1) Start by diagnosing where your ads are actually showing (and why)
Separate “where you targeted” from “where you matched”
Before you touch settings, confirm whether you’re dealing with a true geo-targeting problem or a reporting misunderstanding. In location reporting, you’ll typically see a view for the locations you intentionally selected (your targeted locations) and a view for the locations that matched your ads (matched locations). The matched view can include both a person’s physical location and locations they’ve shown interest in, depending on your campaign’s location intent settings.
When advertisers tell me, “My ads are showing outside my target area,” the fastest reality check is comparing targeted locations vs matched locations, then drilling into the most specific level you can (postal code, city, airport, university, district—availability depends on the country and privacy thresholds). This quickly reveals whether the “leakage” is coming from interest-based matching, ambiguous searches (like “near me”), or genuinely irrelevant traffic.
Use distance reporting when you’re a local business
If you’re using location assets (your store or office locations attached to ads), you can evaluate performance by distance from the nearest location. This is one of the most practical ways to refine geo strategy because it ties performance to real proximity, not just city boundaries. If conversions fall off sharply beyond (say) 8 miles, you’ve found a clean optimization lever: tighten targeting, or reduce bids as distance increases.
2) Tighten geo-targeting without accidentally strangling volume
Choose the right location intent: “Presence or interest” vs “Presence”
Most campaigns default to a setting that can reach people who are in your targeted location, regularly in it, or have shown interest in it. This can be excellent for businesses where interest matters (travel, education, real estate, national brands), but it can be painful for businesses that only serve customers physically in-market (local services, in-person appointments, limited delivery zones, regulated/sensitive categories).
If your priority is “calls and leads from people who can actually be here,” switch your campaign’s location targeting intent to the option that only reaches people in or regularly in your targeted locations (“Presence”). Expect impressions to drop—sometimes noticeably—because you’re removing interest-based reach. That’s not a bug; it’s the tradeoff for precision.
Also note a key platform change: since March 2023, location intent options were standardized across the interface and tooling, with “Presence or interest” becoming the default positive targeting behavior and “Presence” becoming the default behavior for location exclusions. In plain terms, the platform is built to include interest by default unless you explicitly narrow it.
Use exclusions like a scalpel (and understand the hierarchy)
Excluding locations is often the cleanest way to refine geographic reach—especially when you want broad coverage but need to remove pockets of waste. Exclusions can be added one-by-one or in bulk, and they’re evaluated in a hierarchy where exclusions can override inclusions when they’re nested. For example, if you exclude a state but target a city inside that state, the city will be excluded because it sits within the excluded boundary. If you both target and exclude the same city, the exclusion wins and you get no traffic there.
One more “gotcha” that matters operationally: as of March 31, 2024, campaigns that target “all countries and territories” have a limit of 122 country-level exclusions. If you’re running global reach with a long exclusion list, you may need a different structure (for example, separate regional campaigns with positive targeting) rather than relying on ever-growing country exclusions.
Fix the “country targeting still brings in outsiders” scenario
There’s a common edge case when you target at the country level: you can still see activity that appears to come from outside the country. Some of that is legitimate (travelers, people “regularly in” the country, imperfect location signals, and users whose location can only be resolved broadly). If you must be strict, do two things: keep your location intent on “Presence,” then consider targeting the country’s regions/states/provinces instead of the country as a single target. This approach can reduce mismatches where the system can’t confidently place a user beyond the country level.
3) Build precise geo coverage: radius targeting, bulk locations, and location groups
Proximity (radius) targeting: powerful, but follow the rules
Radius targeting (also called proximity targeting) is ideal when your service area is “X miles from this address,” not “these specific cities.” In the interface, you set a center point (address) and a radius distance. A crucial constraint: radius targets must be at least 1 km due to privacy thresholds. Very tight radii can also cause intermittent serving if the audience size is too small to meet thresholds consistently.
From a scaling and governance standpoint, be aware of limits: campaigns can include up to 10,500 total location targets (targeted + excluded) and up to 500 proximity targets per campaign. If you’re managing multi-location brands, you’ll want to plan structure early so you don’t hit limits mid-growth.
Location assets + “optimize by distance” is the best local refinement loop
If you have physical locations and you’re already attaching them via location assets, you gain two major advantages: you can evaluate performance by distance, and (for U.S.-only location sets) you can build radius strategies around those locations. Once you see the conversion curve by distance, you can refine in a way that’s defensible: either tighten the radius, or use bid multipliers/adjustments to bid higher close to the store and lower farther away.
This is the closest thing to a “data-driven geo fence” inside the platform because it aligns bidding with proven conversion density rather than arbitrary city borders.
Bulk-add locations when you need precision at scale
When precision means “hundreds of zip codes” or “every city except these 30,” manual clicking is both slow and error-prone. Bulk location entry lets you paste up to 1,000 locations at a time (one per line), and you can repeat the process to go beyond 1,000. Keep the entries consistent and explicit—include the state/region for cities and the state for zip codes—to avoid mismatches.
