Performance Max has now been a core part of Google Ads for several years. What began as a relatively opaque, highly automated campaign type has gradually evolved into something more mature. Advertisers now have more reporting, more control and a better understanding of how the system behaves.
At the same time, the fundamental principle behind Performance Max remains unchanged. Google’s machine learning systems determine how budgets are distributed across Search, Shopping, Display, YouTube, Discover and Gmail in order to achieve a specified conversion goal.
For many advertisers, particularly ecommerce businesses, Performance Max has become the central campaign type within their accounts. However, running it effectively still requires a thoughtful approach. Automation can drive strong performance, but only when it is guided by good data, strong inputs and sensible structure.
In 2026, best practice is less about trying to control every lever within Performance Max and more about setting the campaign up in a way that allows the system to make good decisions.
This article explores the key best practices advertisers should follow when running Performance Max campaigns in 2026.
Start with Accurate Conversion Tracking
The most important factor influencing Performance Max performance is conversion tracking.
Unlike traditional search campaigns where advertisers could influence performance through keyword selection and bidding adjustments, Performance Max relies heavily on conversion data to guide optimisation. The algorithm looks for patterns in users who convert and then attempts to find more people with similar characteristics.
If conversion tracking is inaccurate, incomplete or misaligned with business goals, the campaign will optimise towards the wrong outcomes.
For example, if a campaign is optimising towards newsletter sign-ups rather than actual sales or qualified leads, the system may prioritise low-value traffic that generates large volumes of those sign-ups.
Advertisers should ensure that their primary conversion actions reflect genuine business value.
For ecommerce advertisers, this usually means tracking purchases with accurate revenue values. For lead generation businesses, it may involve tracking qualified leads rather than simple form submissions.
It is also worth reviewing whether multiple conversion actions are being counted in a way that confuses the algorithm. In many cases, simplifying the set of primary conversion actions can improve optimisation.
In short, Performance Max is only as good as the signals it receives.
Provide Strong Creative Assets
Performance Max campaigns depend heavily on creative assets.
Rather than showing a single static advertisement, the system dynamically combines headlines, descriptions, images and videos to create different ad variations across Google’s networks.
This means the quality and diversity of creative assets can have a significant impact on campaign performance.
Advertisers should provide multiple variations of headlines and descriptions that highlight different selling points. Some might focus on price, others on product quality, delivery speed or brand reputation.
Images should be high quality and relevant to the product or service being promoted. Visual clarity matters, particularly for placements on Display and YouTube.
Video assets are increasingly important as well. While Google can generate basic videos automatically from images and text, these often perform poorly compared to professionally created content.
Providing at least one well-produced video asset can significantly improve campaign reach, particularly on YouTube placements.
Creative assets should also be refreshed periodically. If the same messaging is used indefinitely, performance may stagnate as users become less responsive to the ads.
Structure Campaigns Thoughtfully
One common misconception about Performance Max is that structure does not matter.
While the campaign type is highly automated, the way campaigns and asset groups are organised still influences how the algorithm interprets signals.
In ecommerce accounts, it is often beneficial to structure campaigns around product categories, margins or business priorities.
For example, a retailer might run separate Performance Max campaigns for high-margin products and lower-margin items. This allows different return on ad spend targets to be applied to each group.
Similarly, segmenting campaigns by product category can help ensure that creative messaging and audience signals remain relevant.
For lead generation advertisers, campaigns might be organised around different services or geographic markets.
The goal of campaign structure should be to provide clear signals to the algorithm rather than creating unnecessary complexity.
If campaigns become too fragmented, the algorithm may struggle to gather enough data to optimise effectively.
Use Audience Signals to Guide the Algorithm
Audience signals are another important input within Performance Max campaigns.
Although the campaign type does not rely on traditional audience targeting in the same way as Display campaigns, providing audience signals helps guide the algorithm during its learning phase.
Audience signals can include customer lists, website visitors or in-market audiences related to the advertiser’s industry.
These signals act as starting points for the system. They help the algorithm understand which types of users are more likely to convert, allowing it to expand targeting beyond those initial audiences.
Customer lists can be particularly powerful.
For ecommerce businesses, uploading lists of previous purchasers allows the system to identify patterns among those customers and find similar users.
For lead generation advertisers, customer lists can help differentiate between high-quality leads and less valuable prospects.
It is important to remember that audience signals are not strict targeting constraints. They are simply hints that help the algorithm learn faster.
Optimise Product Feeds for Ecommerce Campaigns
For ecommerce advertisers, the product feed plays a central role in Performance Max performance.
