Microsoft Adds Performance Max Experiments for Campaign Testing

Microsoft Advertising has added new experiment options for Performance Max campaigns, giving advertisers more ways to test AI-led campaign performance before making wider changes to campaign structure or budget.

The update centers on two experiment types: Uplift experiments for Performance Max and Upgrade experiments for Performance Max. Together, they give advertisers a more structured way to understand how Performance Max performs against existing activity, and whether moving more campaign activity into Microsoft’s automated format makes sense.

For affiliate marketers and media buyers, the key question is whether automation is creating new value, or simply shifting performance away from existing campaigns.

Key Takeaways on Microsoft’s PMax Experiments 

• Microsoft Advertising has added new Performance Max experiment options.
• Uplift experiments help advertisers measure the added impact of Performance Max.
• Upgrade experiments allow advertisers to compare an existing campaign with a Performance Max version.
• The update gives paid media teams a safer way to test automation before scaling.
• Affiliate teams using paid traffic should treat AI-led campaigns as testable systems, not set-and-forget channels.

How Microsoft’s New PMax Experiments Work

Microsoft’s new Performance Max experiments are designed to help advertisers test campaign changes in a more controlled way.

Uplift Performance Max Experiments Measure Added Value

The Uplift experiment is focused on measuring the added value of Performance Max. This matters because advertisers often need to understand whether an automated campaign is generating incremental conversions, rather than overlapping with activity already running elsewhere in the account.

Upgrade Performance Max Experiments Compare Existing Campaigns

The Upgrade experiment is focused on comparison. It allows advertisers to test how an existing campaign performs against a Performance Max version before committing to a full transition.

What’s the Difference Between Uplift and Upgrade Experiments? 

Why PMax Experiments Matter for Affiliate Media Buyers 

For affiliates running paid traffic, the update is less about one Microsoft Advertising feature and more about the direction of paid acquisition. Performance Max is an AI-powered campaign type that uses goals, budget, creative assets, audience signals and conversion tracking to optimize delivery across Microsoft Advertising inventory. That can reduce manual campaign work, but it also changes how media buyers need to evaluate performance. Instead of managing every campaign element manually, advertisers are giving the platform more control over delivery and optimization. That makes testing more important, not less.

This is especially relevant for affiliate programs that work with paid traffic partners. Before scaling automated campaigns, media buyers need to check:

• whether conversion goals are clearly defined;
• whether tracking is accurate across the full funnel;
• whether landing pages are aligned with campaign intent;
• whether audience signals are strong enough to guide delivery;
• whether results show new value, rather than shifted attribution.

These checks are part of the wider media buyer partnership essentials that help affiliate programs build sustainable paid acquisition models. Performance Max experiments fit into that wider paid media workflow. They give teams a better way to ask whether automation is helping performance, or whether results are being redistributed from campaigns that were already doing the work.

Automation Still Needs Measurement

AI-led campaign formats create a clear trade-off for performance marketers. Automation can simplify campaign management and help advertisers reach users across more placements, but it can also reduce visibility into how platform decisions are made. That is why experiment tools matter. They give advertisers a way to test automation before making larger budget or structural changes.

For affiliate marketers, this is especially useful when margins are tight, conversion quality matters and campaign results need to be explained clearly. More conversions are not always enough. Teams still need to ask whether those conversions are new, profitable and coming from the right users. Those questions are central to modern affiliate reporting. As AI reshapes influence and attribution in affiliate marketing, performance teams need to look beyond the final click and assess platform-reported results against wider business goals.

What Affiliate Teams Should Check Before Testing PMax

Affiliate teams using Microsoft Advertising should treat Performance Max experiments as part of a broader testing framework, not as a shortcut to cleaner results.

Before launching a test, teams should review five areas:

1. Conversion goals: Make sure the campaign is optimizing toward the right action, not just the easiest conversion to generate.
2. Tracking setup: Check that conversions are being recorded accurately across the full funnel.
3. Audience signals: Give the platform enough useful data to guide delivery and avoid weak campaign learning.
4. Landing pages: Make sure the page experience matches the campaign intent and supports the conversion goal.
5. Budgets: Set budgets that give the experiment enough room to produce useful results without risking unnecessary spend.

Even a useful experiment tool can produce unclear results if the campaign setup is weak.

This connects to a wider measurement challenge. As AI changes how users discover and compare products, affiliate marketers need clearer visibility across traffic sources and conversion paths. Knowing how to track AI traffic in GA4 is part of that same shift.

For affiliates, the takeaway is simple: test AI-led campaigns carefully, measure incrementality where possible and scale only when the data supports it.