Performance Max Asset Groups: How to Structure for Shopping-First Campaigns

Most advertisers launch a Performance Max campaign, dump all products into a single asset group, and wonder why performance is inconsistent. The truth is that asset group structure is one of the most underused levers in PMax optimization, especially for Shopping-focused campaigns where product segmentation directly impacts which products get budget, which audiences see your ads, and ultimately your return on ad spend.

This guide covers how to structure asset groups specifically for Shopping-first Performance Max campaigns. You will learn the segmentation strategies that work, the settings you need to configure (and the ones to turn off), and how to build a campaign architecture that keeps Google's automation focused on Shopping placements rather than diluting your budget across Display and YouTube.

What Are Asset Groups in Performance Max?

An asset group is the building block of every Performance Max campaign. Think of it as the equivalent of an ad group in traditional campaigns, but with more components bundled together. Each asset group contains:

• Creative assets: Images, logos, headlines, long headlines, descriptions, and optionally videos
• Listing groups: The products from your Merchant Center feed that should be advertised within this group
• Audience signals: Hints to the algorithm about who is most likely to convert for these products
• Search themes: Keyword-like signals that guide which search queries trigger your ads

A single Performance Max campaign can contain up to 100 asset groups. Each asset group should represent a distinct theme, product segment, or audience. Google's AI then decides which combination of assets to serve, on which channel, to which user, at which time.

Why Structure Matters for Shopping-First Campaigns

If you are running a Performance Max campaign alongside or instead of Standard Shopping, asset group structure determines three critical outcomes:

1. Budget Distribution Across Products

Performance Max allocates budget at the campaign level, and the algorithm distributes it across asset groups based on predicted performance. If all your products sit in one massive asset group, you have zero visibility into (or control over) how budget flows between product segments. Your best sellers and your worst performers compete for the same pool of spend.

With separate asset groups, you get reporting at the asset group level. You can see which product segments are spending efficiently and which are draining budget. While you cannot set individual asset group budgets, the algorithm treats each group as a distinct optimization target, which typically improves allocation. For deeper analysis of spend efficiency, tracking ROAS by segment becomes possible when you have well-defined asset groups.

2. Creative Relevance and Messaging

Each asset group has its own set of headlines, descriptions, and images. When you put running shoes and formal dress shoes in the same asset group, Google serves the same generic headlines for both. Separate asset groups let you write tailored copy: performance-focused messaging for running shoes, style-focused messaging for dress shoes. This improves ad relevance and click-through rates on non-Shopping placements.

3. Audience Signal Precision

Audience signals in PMax are not hard targeting constraints. They are hints. But better hints lead to faster learning and better performance. Someone who recently searched for trail running shoes is a fundamentally different prospect than someone browsing leather oxfords. Separate asset groups let you give the algorithm more precise signals per product segment, which helps it find the right users more efficiently.

How to Structure Asset Groups for Shopping

There is no single correct structure. The best approach depends on your catalog, your margins, and your business goals. Here are the primary segmentation strategies, along with when each makes sense.

By Product Category

The most straightforward approach. Create one asset group per major product category or product type. This works well for retailers with diverse catalogs where different product lines have distinct audiences and require different messaging.

• When to use: Diverse product catalog with distinct categories (e.g., electronics retailer with phones, laptops, accessories, and peripherals)
• How to filter: Use Google product category or product type in listing group filters
• Advantage: Easy to set up, aligns with how most retailers think about their products, straightforward reporting

By Margin or Profitability Tier

Group products by their profit margin. High-margin products can tolerate higher CPCs and lower ROAS targets; low-margin products need tighter efficiency. This approach is especially powerful when combined with custom labels in your product feed that tag each product with its margin tier.

• When to use: Significant margin variation across products (e.g., 15% on commodity items, 60% on proprietary products)
• How to filter: Use custom_label_0 mapped to margin tiers in your feed, then filter listing groups by that label
• Advantage: Aligns ad spend with profitability, prevents low-margin products from consuming budget that high-margin products would use more efficiently

By Brand (Own vs. Third-Party)

For retailers that sell multiple brands or a mix of own-brand and third-party products, brand segmentation is a strong strategy. Your own brand products typically have different margins, different messaging (you control the narrative), and different competitive dynamics than third-party products you resell.

