PMax Audience Signals: How to Guide Google’s AI Toward Your Best Customers
Performance Max campaigns promise automation, but without the right guidance, that automation can burn through your budget chasing the wrong people. Audience signals are your primary tool for steering Google’s machine learning toward users who actually convert—not just click.
In this guide, I’ll break down exactly what audience signals are, how they work, and how to use them strategically based on what I’ve seen across hundreds of accounts over 17+ years in Google Ads.
If you want to explore all the posts I have written on the topic of audience signals start here: Google Ads Signals & Value Hub
What Are PMax Audience Signals? (Answer the Query Fast)
Performance Max audience signals are suggestions you provide to Google’s algorithm about who is most likely to become a customer. They’re not hard targeting rules—they’re hints that help the machine learning models understand what a good prospect looks like for your business.
These signals live at the asset group level, which means each asset group in your PMax campaign can have its own distinct audience configuration. They help speed up the learning phase by giving Google a starting point, and you can change audience signals at any time without rebuilding your campaign from scratch.
Here’s how it actually works: You feed Google your first party data (past customers, website visitors), custom segments (search terms, competitor URLs), detailed demographics, and interest-based audience signals. Google then uses your signals plus its own data from across Search, YouTube, Display, Gmail, and Discover to find more users who behave like your converters—even if they weren’t in your original lists.
Quick example: A local HVAC company might add audience signals including:
A customer match list of past service customers
Custom segments built around search terms like “AC repair near me” and “emergency HVAC service”
In-market audiences for home services
Google takes these inputs and expands reach to similar users across all placements, prioritizing those who look most likely to book an appointment.
From my perspective, getting performance max audience signals right is one of the fastest ways to cut wasted spend in new or underperforming PMax campaigns. When I audit accounts, missing or poorly configured signals are often the first thing I fix.
How Performance Max Uses Audience Signals Under the Hood
When you launch a PMax campaign with audience signals, you’re essentially pointing Google’s AI toward your most likely buyers during the critical first 2-4 weeks of learning.
During this phase, Google’s machine learning models use your signals as a starting point to determine who sees your ads. But here’s the key distinction: signals influence where ads show, but they don’t cap or restrict delivery. If Google predicts better conversions or a cheaper CPA from users outside your specified audiences, it will absolutely go after them.
The algorithm draws on multiple inputs to build its understanding:
Recent search behavior and search queries
On-site behavior (pages visited, time on site, cart activity)
YouTube engagement patterns
App usage data
Demographic signals (age, income, location)
Your first party data signals from customer lists and remarketing
Timing matters. After you add or adjust audience signals, expect 10-14 days before you see significant optimization changes. This is why impatient, rapid-fire edits are risky—you may reset the learning phase before the algorithm has enough data points to optimize properly.
One frustration worth acknowledging: Google does not show performance broken out by individual signal. You can’t see “remarketing list drove X conversions” versus “custom segment Y drove Z conversions.” This opacity is exactly why structure and testing matter—topics I’ll expand on later in this article.
Types of Audience Signals You Can Use in PMax
This section walks through the main signal types you can feed into a PMax asset group. Understanding the options helps you build a signal strategy that actually matches your business, rather than just checking boxes.
The core categories are:
| Signal Type | What It Covers |
|---|---|
| First-party data | How users have interacted with your business (visitors, leads, customers) |
| Custom segments | Keywords, URLs, and apps that indicate intent |
| Demographics | Age, gender, parental status, household income |
| Interest & in-market | Google’s predefined audiences based on habits, interests, and recent purchase intent |
For most small to mid-sized businesses, first-party data and high-intent custom audience segments are the highest-impact starting points. Broader audience signals like affinity audiences work better as secondary layers once you’ve established a converting baseline.
First-Party Data: How They’ve Interacted With Your Business
First-party data includes users who have already touched your business in some way: visited your website, filled out a form, called your office, made a purchase, or exist in your CRM. This is your own data—the gold standard for training Google on what your ideal customer actually looks like.
