Performance Max finally has real demographic exclusions. You can now exclude specific age brackets (18-24, 25-34, 35-44, 45-54, 55-64, 65+) and genders at the campaign level, not just suggest them as audience signals. These are hard exclusions: Google won't show your ads to blocked segments, period. Early adopters report 15-30% reductions in wasted ad spend by excluding demographics that can't or won't convert.
The Rollout Timeline
January 2025: Google announced age-based demographic exclusions coming to Performance Max campaigns in beta.
April 2025: Age exclusions started appearing in accounts. Previously, demographic exclusions only worked at the asset group level, you could exclude 18-34 OR 25-48, but not both. Campaign-level controls let you exclude any combination of age brackets.
July 2025: Gender exclusions launched in beta. First time PMax offered any gender targeting control beyond audience signals.
August 2025: Both features merged into a single "Demographic Exclusions" section in campaign settings.
December 2025: Full rollout to most accounts. No longer requires beta access.
Why This Actually Matters
Before demographic exclusions existed:
- You run a luxury spa. Services are adults-only, minimum age 18. Your PMax campaign serves ads to teenagers searching "spa day near me" because Google's algorithm thinks some might convert. You burn $400 last month on clicks from users who legally can't book.
- Or you sell men's grooming products. You add "men interested in grooming" to your audience signals. PMax still shows 35% of impressions to women because the algorithm predicts gift purchases. Sounds smart, except your historical data shows women account for 8% of actual conversions. You're spending $2,600 on the wrong demographic.
The difference between audience signals and demographic exclusions: Signals are suggestions. Exclusions are rules.
Before August 2025, if you added "women 25-45" to your audience signal, PMax could still serve ads to men 65+ if the algorithm predicted a conversion. Now when you exclude males and 65+, those segments see zero impressions.
How to Set Up Demographic Exclusions
Step 1: Open your Performance Max campaign → Settings → scroll to "Demographic exclusions"
Step 2: Enable age exclusions and check the boxes for age ranges to exclude:
- 18-24
- 25-34
- 35-44
- 45-54
- 55-64
- 65+
- Unknown (users with unidentified age)
Unselected ages will receive impressions. You can exclude multiple non-contiguous ranges (18-24 AND 65+, for example).
Step 3: Configure gender exclusions in the same section:
- Male
- Female
- Unknown
Important: Google estimates gender using account data (if users specified it) or contextual signals (browsing behavior). 15-25% of users typically fall into "Unknown."
Step 4: Save changes. Exclusions apply immediately across all PMax inventory: Search, Display, YouTube, Shopping, Discover, Gmail.
For more details on Performance Max optimization, see Google's official Performance Max visibility and control guide.
5 Use Cases That Actually Work
1. Age-Restricted Products
Scenario: Craft brewery selling direct-to-consumer beer online.
Problem: Ads appeared to under-21 users, violating regulations and wasting budget.
Solution: Excluded 18-24 age bracket. Spend decreased 15%, conversions increased 23%.
2. Gender-Specific Product Lines
Scenario: Retailer with separate campaigns for women's activewear and men's athletic gear.
Problem: Women's campaign showed 38% of impressions to males despite audience signals.
Solution: Excluded males from women's campaign, females from men's. CTR improved 18%, CPA dropped 31%.
3. High-Ticket Services with Narrow Demographics
Scenario: Medical spa offering anti-aging treatments ($500-$5,000 price range).
Problem: Significant wasted impressions on under-30 users.
Solution: Excluded 18-24 and 25-34 to focus on 35+. Conversion rate increased 42%.
4. Age-Gated Products (Medicare, Senior Services)
Scenario: Medicare supplement insurance (only available to 65+).
Problem: 60% of ad spend went to under-65 users who couldn't purchase.
Solution: Excluded all brackets except 65+. Same conversions with 55% less spend.
5. Testing Demographics for Optimal Allocation
Scenario: Professional certification courses, unsure which ages convert best.
Problem: One catch-all campaign made demographic testing impossible.
Solution: Split into two campaigns, one targeting 25-44, another 45-64. After four weeks, 25-44 showed 2.8x higher ROAS, so shifted 70% of budget there.
4 Common Mistakes to Avoid
Excluding without data: Check your demographic reports before excluding anything. One home services advertiser excluded 18-24 assuming young adults don't own homes. Data showed 18-24 actually converted at 1.7x the rate of 45-54, first-time homebuyers were their best customers.
Ignoring the "Unknown" segment: Represents 15-30% of traffic. Before excluding it, test performance separately. You might be blocking qualified buyers.
Forgetting about gift purchases: A men's cologne brand excluded women entirely. Turns out 35% of revenue came from women buying gifts. Revenue recovered after re-including women.
Using stereotypes instead of data: A gaming peripherals company assumed only 18-34 males buy mechanical keyboards. Data showed 45-54 professionals, who type 8+ hours daily and have disposable income, were highest-value customers.
What Happens After You Add Exclusions
Learning period: Expect 7-14 days of fluctuating performance while Google's AI re-optimizes for your new demographic constraints.
Reach reduction: That's the point. One luxury watch brand saw reach drop 40% after excluding under-35. But CPA dropped 52% because they stopped paying for clicks from people who couldn't afford $8,000 watches.
Budget redistribution: Your daily budget stays the same, but redistributes to remaining demographics. Often means higher frequency among target audience, improving brand recognition and conversion rates.
