Google Ads Launches New Search and AI Max Experimentation Tools via @sejournal, @brookeosmundson

Google Ads is giving advertisers more ways to test campaign changes before applying them more broadly.

Google announced new experimentation and planning capabilities for Search campaigns and AI Max, including updates aimed at testing budget, bidding and targeting changes with more control.

Some of these tools are available now, while a new multi-campaign testing option will begin rolling out in September.

Together, the updates give advertisers more flexibility to measure how larger campaign changes could affect performance before deciding whether to implement them.

Multi-Campaign Search Experiments Coming in September

Starting in September, advertisers will be able to test budget and ROI target changes across multiple Search campaigns within a single A/B experiment.

The new capability builds on the one-click experiments Google previously introduced for AI Max, but expands testing beyond individual campaign changes.

For example, an advertiser considering a larger budget increase could test that change across a group of Search campaigns rather than making adjustments campaign by campaign. ROI targets can also be included in the experiment.

Google says this will help advertisers measure how scaling campaigns affects their bottom line before rolling those changes out more broadly.

That could be a useful case for accounts where budgets and bidding targets are managed across a portfolio of campaigns. Instead of evaluating each campaign independently, advertisers can test a broader strategy while maintaining a control group for comparison.

AI Max Experiments Can Now Keep Brand and Location Controls

Google is also expanding what advertisers can keep in place when testing AI Max for Search campaigns.

Advertisers can now run AI Max experiments with brand and location settings enabled. Previously, those controls could limit how advertisers tested AI Max if they were part of the campaign’s intended setup.

The change should make it easier to evaluate AI Max under conditions that more closely reflect how the campaign would run after an experiment.

This is especially relevant for advertisers that rely on brand controls or geographic restrictions and don’t want to remove those guardrails simply to measure AI Max performance.

Rather than choosing between maintaining those controls and running an experiment, advertisers can now test AI Max with them in place.

Performance Planner Adds One-Click Campaign Changes

Google is also making it easier to move from planning a campaign change to implementing it.

Performance Planner can now show how changes to bidding or budget targets may affect existing campaign performance. Advertisers can then apply those suggested changes directly to their campaigns with one click.

Before applying a plan, advertisers can review the proposed changes at the campaign level and deselect any campaigns they don’t want to update.

Applied changes can also be monitored through the Bulk Actions section in Google Ads, where advertisers have the option to undo them if needed.

The update is meant to shorten the gap between forecasting a change and putting it into practice. That makes Performance Planner more actionable, but it also puts more weight on reviewing the forecast and proposed changes before applying them.

What This Means For Advertisers

As Google Ads continues to automate more campaign decisions, advertisers need reliable ways to understand how those decisions affect performance.

The new experimentation tools provide more options to validate changes before rolling them out across an account. Advertisers can test larger budget or ROI target adjustments across multiple campaigns, while AI Max experiments can better reflect the settings they plan to use long term.

Keeping brand and location controls in place during AI Max experiments should also make those test results more useful. Advertisers that depend on these settings no longer have to alter their intended campaign setup to evaluate AI Max results.

The Performance Planner update makes implementation easier once advertisers decide to move forward. However, the ability to apply suggested changes with one click makes reviewing those recommendations just as important.

More Testing Comes Alongside More Automation

Google continues to expand how much automation can influence Search campaign management, from bidding and budgets to how AI Max finds additional opportunities.

More experimentation capabilities give advertisers a better way to evaluate those changes using their own performance data before applying them more broadly.

As these tools roll out, advertisers have more options to test how Google’s recommendations and automated features perform within their specific accounts. That can provide a stronger basis for deciding which changes to adopt and where existing strategies still perform better.