Concrete sources to pull from:
Remarketing lists from Google Ads or GA4 (website visitors, cart abandoners)
Customer Match uploads from your CRM or email platform
Data from past Smart Shopping or Standard Shopping campaigns
Call tracking data where available
Examples of high-value lists to create:
All website visitors in the last 30 days
All website visitors in the last 180 days
Leads who haven’t converted to customers yet
High-value customers from the past 12 months
Repeat purchasers
Why are these signals so powerful? They train Google on what your actual buyers look like and let the algorithm build look alike audience patterns across Search, YouTube, Display, Discover, and Gmail. Instead of guessing, Google starts with a template of proven converters.
In my audits, missing or misconfigured first-party signals is one of the most common reasons PMax over-spends on low-intent traffic. Business owners often skip this step because uploading lists feels tedious—but it’s the single highest-leverage action you can take.
Your Custom Segments: Search Terms, URLs, and Apps
Custom segments let you build audiences around what people are actively searching for or engaging with online. Unlike remarketing (which targets past visitors), custom segments target user groups based on their behavior across the web.
Keyword-based custom segments: Use actual high-intent search terms that historically convert or clearly signal buying intent. Examples:
“Emergency plumber Columbus” (not “how to fix a leaky faucet”)
“B2B SaaS demo software” (not “what is SaaS”)
“Best orthodontist for teens” (not “braces vs invisalign comparison”)
The distinction matters. You want performing search terms that indicate someone ready to buy, not informational queries from people just researching.
URL-based custom segments: Add URLs of competitor product pages, category pages, or landing pages closely related to your offer. Skip generic homepages—Google needs specific signals about what content matters.
App-based custom segments: When relevant, add apps your ideal customer likely uses. For B2B, this might be industry tools like Salesforce or HubSpot. For consumer electronics, it might be specific shopping or comparison apps.
Example scenarios:
Local dentist: Build a custom segment around terms like “dentist accepting new patients [city],” “emergency dental care,” and “teeth whitening cost.” Add URLs from competitor dental practices in the area. Skip broad terms like “dental health tips.”
B2B software company: Create segments around “project management software for agencies,” “alternative to [competitor name],” and “best team collaboration tools.” Include URLs from competitor pricing and feature pages.
The goal is focus. A messy, broad custom segment teaches Google nothing useful about your target audience.
Demographic Targeting in Audience Signals
Demographic signals help narrow or guide Google based on age, gender, parental status, and household income. These can be valuable when your offer has clear demographic boundaries.
When demographics are especially useful:
Age-specific offers (retirement planning, college prep, pediatric services)
Gender-specific products (women’s fitness, men’s grooming)
Income-sensitive pricing (luxury services vs. budget options)
Parental status triggers (childcare, family vehicles, home sizing)
However, remember that in Performance Max, demographics are still “soft” signals. Google can decide to show ads outside your preferred segments if it predicts strong performance there. You’re providing guidance, not setting hard limits.
Best practice: Avoid over-restricting demographics at launch unless you have strong historical data proving certain groups don’t convert. Start broader and exclude obvious poor performers once you have enough data points to make informed decisions.
Examples:
Targeting parents aged 25-44 with household income in the top 30% for a private preschool
Focusing on ages 55+ for a retirement planning service
Excluding household income brackets that historically produce low value customers for high-ticket home renovations
Additional Segments: Interests, Habits, and In-Market Behavior
These are Google’s predefined audiences based on interests (affinity audiences), habits, and in-market signals—users actively researching a specific product or service category.
Focus on in-market and life events segments closely aligned with purchase decisions:
In-market for business services
In-market for home renovation
Life event: new business formation
Life event: recently moved
In-market for consumer electronics
These segments capture recent purchase intent, which makes them more valuable than broad affinity audiences that reflect general interests without immediate buying signals.
A word of caution: Very broad interest segments like “Business & productivity” or “Travel buffs” should usually be layered in only after you have strong performance from first-party and custom search segments. They can dilute your signal quality and lead Google toward users who are interested but not ready to buy.