Because the campaign relies on product data from the feed, the quality of that information directly affects how products are matched with user searches.
Product titles are especially important. They should include key details such as brand names, product types, sizes or other attributes that users might search for.
Descriptions should provide additional context and highlight key selling points.
Images also matter. Clear, high-resolution product images tend to perform better than cluttered or low-quality visuals.
Advertisers should also ensure that product attributes such as price, availability and product category are accurate.
Feed optimisation is not a one-time task. Regular reviews can help identify products that are underperforming due to incomplete or poorly structured data.
Improving feed quality can sometimes produce significant performance gains without changing campaign settings at all.
Monitor Search Insights and Query Behaviour
Although Performance Max campaigns do not rely on traditional keyword targeting, search behaviour still plays a major role in how they perform.
Google now provides search insights that show some of the queries driving traffic within Performance Max campaigns.
Reviewing this data can reveal valuable information about user intent.
For example, advertisers may discover that campaigns are appearing for informational queries that indicate research behaviour rather than purchase intent.
In those cases, negative keywords may be added to prevent wasted spend.
Search insights can also reveal new opportunities.
High-performing queries discovered through Performance Max may justify the creation of dedicated Search campaigns where bidding and messaging can be more precisely controlled.
Regularly reviewing search behaviour helps ensure that Performance Max campaigns remain aligned with business objectives.
Be Strategic with Brand Traffic
Brand traffic is another important consideration when running Performance Max campaigns.
Many advertisers find that a portion of Performance Max conversions come from branded searches. While this can improve reported performance metrics, it may not represent incremental value.
If a user is already searching specifically for a brand name, there is a good chance they would have converted regardless of the campaign.
Advertisers therefore need to decide whether branded traffic should be included within Performance Max campaigns.
Some businesses choose to exclude brand terms from Performance Max in order to measure true incremental performance.
Others allow branded traffic within the campaign if it helps drive lower acquisition costs.
The right approach depends on how brand traffic fits within the broader account strategy.
What matters most is understanding how branded queries influence reported results.
Allow Campaigns Time to Learn
Performance Max campaigns rely heavily on machine learning models that require sufficient data to optimise effectively.
When a campaign is first launched or undergoes significant changes, it enters a learning phase where performance may fluctuate.
During this period, the algorithm is testing different combinations of placements, audiences and creative assets to determine what works best.
Advertisers should avoid making frequent structural changes during this learning phase.
Adjustments such as changing bidding strategies, altering budgets significantly or restructuring asset groups can reset the learning process.
In most cases, campaigns should be allowed to gather enough data before major changes are made.
Patience is often an important part of achieving stable performance.
Combine Performance Max with Other Campaign Types
Although Performance Max is designed to cover all Google inventory, it should not necessarily replace every other campaign type.
In many accounts, the best results come from combining Performance Max with traditional Search campaigns.
For example, advertisers may choose to run dedicated Search campaigns for high-intent keywords while using Performance Max for broader discovery and shopping placements.
This hybrid approach allows advertisers to retain control over their most valuable search traffic while still benefiting from the reach and automation of Performance Max.
Similarly, remarketing campaigns or specialised video campaigns may still play a role within the overall account structure.
Performance Max works best when it is integrated into a broader strategy rather than treated as the sole campaign type.
Refresh Assets and Review Performance Regularly
Although Performance Max automates many aspects of campaign management, it should not be treated as a “set and forget” solution.
Regular reviews remain important.
Advertisers should monitor asset performance, search insights and product data to identify opportunities for improvement.
Low-performing creative assets can be replaced with new variations.
Product feeds can be refined to improve matching with user searches.
Search insights can reveal irrelevant queries that may require negative keywords.
Even small incremental improvements can compound over time.
The key is maintaining a balance between allowing automation to operate and providing ongoing guidance.
Conclusion
Performance Max has matured significantly since its introduction. The campaign type now offers greater transparency and more tools for advertisers to guide its behaviour.
However, the fundamental principle remains the same. Performance Max is designed to use machine learning to optimise across Google’s advertising ecosystem.
In 2026, best practice is less about trying to override the system and more about giving it the right inputs.
Accurate conversion tracking, high-quality creative assets, strong product feeds and thoughtful campaign structure all play essential roles.
Advertisers who focus on these foundational elements are far more likely to see strong results.
As Google continues to refine Performance Max, the balance between automation and control will likely keep evolving.
For now, the most successful advertisers are those who understand how to guide the system rather than fight against it.