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4 Performance Max segmentation strategies and how to leverage them

While auditing PPC accounts from agencies, freelancers and in-house teams, I’ve found that Performance Max campaigns typically fall into one of four categories.

Below, I’ll break down each category, discuss their pros and cons and share some insider tips on how we run our accounts. This should help you make the most of opportunities in the Performance Max auction.

1. Top performer/high margin segmentation

By far and away, the most common structure our audits uncover is a focus on “top products.” Many advertisers work under the assumption that they should focus their advertising on the products they sell the most. Sure, they have other products in their catalog, but they may not want to advertise all of them. 

By segmenting products into “top performer” and “long-tail” campaigns, you can artificially force Performance Max to spend more on top-performing products by setting lower ROAS targets. This can cut down on the time it takes for Performance Max to learn what products are good versus bad.

This approach sometimes works, but it is usually driven by bad assumptions: 

  • The product clicked is not necessarily the product purchased. Our internal research determines cross-sell rates to most commonly sit at ~70%. By forcing Google to show the product you want to sell instead of the product they want to show, CPCs often rise, while CTRs decrease.
  • Assigning queries to the most appropriate product is vital to success in shopping. For instance, the top products for shoe retailers may be Nike, Adidas and HOKA. However, a New Balance search should turn up a New Balance sneaker. Forcing top products likely means they’ll be the only retailer in the SERP showing a Nike shoe on a New Balance search. They’ll lose the click along with a long-tail sale opportunity.
  • A common mistake we uncover is when advertisers fail to segment asset groups by product type. If your top products segment contains products from multiple categories or brands, use asset groups to make sure ad creative and copy make sense. Otherwise, you could end up with ads that talk about women’s apparel but show images of men’s products, like this one:
Cycling apparel adCycling apparel ad

2. Product type segmentation

The second most common structure is a strategy that groups like products together. Operating this way ensures that asset groups are relevant, with budgets and promotions easily managed. This structure keeps seasonal demand trends groups. Additionally, it enables maximally relevant auction insights.

Not only does this structure keep data clean and assets relevant, it is probably one of the easiest to execute. However, it fails to consider business contexts surrounding margins, call center sales volumes, customer types and more.

Moreover, a common mistake we find is when people quickly use feed product types to segment all products into campaigns and send them live. While this is an easy approach, adding a layer of data analysis before you launch is worth the extra step.

Performance Max requires sufficient signal volume to be successful. Examine the historical performance of your products, and you may discover smaller categories with insufficient volume to stand on their own. These may need to be grouped with other long-tail categories to be successful. Just be sure to use asset groups to keep ad copy cleanly segmented. 

Dig deeper: The Performance Max playbook: Best practices and emerging tactics for 2024

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3. Brand and non-brand segmentation

I don’t commonly see this structure in account audits, possibly because implementing it is a little more complex.

That said, it’s a common recommendation from self-appointed experts on LinkedIn who claim Google inflates Performance Max’s performance by including branded traffic. While it is true that Performance Max runs on branded content, I don’t believe it is as big an issue as it is often made out to be.

Performance Max’s branded search traffic in the shopping network is a good volume that does not cannibalize any organic traffic (besides negligible free listing clicks). 

However, some advertisers take issue with Performance Max running branded text ads that they’d rather run through existing search campaigns. However, since Performance Max cannot run a search ad if the user’s query exactly matches the text of any keyword you have built, this should not be a problem.

Note: This has nothing to do with “exact match” the match type.

So, either:

  • You have built a sufficient breadth of branded keywords, including any variants and/or misspellings with significant volume, and there is no problem.
  • You have not built a sufficient breadth, and Performance Max is entering the auction with your search campaign and, due to higher ad rank, is entering the auction with a lower CPC than your branded campaign. You just saved money.

That said, this does become an issue when Performance Max is limited by budget and is forced to run a lot of branded text ads because of a bad search build. This will leave Performance Max with no budget for shopping, which will definitely hurt performance. 

If you build a high-quality, comprehensive branded search campaign, you don’t have a problem. 

The positive aspect of this strategy is that it can fix problematic Performance Max/Search overlap in poorly built and managed accounts. It can also segment brand and non-brand in shopping in case ROAS targets, budgets or other campaign-level settings must differ between brand and nonbrand.

However, this strategy often solves a problem that doesn’t exist. This causes data to be segmented between more campaigns, often leading to less revenue at the same efficiency. Also, the brand is usually recommended to be run on standard shopping, which again nets less revenue at the same efficiency.

4. Customer segmentation based on nCAC/LTV

This is the least common structure I see in audits. When I do, it often has significant errors due to its complexity. The general idea is to build Performance Max based on a customer acquisition strategy informed by new customer acquisition cost (nCAC) and lifetime value (LTV).

This strategy enables advertisers to justify higher CPAs by understanding the true value of a purchase beyond the average order value. This way, Performance Max algorithms bid to the value of the consumer rather than the value of the transaction. 

This helps them win more of the right auctions that help businesses grow long-term. By emphasizing high-value new customers, Performance Max can support the growth of more efficient channels like email, branded search and direct load.

However, this strategy ultimately enables lower ROAS in-platform and can significantly squeeze margins. This can be particularly difficult in the short term if you use a long payback window in your LTV calculation, creating a cash crunch that requires advertisers to level up their understanding of the whole sales practice.

Yet, those who can pull off this strategy will go the furthest, the fastest. However, an expert must implement this strategy because it can quickly get out of hand, squeezing margins beyond profitability. Proceed with caution.

Two Performance Max must-haves

With that, I’ll leave you with a few must-haves, regardless of what strategy you choose: 

  • Zombie SKU campaigns: These campaigns are filled with products that are the “living dead.” They are active, in stock and eligible to serve but get very few (or 0) clicks. Sometimes, these products don’t get the attention they should get from bid algorithms due to low historical volume. By separating them into their own campaign, the algorithm is forced to test them. Occasionally, a winner that adds meaningful incremental volume will emerge.
  • Catch-all: Set to low priority, this campaign helps ensure you aren’t missing anything in your build. Sometimes, existing targeting will not pick up new products that are added. Incorporating this campaign and monitoring volume pick-up helps you take advantage of products as soon as they hit the catalog, whether you’ve been kept in the loop or not.

Enhance your Performance Max campaigns through segmentation

Performance Max has come a long way since its debut in late 2021. As an out-of-the-box solution, it works reasonably well for advertisers. 

Smart Bidding and Smart Campaigns have largely commoditized both bidding and budget allocation. As a result, a major way to win in modern Google Ads is through structuring that gives Performance Max the best signal quality and volume. Get out there and win.


Contributing authors are invited to create content for Search Engine Land and are chosen for their expertise and contribution to the search community. Our contributors work under the oversight of the editorial staff and contributions are checked for quality and relevance to our readers. The opinions they express are their own.


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