Example: A local kitchen remodeling company added the narrow in-market segment “Kitchen & dining furniture” alongside their first-party data and custom segments. This helped refine their PMax campaign to reach users actively researching kitchen upgrades, not just people who follow home design accounts on Instagram.
Combining these segments with good creative—messaging that speaks directly to that interest or life event—is more effective than relying on the segments alone.
How to Add Audience Signals to a Performance Max Asset Group
This section walks through the actual Google Ads interface steps to attach audience signals to an existing or new PMax asset group. The process is straightforward once you know where to look.
Signals are set at the asset group level, not the campaign level. This means each asset group needs its own audience signal configuration—you can’t just set signals once for the entire campaign.
High-level flow:
Select your PMax campaign
Navigate to the specific asset group
Click “Edit audience signals” (or “Signals”)
Add Your Data (remarketing and customer lists)
Add custom segments
Add demographics and interest-based segments
Save changes
When viewing asset groups in a table format, you may need to click into “Summary” or the pencil icon to access the audience signals panel. The interface changes occasionally, but the signals section is always accessible from within the asset group editing screen.
After saving, note the date. It can take 1-2 weeks before the impact of new signals becomes visible in performance trends. Don’t panic if you don’t see immediate changes.
Prerequisites Before You Add Signals
Before setting audience signals, make sure your foundation is solid. Feeding signals into a broken tracking setup just teaches Google the wrong outcomes.
You need:
Accurate conversion tracking via Google Ads or GA4
Clear campaign goals (target CPA, target ROAS, or maximize conversions with a budget cap)
Clean account structure without duplicate or conflicting campaigns
Conversion actions should be meaningful: Configure at least one or two actions that represent actual business value—lead form submissions, phone calls over 30 seconds, purchases, booked appointments. Avoid tracking micro-conversions like page views as primary goals.
Lists should be ready: Ensure your customer match list and remarketing audiences are properly imported into your Google Ads account, consent-compliant, and large enough to be useful. Google generally needs hundreds or thousands of users on a list for effective signal building.
In my audits, I often pause signal work until tracking is fixed. If your conversion data is inaccurate—counting spam leads as conversions, missing phone calls, or attributing to the wrong campaigns—adding audience signals just accelerates waste.
Pre-flight check:
[ ] Primary conversion action configured and tested
[ ] Google Ads and GA4 properly linked
[ ] Customer lists uploaded and processed
[ ] Remarketing lists populated (check Audience Manager)
[ ] Campaign goal clearly defined
Step-by-Step: Adding Audience Signals in the Interface
Here’s a concise walkthrough based on the current Google Ads layout. Button labels may shift slightly over time, but the core process remains consistent.
Log into Google Ads and navigate to “Campaigns” in the left sidebar.
Select your Performance Max campaign from the campaign list.
Click into the specific asset group you want to configure. You’ll see your asset groups listed—click the name or the edit icon.
Find the “Audience signals” section. This typically appears in a right-hand panel or within the asset group editing screen. Look for “Signals” or “Audience signals.”
Add Your Data first. Click to add remarketing lists and customer match lists. Prioritize:
High-value customer lists
All converters from the past 180-540 days
Website visitors (30-day and 180-day segments)
Add custom segments. Create or select segments based on high-intent search queries and relevant URLs. Use specific custom segments rather than generic ones.
Add demographics. Set any relevant demographic parameters (age ranges, parental status, household income) based on your customer profile.
Add interest and in-market audiences. Layer in narrow in-market or life events segments that align with purchase decisions.
Save your changes.
Document the date in a simple tracking sheet. When you review performance in 2-3 weeks, you’ll want to correlate changes with specific signal updates.
How Audience Signals Impact PMax Performance (Benefits & Tradeoffs)
Strong audience signals deliver three main advantages: faster ramp-up, more relevant traffic, and better budget efficiency. When configured properly, they transform PMax from a black box into something closer to a guided system.
Faster learning phase: Signals help Google skip some of the “guessing” phase at launch by anchoring initial optimization on known converters and high-intent behaviors. Campaigns with robust signals can reach optimal performance in days versus weeks without them—potentially cutting early-phase costs by 15-25% through reduced irrelevant impressions.