• When to use: Multi-brand retailers, D2C brands that also resell complementary products, distributors
• How to filter: Use the brand attribute in listing group filters, or custom labels for brand tiers
• Advantage: Tailored messaging per brand, different audience signals (brand loyalists vs. comparison shoppers), clearer performance attribution

By Price Range

Products at different price points attract different buyer behaviors. A $20 impulse buy converts differently than a $500 considered purchase. Segmenting by price range lets you tailor audience signals (impulse buyers vs. researchers) and adjust expectations for conversion rates and ROAS.

• When to use: Wide price range within categories (e.g., $10 phone cases and $1,200 phones in the same catalog)
• How to filter: Use custom labels mapped to price buckets in your feed
• Advantage: Separate bidding behavior by purchase intent, more accurate audience targeting

Hybrid Approaches

Most mature advertisers use a combination. For example, separate campaigns by margin tier (to control bidding targets), then split asset groups by category within each campaign. Or segment campaigns by brand, with asset groups by product line within each brand campaign. The key is choosing the dimension that has the biggest performance impact at the campaign level (because that is where bidding targets live) and using asset groups for finer segmentation within that structure.

For a detailed look at setting up the feed attributes that enable these segmentation strategies, see our product feed optimization guide.

Asset Group Settings That Impact Shopping Performance

Getting the structure right is only half the battle. Several settings at both the campaign and asset group level have an outsized impact on how Performance Max handles your Shopping products.

Listing Group Filters

Listing groups are the mechanism that controls which products appear in each asset group. By default, a new asset group includes "All Products" from your Merchant Center feed. For a Shopping-first strategy, you need to replace that default with specific filters.

Available filter dimensions include brand, category (Google product taxonomy), condition, item ID, product type, and custom labels 0 through 4. The most effective approach for Shopping-first campaigns is to use custom labels because they give you complete control over the segmentation logic in your feed, independent of Google's taxonomy. As DataFeedWatch's PMax guide explains, aligning listing group filters with your feed segmentation strategy is foundational to maintaining control in PMax campaigns.

Final URL Expansion

Final URL Expansion is turned on by default in Performance Max campaigns. When enabled, it allows Google to create text ads that send users to any page on your domain, not just the product URLs in your feed. This means your Shopping campaign budget can end up funding text ads pointing to blog posts, about pages, or category pages.

For Shopping-first campaigns, turn Final URL Expansion off. An important nuance: Final URL Expansion does not directly affect Shopping ad placements because those always use product URLs from your Merchant Center feed. But it determines whether Google creates additional text ads alongside your Shopping ads, which can consume budget that would otherwise go to Shopping placements.

Audience Signals

Audience signals are arguably the most underappreciated setting in PMax. They are not targeting in the traditional sense. They are suggestions to the algorithm about where to start looking for converters. Without signals, PMax starts with zero context and burns through budget during its learning phase.

As Store Growers' PMax guide emphasizes, strong audience signals are one of the few real levers advertisers have in Performance Max. For each asset group, add:

• Customer Match lists: Upload your existing customer emails. Past purchasers of running shoes are your best signal for the running shoes asset group.
• Website visitor segments: People who visited specific product category pages on your site.
• In-market audiences: Google's pre-built segments of users actively shopping in relevant categories.
• Custom segments: Build audiences based on search terms users have used or apps they have used.

Search Themes

Search themes were added to Performance Max in 2023 and function similarly to keywords. You can add up to 25 search themes per asset group. For Shopping-first campaigns, use product-specific search terms that reflect how customers search for items in each segment. This is especially useful for helping the algorithm understand the distinction between your asset groups.

The Shopping-First PMax Architecture

A Shopping-first PMax campaign is not just a regular Performance Max campaign with a feed connected. It is a deliberate setup designed to maximize the proportion of spend that goes to Shopping placements versus Display, YouTube, Gmail, and Discover. Here is how to build one.

Step 1: Connect Your Merchant Center Feed

This is the foundation. Without a product feed, Performance Max has no Shopping inventory to work with. Make sure your feed is healthy. Title quality, image quality, accurate pricing, and proper categorization all directly impact Shopping ad performance. Our feed optimization guide covers this in detail.

