How do I exclude irrelevant audiences?

Clarify what “irrelevant” means before you start excluding

When advertisers say they want to “exclude irrelevant audiences,” they usually mean one (or more) of these problems: people who will never buy (wrong intent), people who can’t buy (wrong geography, age restrictions, B2B vs B2C mismatch), people who already bought (existing customers you don’t want to pay to re-acquire), or people who can technically buy but consistently drive poor ROI (low conversion rate, low average order value, low lead quality, high refund rate).

The most expensive mistake I see is excluding based on a “feels wrong” signal (like low CTR or a placement that looks odd) without tying it back to a measurable business outcome. Your exclusions should be grounded in conversion quality, not just traffic quality.

A fast diagnostic checklist (do this before touching exclusions)

• Confirm your primary conversion is correct (and that you’re not optimizing to something too soft like page views when the real goal is qualified leads or purchases).
• Segment performance by audience, demographics, and inventory to find patterns (for example: “Unknown” age/gender, certain household income tiers, specific audience segments, or specific placements/apps/videos).
• Check where expansion is happening (for example: settings that intentionally reach beyond your selected audiences, or campaign types that treat audiences as guidance rather than strict targeting).
• Look for “existing customer leakage” if you’re running acquisition campaigns but using broad targeting.

Once you know which kind of irrelevance you’re dealing with, the right exclusion method becomes obvious—and you avoid cutting out profitable reach by accident.

Use the right exclusion lever for the campaign type (not all exclusions behave the same)

1) Exclude specific audience segments (the most direct “audience” fix)

If you’ve identified audience segments that consistently underperform—whether they’re affinity-style segments, in-market segments, or your own first‑party lists—you can exclude them at the campaign or ad group level. Practically, this is how you stop paying for known-bad pockets while keeping the rest of the campaign intact.

Two important realities to plan around. First, exclusions are typically added after a campaign exists (not during creation), so you’ll often start by observing performance and then tighten. Second, exclusions may not fully apply to people who have opted out of ad personalization, so you should still use other controls (like creative alignment, keywords, placements, and geography) to protect efficiency.

For app-focused campaigns, exclusions can be more constrained. In many cases you’ll need to build an exclusion segment first, and exclusions are applied at the campaign level (not ad group level), so think in terms of broader guardrails rather than granular sculpting.

2) Use “Observation” first, then exclude (or switch to stricter targeting only when it’s justified)

In Search and Shopping-style setups, audiences are often used in Observation mode by default. That’s usually the right starting point: you get clean performance readouts by segment without restricting reach. Once you’ve got statistically meaningful data, you can exclude truly irrelevant segments, or—if you have a very specific use case—build a separate campaign/ad group that targets only a narrow audience (for example, a remarketing-only search campaign).

In Display-style setups, you have more flexibility to use Targeting and Observation across different targeting types. The best practice is to observe first when you’re unsure, then convert winners into true targeting and convert losers into exclusions. This prevents over-tightening too early and starving the algorithm of conversion volume.

3) Turn off (or control) automated audience expansion where you can

Modern campaigns frequently include automated reach features designed to find additional converters beyond your manually selected segments. That’s great when the campaign is profitable, but it can be a major source of “irrelevant audience” complaints when conversion tracking is weak, budgets are tight, or the offer is niche.

For Display, Demand Gen, and Video Action–style setups, you can typically toggle optimized targeting at the ad group level. When you turn it off, your audience choices behave more like strict boundaries; when it’s on, your audiences act more like starting signals. If you’re fighting waste, consider turning it off temporarily while you clean up targeting and measurement—then re-test once you’re confident the system is learning from high-quality conversions.

For highly automated campaign types, audiences may be guidance only. For example, audience signals can help steer automation, but ads may still serve beyond those signals if the system believes it can hit your goals. In those cases, think “improve the inputs and add guardrails” rather than expecting a pure audience lock.

4) Use demographic exclusions and controls (especially “Unknown” segments)

Demographic controls can be a powerful way to remove obviously irrelevant reach. Common examples include excluding age brackets that can’t legally buy your product, excluding age ranges that never convert, or excluding “Unknown” demographics if you see consistent low-quality performance (with the caveat that “Unknown” can include perfectly valid customers whose signals aren’t available).

Be aware that certain sensitive verticals have restrictions on using demographics (and some location granularity) for targeting in specific regions. If you advertise in regulated categories like housing, employment, or consumer finance in the United States and Canada, expect limitations on what demographic targeting can be used, and plan to lean more heavily on non-demographic levers like keyword intent, creative, landing page alignment, and compliant location targeting.