Improved ad relevance: When your signals match your assets (headlines, images, videos), you create coherent messaging that resonates with the right audience. This typically increases CTR, engagement, and conversion rates because users see ads that actually speak to their needs.
Better budget allocation: Signals help prioritize higher-probability prospects, reducing wasted spend on completely cold, unqualified traffic. For small businesses with limited budgets, this efficiency is critical.
The tradeoffs: Over-narrow or poorly chosen signals can slow learning, restrict scale, or push Google to find “look-alikes” that don’t actually match your best customers. Signals are a guide, not a guarantee—and bad signals create bad guidance.
Enhancing Targeting Accuracy Without Hard Limits
Audience signals operate as “soft guidance.” They steer the algorithm, but Google can still reach outside these audiences when it sees better opportunities. This is fundamentally different from legacy manual targeting, where you could explicitly include or exclude audiences with full control.
In PMax, you’re essentially saying “start here” rather than “only go here.”
Judge success by outcomes, not audience matching. The right metric is overall campaign performance—CPA, ROAS, lead quality—not how neatly traffic matches your audience lists. If Google finds relevant audiences you didn’t anticipate, that’s the system working as intended.
Example: A coaching client selling premium home organization services provided signals focused on “luxury homeowners” and high-income demographics. The algorithm discovered that “value shoppers” who had recently moved (a life event signal) converted at higher rates. The original signals weren’t wrong—they just weren’t the whole picture.
The Insights tab in Google Ads can surface some of these discovered audience categories, even though per-signal breakdowns aren’t exposed. Check it regularly to understand where Google is finding success.
If you want to read about my deeper POV on targeting read this post: Search Isn’t Matching Intent — It’s Matching Predictions: Inside the Predictive Era
Budget Allocation and Wasted Spend
In PMax, you have limited control over placements and search terms. Audience signals become one of the main levers to reduce waste and inform Google about who deserves your ad spend.
Strong signals (first-party data + high-intent custom segments) push more budget toward users similar to your buyers. This typically improves ROAS or lowers CPA because you’re spending on qualified traffic rather than random impressions.
Weak signals (generic interests, vague keywords, untargeted demographics) lead to high impression volume but poor lead quality. You’ll see activity in your account, but the leads won’t convert to revenue.
During audits, I often see PMax overspending on low-quality query themes because the audience signals were built around brand awareness terms instead of buying terms. The campaign looks busy, but the business owner is paying for tire-kickers, not customers.
When budget is limited (common for small businesses): Treat signals like priority lanes for your spend. They must be sharply aligned with revenue, not vanity traffic. Every dollar wasted on non-buyers is a dollar that could have reached your ideal customer.
Best Practices for PMax Audience Signals (From 17+ Years in Google Ads)
This is where I give you concrete, battle-tested guidance based on what actually works in real accounts—not theory, not Google’s marketing materials.
My focus is on small and mid-sized businesses that can’t afford months of inefficient learning. You need PMax to prove itself quickly or risk burning through budget with nothing to show for it.
The core principles:
Start with high-intent, specific audiences
Leverage first-party data aggressively
Structure asset groups around clear themes
Align creative assets with your signals
Test and iterate without constant tinkering
Data quality beats complexity every time. Fewer, better signals consistently outperform giant, messy lists. Treat this section as a checklist to revisit whenever you launch or overhaul a PMax campaign.
Start With High-Intent, Specific Audiences
Begin with the narrowest, highest-intent signals you have: past converters, hot leads, and search terms clearly indicating purchase intent (not just information gathering).
Google will automatically expand reach beyond these seeds, so starting specific doesn’t mean you’ll stay tiny. It anchors the machine learning models on the right direction—toward people who actually buy.
High-intent vs. low-intent examples:
| Business Type | High-Intent Signal | Low-Intent Signal |
|---|---|---|
| Local plumber | “emergency plumber near me” | “how to unclog a drain” |
| eCommerce shoes | “buy running shoes size 10” | “best running shoe brands” |
| B2B software | “CRM software demo” | “what is CRM” |
| Dental practice | “dentist accepting new patients” | “dental hygiene tips” |
Avoid launching PMax with only broad custom segments like “marketing tips” or “plumbing DIY.” These flood campaigns with non-buyers who are researching, not purchasing.
