Google just lowered the barriers to measuring what actually works. On October 7, 2026, the company opened self-serve Conversion Lift studies based on users to Search and Performance Max campaigns. Advertisers who meet the thresholds can now run these experiments without calling a Google representative.
The change matters. For years, proving that an extra dollar spent on search terms or a Performance Max campaign truly drove new sales required either high budgets or personal connections inside Google. Now eligible accounts gain direct access. But the bar remains high enough to exclude many smaller players.
Search Engine Land first reported the expansion. Its article details how Search and Performance Max join Display, Video, Demand Gen and App campaigns in the user-based Conversion Lift program. Previously those two formats demanded representative assistance.
Requirements prove strict. Accounts need at least 1,000 observed conversions. Those cannot include conversions pulled from supplementary data sources. Campaigns must carry a minimum budget of $5,000. And the account must track at least one conversion action that Google considers compatible.
Conversion Lift operates through a clean split. It creates a holdout group of users never exposed to the measured campaigns. Their behavior gets compared against users who see the ads. The gap between the two groups estimates incremental conversions. No more guessing from last-click attribution or modeled data alone.
Google’s own help documentation confirms the details. The support page for setting up Conversion Lift based on users lists the supported campaign types explicitly. It notes that iOS-targeted App campaigns and Travel Ads stay excluded. Campaigns in alpha or beta still require a representative.
PPC News Feed spotted the help page update first. Its coverage highlights the new section on supported conversion actions and reporting. It also credits Hana Kobzová for surfacing the change.
This move arrives at a telling moment. Google has pushed Performance Max hard. Many advertisers complain about limited visibility into exactly where budget flows and what drives results. Conversion Lift offers one antidote. It delivers statistical evidence of incrementality rather than relying on the platform’s black-box optimization.
Yet questions linger. The 1,000-conversion threshold and $5,000 budget minimum will keep the tool out of reach for thousands of accounts. Smaller e-commerce brands or lead-generation businesses operating on tighter spends may watch from the sidelines. They continue depending on attribution models that Google itself admits can overstate impact.
And. The holdout methodology carries its own limits. It works best with opted-in, logged-in traffic. Privacy changes and signal loss can create measurement gaps. Google acknowledges this in its documentation.
Recent API updates show Google’s longer-term direction. Version 25.1, released in August 2026, added 24 new lift metrics and read-only access to study data. Those features remain behind an allowlist for now. Search Engine Land covered the release. The pattern looks clear. Google widens access gradually while building more sophisticated measurement tools for larger accounts and agencies.
Performance Max itself continues evolving. Just weeks earlier Google introduced A/B testing for asset groups and automatic promotion extraction from advertiser websites. These features aim to give marketers more control and transparency. Conversion Lift fits the same narrative. Provide better measurement so advertisers feel confident scaling spend.
Independent tests of related AI features reveal mixed outcomes. Some campaigns see solid conversion gains from AI Max. Others experience higher costs with uncertain returns. True incrementality measurement could help advertisers separate signal from noise in those experiments.
So what should sophisticated advertisers do? First check eligibility. Review conversion volume and campaign budgets against the new thresholds. Then design studies carefully. Focus on specific campaigns or objectives where the incremental question carries the highest stakes. Compare results against existing attribution data. Look for patterns.
The reporting now breaks out results by conversion action, category, age, gender and country. That granularity helps. Teams can see which audience segments deliver genuine lift and which appear inflated under standard models.
Google also updated its guidance on supplementary conversion reporting. Statistical modeling now helps measure previously hard-to-track actions like store sales or offline leads. The result aims for a fuller picture of incremental return on ad spend.
But. Not every conversion deserves equal weight. Smart teams will combine Conversion Lift data with their own customer lifetime value models and offline revenue tracking. The tool provides one important data point. It does not replace business judgment.
Larger holding companies and performance marketing agencies stand to benefit most. They already run at scale. Many maintain dedicated measurement teams. Self-serve access removes friction and speeds up testing cycles. Smaller independent brands may need to partner with agencies that meet the thresholds on their behalf.
The timing also coincides with broader shifts in how Google structures campaigns. Local Services Ads migrate into Performance Max. AI Max expands across Search. Automation rules the day. Advertisers who cannot measure incrementality risk flying blind as machines make more decisions.
Google’s documentation stresses one key principle. Conversion Lift measures actions directly driven by ads. It isolates causal impact. In an industry flooded with correlated metrics, that distinction carries real power.
Expect iteration. Google lowered budget minimums for incrementality experiments in late 2025. This self-serve expansion for Search and Performance Max represents the next logical step. Future updates could lower thresholds further or extend geographic lift options more broadly.
For now the message stays direct. If you hit the numbers, run the test. Compare holdout behavior against exposed users. Let the data speak about which campaigns truly grow your business and which merely claim credit for demand that already existed. The tool won’t solve every measurement problem. It does give serious advertisers a sharper lens than they had yesterday.