Best Practices
Start broad, then refine: Begin by excluding segments that obviously can't convert (age-restricted products, legal requirements). Run 2-3 weeks, analyze, then test narrower exclusions.
Separate campaigns for vastly different demographics: Teen skincare products and anti-aging serums shouldn't live in one campaign. Create separate PMax campaigns with different creative strategies.
Layer with other signals: Combine demographic exclusions with audience signals, search themes, and geographic targeting. For example:
- Audience: Website visitors
- Search themes: Product keywords
- Geographic: High-converting locations
- Demographics: Exclude non-converting age/gender
Monitor weekly during first month: Check these metrics every 5-7 days:
- Conversion volume (dropped too much?)
- Cost per conversion (improved?)
- Conversion rate by remaining demographics
- Search impression share (maxing out your audience?)
Document everything: Write down why you excluded specific segments. Three months later you won't remember if you based it on data or assumptions.
For more on optimizing PMax campaigns, see our guide on how to use negative keywords in Performance Max.
Tracking Performance
Cost Per Acquisition: Most direct indicator of efficiency. 15-30% CPA reduction is common when excluding irrelevant demographics.
Conversion Rate: Should increase. One B2B software company saw conversion rate jump from 2.3% to 4.1% after excluding 18-24 (their product targets enterprise buyers, not students).
Impressions by Age/Gender: Verify exclusions are working. You should see zero impressions in excluded segments after learning period.
Search Impression Share: Monitor whether you're limiting reach too much. If impression share is 95%+ and you're not hitting budget caps, you might be excluding too aggressively.
Track demographic performance manually through Google Ads reports, or automate the analysis if you're consolidating data from multiple campaigns. Tools like Dataslayer can pull PMax demographic data into dashboards for easier monitoring across accounts, learn more in our Google Ads reporting guide.
Regulatory Considerations
US Financial Services: Cannot exclude by gender due to Equal Credit Opportunity Act. Google automatically disables gender exclusions for finance advertisers.
Housing/Employment Ads: Subject to Fair Housing Act and discrimination laws. Use demographic exclusions only for legitimate business needs, not discriminatory intent.
Age-Restricted Products: Many countries require age verification for alcohol, tobacco, gambling. Demographic exclusions help compliance but don't replace proper age verification at purchase.
GDPR (EU): Document business justification for exclusions. Google's system is GDPR-compliant, but you're responsible for appropriate use.
FAQ: PMax Age & Gender Exclusions
What's the difference between demographic exclusions and audience signals?
Audience signals suggest to Google's AI who might convert, but the AI can ignore them. A campaign with "women 35-54" in audience signals could still show ads to men 18-24 if the algorithm predicts conversions.
Demographic exclusions are absolute rules. When you exclude males and 18-24, those segments get zero impressions. No exceptions.
Can I combine age and gender exclusions?
Yes. You can exclude males AND exclude 18-24 and 65+ simultaneously. For example, a women's health supplement targeting women 25-64 can exclude all males plus the youngest and oldest age brackets.
What happens to the "Unknown" demographic?
Google labels users "Unknown" when it can't determine age or gender. This represents 15-30% of traffic. You can include or exclude Unknown, but excluding it significantly reduces reach. Test Unknown performance separately before excluding.
Do exclusions work across all PMax channels?
Yes. Campaign-level demographic exclusions apply to Search, Display, YouTube, Gmail, Discover, and Shopping. Your ads won't appear to excluded demographics anywhere on Google's network.
How long until exclusions take effect?
Exclusions activate immediately when you save, but you'll see the full impact over 7-14 days as Google's AI re-optimizes bidding, creative combinations, and placements within your new demographic constraints.
Should I create separate campaigns or use one campaign with exclusions?
Depends on how different your messaging is. If you need vastly different creative (teen acne products vs. anti-aging serums), create separate campaigns. If you're selling the same product but avoiding demographics who can't buy (age-restricted items), use exclusions in one campaign.
Can I still use detailed demographics like parental status?
You can add detailed demographics (parental status, household income) as audience signals, but they can't be hard exclusions like age and gender. Only age and gender support true campaign-level exclusions in PMax.
What if excluded demographics were actually performing well?
Remove the exclusion anytime. If you excluded 18-24 based on assumptions but later discover they convert well, uncheck that bracket. The AI will resume targeting them after a brief learning period. Always validate with data.
The Bottom Line
Before demographic exclusions existed, 20-40% of Performance Max budgets went to impressions that couldn't convert because audiences weren't qualified. That's fixed now.
Start by analyzing your demographic performance data. Identify segments that clearly don't convert or can't legally purchase. Implement exclusions conservatively, block only obvious non-converters. Monitor for 2-3 weeks, then refine.
The goal isn't to restrict campaigns so tightly you lose reach. It's to eliminate budget waste on segments that will never become customers.
Next steps:
- Review demographic reports in your current PMax campaigns
- Implement age or gender exclusions in one campaign as a test
- Monitor weekly for 3-4 weeks
- Document results and expand if successful
- Revisit quarterly as your audience evolves
For related PMax optimization techniques, check out Google's November 2025 Performance Max updates on channel reporting and negative keywords.
If you want to track demographic performance across multiple PMax campaigns, you can download reports manually from Google Ads, or automate the analysis by connecting Google Ads to dashboards. Try Dataslayer free for 15 days to pull PMax data into Google Sheets, Looker Studio, BigQuery, or Power BI for consolidated reporting.