Review conversions weekly at first to confirm the leads or sales coming in actually match your ideal customer—not just cheap clicks that look good in the dashboard but never turn into revenue.
Leverage First-Party Data Aggressively (Within Privacy Rules)
Upload customer lists and build remarketing segments as early as possible, even if the lists are relatively small. Something is better than nothing.
Segment by value where you can:
High-LTV customers vs. one-time buyers
Repeat purchasers vs. first-time customers
Closed-won B2B deals vs. all leads
High value customers vs. low value customers
Feeding these back into PMax turns past wins into a training set. Google uses your new customers and repeat buyers as templates for finding similar eligible users.
Data quality matters. If your lists are full of unqualified leads, spam submissions, or customers who churned immediately, you’re teaching Google the wrong patterns. Clean your lists first—remove bad leads, disqualified prospects, and refund customers—before using them as signals.
Always respect consent and platform policies. Customer Match requires proper data collection consent, and Google has specific requirements for list formatting and usage.
Structure: One Core Audience Theme Per Asset Group
Avoid dumping every audience list into a single asset group. Instead, group signals by clear themes so you can actually diagnose what’s working.
Examples of themed asset groups:
High-value customers + look alike audience signals
Cart abandoners (remarketing focus)
Competitor brand searchers (using competitor’s brand names in custom segments)
Local high-intent service queries
Specific product category buyers
Although Google doesn’t show per-signal performance, you can compare multiple asset groups to see which audience themes pull their weight. This gives you actionable data even within PMax’s opacity.
Limit active asset groups at first. If your budget is spread across too many asset groups, none will get enough data points to optimize properly. Start with 2-4 focused groups rather than 10 diluted ones.
In coaching calls, I often restructure accounts live on-screen—consolidating chaotic asset groups into a few purposeful ones. The improvement is usually immediate because the algorithm finally has clear direction.
Align Creative Assets With Your Audience Signals
Audience signals work best when the matching creative speaks directly to that particular audience’s needs and language. Generic ads paired with specific signals is a recipe for mediocre performance.
Tailor messaging by theme:
| Audience Theme | Messaging Approach |
|---|---|
| Competitor searchers | Comparison messaging, “switch and save” angles |
| Remarketing (cart abandoners) | Urgency, guarantees, removed friction |
| Cold high-intent | Clear problem-solution framing, credibility signals |
| Past customers | Loyalty offers, new products, referral incentives |
Use search term insights and audience insights to refine messaging over time based on what real users respond to. Your tailored ads should feel like a natural extension of the user’s intent.
Consistent messaging between audience, ad, and landing page boosts conversion rates enough to offset PMax’s lack of granular placement control. When everything aligns, the funnel works.
Misaligned creative—generic headlines paired with highly specific signals—is a frequent cause of mediocre PMax performance in real accounts. Don’t waste good signals on lazy ads.
Test, Observe, and Iterate Without Constant Tinkering
Run meaningful tests: change one major audience factor at a time and allow at least 2-3 weeks (depending on volume) before judging results.
PMax blends so many signals that over-editing audiences every few days keeps the algorithm in permanent “learning” mode. You never get stable performance because you never let optimization complete.
Better approaches:
Use separate asset groups or draft/experiment campaigns to test significantly different audience signal strategies
Document every change with dates so you can correlate performance shifts
Set specific test timeframes before you start (e.g., “We’ll evaluate after 14 days and 50+ conversions”)
Leverage the Insights tab to spot new audience categories that consistently drive conversions. When you find patterns, incorporate them into more intentional signals rather than ignoring Google’s discoveries.
For low-volume accounts, I use coaching calls to set clear test timeframes and guardrails. Business owners sometimes panic and reset campaigns too early—before there’s enough data to learn anything useful.
Common Mistakes With PMax Audience Signals (And How to Fix Them)
This section is based on real-world audits where PMax wasn’t profitable or lead quality was poor. These patterns show up repeatedly across different industries and business sizes.