5) Exclude “where ads show” to remove irrelevant contexts (placements, content controls, and brand safety)

Many “irrelevant audience” issues aren’t really audience problems—they’re context problems. If your ads appear on low-quality apps, off-topic videos, or websites that attract accidental clicks, you’ll feel like your audience is wrong even when your targeting is fine.

Placement exclusions let you block specific websites, videos, channels, or apps. You can apply exclusions at the ad group, campaign, account, or manager level depending on how broadly you want the protection. This is one of the fastest ways to clean up waste once you’ve identified repeat-offender placements.

Content suitability controls go beyond single placements. They help you exclude categories, content types, content labels, content keywords, and content themes. The key nuance is that not every control applies to every inventory surface. Some settings cover certain video placements and partner inventory but not every feed or format. So if you exclude something and still see surprising exposure, it’s often because that control doesn’t cover that specific surface rather than because the system ignored you.

Also note that brand-safety controls evolve. Certain label-based controls may not apply to all video surfaces over time, so you should periodically confirm which suitability settings actually cover the placements you care about, and rely on the controls that are explicitly supported for that inventory.

6) Eliminate irrelevant search traffic (negative keywords and account-level guardrails)

In Search and Shopping inventory, the most common “irrelevant audience” is simply irrelevant intent. The cleanest fix is negative keywords. If you’re seeing repeat patterns across multiple campaigns, account-level negative keywords can act as a global firewall so the same bad queries don’t leak into every new build.

For automated, multi-inventory campaigns, new control features have continued to roll out over time (including more robust negative keyword options). The practical takeaway: if you’re running a highly automated campaign type and struggling with irrelevance, your first step should be to implement the strongest supported query controls available in that campaign type, then refine creatives and landing pages to better pre-qualify clicks.

A practical workflow to exclude irrelevant audiences without breaking performance

Step 1: Start with measurement and segmentation, not exclusions

Give yourself a clean baseline. Run for long enough to get signal (not just a handful of clicks), then segment performance by audience segment, demographics, and where ads showed. Look for pockets with clearly worse conversion rate, CPA, ROAS, or lead quality. This is where exclusions pay for themselves quickly.

Step 2: Apply exclusions in layers (from least risky to most aggressive)

I generally recommend tightening in this order: first remove obviously bad placements and clearly irrelevant search intent, then exclude consistently poor audience segments, then consider demographic exclusions, and only after that consider disabling expansion features or switching from Observation to strict Targeting. This sequencing protects volume and avoids forcing the system into a corner where it can’t learn.

Step 3: Re-check expansion settings and automation expectations

If your campaign type treats audiences as signals (not strict gates), you won’t “fix” irrelevance with audience exclusions alone. You’ll need a combination of guardrails (query controls, placement/suitability controls, geo/device controls) and better training data (high-quality conversion actions, values, and accurate attribution windows). When those are solid, automation tends to find the right customers more reliably—and you’ll need fewer exclusions overall.

Step 4: Monitor the side effects (the hidden cost of exclusions)

Every exclusion reduces reach. That’s fine when it removes waste, but it can also increase costs if you over-restrict and force the campaign to compete harder in a smaller pool. After each tightening move, watch three things: impression volume (are you starving delivery?), conversion volume (did you fall below the learning threshold?), and marginal CPA/ROAS (did efficiency actually improve, or did you just shift traffic around?).

Step 5: Make exclusions a recurring hygiene habit

Markets change, inventory changes, and campaign automation adapts. The best accounts treat exclusions as ongoing maintenance, not a one-time cleanup. A monthly cadence is usually enough for stable accounts; weekly is better for high-spend or fast-moving promotions.

If excluding “irrelevant audiences” in Google Ads feels messy, it’s often because the problem isn’t just one setting: you typically need to separate bad intent (queries), bad contexts (placements/content), and truly low-quality segments (audiences/demographics), then tighten gradually so you don’t choke delivery or starve automation of learning data. Blobr is built for that kind of ongoing hygiene: it connects to your Google Ads account, continuously spots where spend is leaking, and turns best-practice checks into concrete recommendations; for example, its Negative Keywords Brainstormer can suggest new negatives to block recurring off-target searches, while the Negative Keywords Cleaner helps you avoid over-blocking by refining match types—useful guardrails when “irrelevant” traffic is really coming from query expansion rather than the audience list you started with.