Step 2: Create Campaigns by Bidding Target

Since bidding strategy targets are set at the campaign level, create separate campaigns for product segments with different profitability profiles. A common structure is three campaigns: high-margin (aggressive tROAS), mid-range (moderate tROAS), and a catch-all for remaining products with a conservative target.

Step 3: Build Asset Groups by Segment

Within each campaign, create asset groups for your product segments. Use listing group filters to ensure no product overlap. Add segment-specific creative assets and tailored audience signals for each group. If you are running a feed-only PMax setup, you can skip creative assets entirely and rely purely on your product feed for Shopping placements.

Step 4: Minimize Non-Shopping Assets

The less non-Shopping creative you provide, the more the algorithm will rely on Shopping placements. If you want a truly Shopping-first campaign, consider providing only the minimum required assets (or none at all for a feed-only approach). When you give PMax high-quality Display and YouTube assets, it will gladly spend budget there because those placements are cheaper. That is not necessarily a bad thing, but it means less budget for Shopping.

Step 5: Configure Critical Settings

• Turn off Final URL Expansion
• Set Target ROAS appropriate to each campaign's margin tier
• Add audience signals to every asset group
• Add search themes per asset group
• Exclude underperforming products from listing groups. Use low-performer analysis to identify which products to exclude.

Common Mistakes to Avoid

1. One Giant Asset Group for All Products

This is the default setup and the biggest mistake. A single "All Products" asset group gives you no segmentation, no tailored messaging, and no granular reporting. Even splitting into just 3-4 asset groups by major category is a significant improvement over a single group.

2. Leaving Final URL Expansion On

As Search Engine Land's PMax optimization guide points out, this is one of the most common but easily fixable mistakes. Final URL Expansion leaks Shopping budget to non-product pages. Turn it off for Shopping-first campaigns.

3. Overlapping Products Across Asset Groups

When the same product exists in multiple asset groups, your data becomes meaningless. You cannot tell which audience signals work, which creative performs, or how different segments compare. Use listing group filters to create clean, mutually exclusive product sets.

4. Ignoring Audience Signals

Performance Max will eventually find your customers through trial and error. But the learning phase costs money. Every first-party audience list, every in-market signal, every custom segment you add shortens the learning curve and reduces wasted ad spend during ramp-up.

5. Creating Too Many Asset Groups

While one asset group is too few, 20 or more is too many. Each asset group needs enough conversion data to optimize. If you split your budget across too many groups, none of them get enough signal for the algorithm to learn effectively. Aim for 2-5 asset groups per campaign as a starting point, and only add more when you have the conversion volume to support them.

6. Not Using Custom Labels for Segmentation

Relying solely on Google product categories or brand attributes for listing group filters limits your flexibility. Custom labels let you tag products with performance data, margin tiers, seasonality flags, and any other business logic. They are the bridge between your business intelligence and your PMax structure.

7. Using the Same Creative Across All Asset Groups

If every asset group has the same headlines and images, you have segmented your products but not your messaging. Write headlines and descriptions that speak directly to the audience for each product segment. Use product-specific images rather than generic brand imagery. Strong product titles in your feed help with Shopping placements, while tailored text assets improve non-Shopping performance.

Frequently Asked Questions

Conclusion

Asset group structure is one of the few meaningful levers advertisers have in Performance Max campaigns. For Shopping-first setups, thoughtful segmentation by product category, margin tier, or brand gives you better control over budget allocation, more relevant ad creative, and clearer performance reporting.

The key settings to get right are turning off Final URL Expansion, configuring listing group filters so product segments are mutually exclusive, adding strong audience signals to each group, and using custom labels in your feed to enable flexible segmentation. Combined with a multi-campaign architecture split by bidding targets, these practices let you run Performance Max campaigns that genuinely prioritize Shopping placements.

Start with the approach that matches your biggest business variable. If margins vary wildly, segment by margin. If you carry many brands, segment by brand. If your categories serve fundamentally different audiences, segment by category. You can always refine the structure over time as you gather data. What matters most is moving beyond the default single-asset-group setup and giving the algorithm the structure it needs to work intelligently across your product catalog.