Core mistake patterns:
No first-party data used at all
Signals built around curiosity instead of intent
Everything stuffed into one asset group
Measuring only volume (clicks, impressions) instead of quality (lead value, ROAS)
For each mistake, there’s a straightforward fix you can implement without rebuilding your whole account. The goal is to align signals with your actual paying customers—not just traffic sources that look busy in Google Ads.
When issues are complex or you’ve been struggling for months, a structured Google Ads audit or a one-hour coaching session can shortcut the trial and error. Sometimes fresh eyes find what you’ve been missing.
Relying on Broad Interests Instead of Intent
The mistake: Building audience signals only around broad interests like “Business & productivity” or “DIY & home improvement” that reflect hobbies more than purchase decisions.
This usually leads to lots of impressions and clicks but low-quality leads, freebie seekers, or people far from a buying decision. Your dashboard looks active, but your sales team complains about garbage leads.
The fix: Rebuild key asset groups around high-intent custom segments and first-party converters. Add narrow in-market or life events segments as secondary layers—not primary signals.
Review search term insights to identify phrases used right before conversions. Those specific queries should seed new custom segments because they represent proven buyer behavior.
Before and after example:
Before: A home services company used broad affinity audiences like “Home & garden enthusiasts” and “DIY” as primary signals. Lots of traffic, very few booked appointments.
After: Rebuilt signals around specific custom segments (“water heater installation cost,” “emergency plumber [city]”) plus customer match list of past clients. Lead quality improved within two weeks, and cost per booked job dropped by over 30%.
Ignoring or Misusing First-Party Data
The mistake: Leaving customer match lists and remarketing lists unused, or using bloated lists that mix good and bad leads together with no value tiers.
This confuses the algorithm about what a “good” customer looks like and slows learning. Google’s machine learning models can’t distinguish between a high-value customer and someone who submitted a spam form if they’re in the same list.
The fix:
Export past leads or customers from your CRM
Clean the data—remove spam, disqualified leads, refund customers
Segment by value (high-value buyers vs. general leads)
Re-upload as other segments with clear labels
Prioritize cleaned lists in PMax audience signals
Use these cleaned lists as a benchmark for new traffic quality. If new leads don’t resemble your best customers, your signals may need refinement.
I frequently find mislabeled or duplicated lists during audits. Simply fixing list hygiene—without changing anything else—can materially improve PMax campaign performance.
When You Should Get Expert Help With PMax Audience Signals
While many businesses can set up basic signals themselves, there are clear signs that indicate you should seek expert support rather than continuing to experiment alone.
Red flags that warrant outside help:
High spend with consistently low-quality leads
Strong Search or Shopping campaign performance but weak PMax results
Leadership demanding PMax usage without a clear strategy
Conversion tracking you don’t fully trust
Months of “learning” with no improvement
A focused Google Ads audit can quickly reveal whether audience signals, tracking, or broader account structure are the main blockers. Often it’s a combination—signals can’t fix broken tracking, and good tracking can’t fix absent signals.
How I work with clients:
Second-opinion audits: I review your account, identify where money is leaking, and give you a clear picture of what’s working and what’s not
1:1 coaching calls: We get on a call and fix issues live in your account—no waiting for a report, no vague recommendations
90-day build-and-train engagements: I build or restructure your campaigns and train you or your team to manage them profitably
If you feel “blindfolded” by PMax automation—spending money but unsure whether it’s actually working—at least get a one-time second look at your signals and conversion data. You don’t need to commit to ongoing management to get clarity on where you stand.
Audience signals are powerful, but they’re just one piece of a larger system. Getting them right requires accurate tracking, clean data, aligned creative, and realistic expectations. When those pieces work together, PMax stops feeling like a gamble and starts delivering accountable results.
Ready to find out if your PMax audience signals are actually working? A structured audit can reveal exactly where your budget is going and whether your signals are guiding Google toward buyers or wasting spend on non-converters. Learn more about getting a second opinion on your Google Ads account.
