.

Customer Value mode and customer retention goals add another critical dimension. Instead of optimizing purely for volume, PMax can now orient around the expected value of a customer or the goal of winning back lapsed buyers. This is especially important when some audience segments drive much higher lifetime value than others. Asset groups that isolate high-value products or VIP audiences can be paired with these goals to push budget toward your most profitable users, not just the cheapest conversions.

Use these controls strategically at the asset-group level. For example, build dedicated groups for lapsed customers with retention-focused messaging and pair them with retention goals. For low-intent or prospecting groups, set stricter negative keyword lists and broader search themes to guide discovery without runaway spend. This combination of creative structure and policy-level control keeps automation productive rather than wasteful.

Cleaning up wasted spend without throttling growth

Regular search term and placement reviews remain essential, even with PMax’s automation. Use campaign-level negative keywords to block obvious mismatches and brand safety issues. Then, refine search themes to nudge Google’s systems toward more profitable pockets of intent over time.

When an asset group consistently attracts low-quality traffic, diagnose whether the issue is audience signals, creatives, or search themes. Often the fix is not to pause the group entirely, but to tighten its focus with better exclusions and stronger, more precise messaging. That way, performance improves without cutting off opportunities for the system to discover new high-intent segments.

As these controls roll out to more accounts, the gap widens between advertisers who actively manage them and those who leave everything on default. Asset groups built with these tools in mind tend to scale more predictably and with fewer spikes in CPA.

Use Channel Insights and Asset Segmentation to Guide Optimization

Another barrier to effective PMax optimization has been the lack of clarity on which channels are carrying the weight. When results are aggregated, it becomes difficult to know whether Search, YouTube, or Display is actually driving conversions for a given asset group. That makes creative and budget decisions feel like guesswork.

New granular asset segmentation and beta channel reporting are starting to change that. According to coverage from WebProNews on Google’s enhancements to PMax, advertisers gaining visibility into asset performance across Search, YouTube, and Display are seeing potential efficiency gains in the range of 20–40% when they act on those insights. The key is not just having the data, but reorganizing asset groups and creatives around what the data says.

For example, if an asset group’s YouTube placements are driving strong assisted conversions while Display is lagging, shift that group’s creative emphasis toward video and visual storytelling. Conversely, if Search is carrying most of the performance, double down on headline and description testing while treating video and image assets as support instead of the main driver. Channel insights tell you where each asset group is naturally strong, so strategy can follow performance instead of guessing.

Turning insights into structural changes

As patterns emerge, consider splitting asset groups by channel bias. One group might be tailored toward video-dominant performance, with emphasis on YouTube-friendly hooks, while another is tuned for search-heavy performance with tightly tested text ads. Even though PMax will still decide final placements, the assets themselves will be more aligned with each channel’s strengths.

Also, use asset-level reporting to identify creatives that consistently overperform across channels. Promote those into more asset groups or reuse their core ideas in new variations. Underperforming assets should be paused or replaced, freeing up learning capacity for more promising tests. Think of each asset group as a mini-laboratory where the best ideas graduate into your broader creative system.

Over time, this approach builds a library of proven, channel-aware assets that work together rather than at random. That’s when Performance Max begins to feel less like a black box and more like a predictable, controllable engine for acquisition and growth.

How We Optimize PMax Asset Groups at North Country Consulting

At North Country Consulting, we treat Performance Max as a structured testing and scaling framework, not just a checkbox campaign type. When we build or inherit PMax campaigns, the first priority is reorganizing asset groups so they mirror how real customers move from discovery to purchase, and how value varies between segments. That often means tearing down old “catch-all” structures and replacing them with clean, intent-led groupings.

We start by mapping audience signals, product economics, and customer lifetime value. From there, we design asset groups that isolate high-value segments, protect brand terms, and carve out experimental space for new markets or creative concepts. Each asset group receives creatives tailored to its audience and channel tendencies, based on both first-party data and what we see working across our portfolio.

Because we live inside these accounts daily, we continually adjust negative keywords, search themes, and asset mixes as new insights arrive. We use AI and automation heavily for ideation and scaling, but we stay hands-on with strategy, segmentation, and quality control. For businesses that feel like PMax is “out of control” or underperforming, we specialize in turning that chaos into a disciplined system that predictably grows revenue while protecting ROAS. Working with us means having a team that knows how to bend PMax to your goals instead of bending your goals to PMax’s defaults.

Advanced Testing: Feed-Only vs Full-Funnel Assets

One of the more nuanced levers in Performance Max is deciding how heavily to lean on feed-based assets versus full creative sets. Some advertisers assume that adding every possible asset type will always help. The data suggests a more careful approach is warranted, especially for ecommerce and catalog-driven businesses.

Research from Optmyzr’s State of PPC study shows that campaigns using feed-only assets in Performance Max reported a median ROAS of 502.21%, compared to 101.71% for campaigns using all asset types. While this doesn’t mean everyone should switch to feed-only setups, it does highlight how powerful a clean, well-optimized product feed can be-and how easily unfocused creatives can dilute performance if they send mixed signals.

For brands with strong product imagery, consistent pricing, and a robust feed, starting with feed-only or feed-heavy asset groups can be a smart control test. Measure how those groups perform against more creative-heavy groups. If feed-only groups drive stronger ROAS but weaker top-of-funnel discovery, consider using them as your core revenue engine while running a smaller set of creative-rich asset groups for awareness and prospecting. The goal isn’t to pick one side forever, but to understand where each approach fits in your broader acquisition strategy.

How to run clean tests without wrecking performance

When testing feed-only versus full-funnel assets, isolate variables as much as possible. Keep audience signals, budgets, and targeting logic comparable between groups. Avoid changing multiple settings at once; otherwise, it becomes impossible to know what caused the difference in performance. Let each test run long enough for PMax to stabilize before calling a winner.

Use results from these tests to guide where you invest creative production resources. If full-funnel assets consistently underperform against strong feeds, the issue might be messaging quality rather than the presence of creatives themselves. In that case, refine angles, clarify offers, or tighten alignment between ad copy and landing pages before giving up on richer assets altogether.

Over time, a disciplined testing approach turns Performance Max from a guessing game into a data-backed system. Asset groups become levers you can pull on purpose, not mysteries you poke at and hope for the best.

Ready to harness the full potential of your PMax Asset Groups and see tangible improvements in your Google Ads performance? At North Country Consulting, our expertise is deeply rooted in the world of digital marketing and revenue operations, with a track record of success that speaks for itself. Our founder's extensive experience with Google Ads and leadership roles at Stripe and Apollo.io has shaped our approach to driving results. Don't miss the opportunity to elevate your campaigns. Book a free consultation with us today and take the first step towards optimizing your digital marketing strategy for better results.