4) Common geo-targeting problems (and the fastest fixes)
Why performance campaigns can show “outside your targets”
Some campaign types are designed to expand and interpret intent more broadly. Even when you’re confident your targeting is correct, you may still see some traffic outside the exact boundaries you selected. That can be normal behavior, especially if you’re using interest-inclusive settings. The practical response isn’t panic—it’s control: tighten to “Presence” when appropriate, then add exclusions based on what the location reports show is wasting budget.
Quick diagnostic checklist (use this before you restructure anything)
- Check location intent: Confirm whether your campaign is set to reach people “in or regularly in” your targets (Presence) versus also including “interest in” those targets.
- Review matched locations: Identify the exact cities/zip codes/districts generating spend with weak conversion rate, then exclude those areas.
- Validate exclusion logic: Make sure you didn’t exclude a parent region that unintentionally blocks your intended sub-locations.
- Use distance data (if available): If conversions drop after a certain radius, tighten targeting or reduce bids beyond that threshold.
- Expect imperfect signals: Location is determined by multiple signals (settings, device behavior, network signals), so 100% accuracy is not guaranteed—optimize to outcomes, not assumptions.
Advanced refinement tip: locations-of-interest at the ad group level (when available)
If you’re using AI-assisted Search features that support ad group–level “locations of interest,” you can add a second layer of control: the user must meet the campaign’s geo rules and also demonstrate interest in the ad group’s selected geography. This is especially useful for queries like “hotels in Madrid” from users physically located elsewhere, where you want to separate “interest in Spain” campaigns from your general campaigns without letting the system guess too broadly.
The key is to use this intentionally: treat it as a precision tool for destination-based intent, not as a replacement for solid campaign-level geo strategy.
Let AI handle
the Google Ads grunt work
| Step / Area | What to Check or Do | Why It Matters | Key Google Ads Features & Docs |
|---|---|---|---|
| 1. Diagnose where ads are actually showing | Compare targeted locations vs matched locations in your location reports, then drill down to the most granular level available (postal code, city, airport, university, district). | Separates a true geo-targeting problem from normal behavior based on intent and location signals. Reveals where “leakage” comes from and which areas are actually driving spend. | Use location reports and the matched locations view to see where your ads appeared and analyze performance by geography. |
| 1.1 Local businesses: use distance reporting | If you use location assets, pull a distance report to see performance by distance from the nearest store or office. Identify where conversions drop off (for example, beyond 8 miles). | Ties performance to real-world proximity instead of arbitrary boundaries, giving you a defensible radius for your core market and for bid adjustments. | Generate distance reports for campaigns using location assets to understand conversion behavior by distance. |
| 2. Choose the right location intent |
Decide between:
|
Prevents leads from users who can’t realistically become customers (e.g., out-of-area users just researching). You’ll often see fewer impressions but better in-market relevance. | Configure advanced options using advanced location options, where Presence or interest is the default positive targeting and Presence is the default for exclusions. |
| 2.1 Use exclusions like a scalpel |
Add exclusions to carve out low-value regions from your coverage. Remember:
|
Lets you keep broad reach while eliminating pockets of waste. Understanding the hierarchy prevents accidental blocking of valuable sub-locations. | Follow guidance on excluding geographic locations, including bulk exclusions and the country exclusion limit for “All countries and territories” campaigns. |
| 2.2 Fix “country targeting still brings in outsiders” |
When country-level targeting still shows some activity from outside that country:
|
Reduces mismatches caused by imperfect signals or users only resolvable at a broader level, tightening alignment between your customer base and ad delivery. | Use the breakdown of location target types by country to target regions, states, and smaller units instead of a single broad country target. |
| 3. Proximity (radius) targeting |
For “X miles from this address” service areas, use radius targeting:
|
Gives granular control around actual service areas while staying within technical limits and privacy constraints, especially important for multi-location brands. | Set proximity settings within location targeting, combining radius targets with standard locations as needed. |
| 3.1 Location assets + “optimize by distance” loop |
Attach your physical locations as assets, then:
|
Functions like a data-driven geo-fence, aligning bids and coverage with actual conversion density rather than guesswork or arbitrary borders. | Implement with location assets and analyze performance using distance reports. |
| 3.2 Bulk-add many precise locations |
When you need “hundreds of ZIP codes” or “every city except these 30,” use bulk location entry instead of manual clicks:
|
Speeds up complex setups and reduces human error in campaigns with detailed coverage requirements. | Use the bulk options in location targeting, and for spreadsheet workflows see the bulk upload section in format spreadsheets for bulk edits. |
| 3.3 Use location groups/location sets | Group locations into reusable sets (by region, brand, or performance) and apply them at campaign or ad group level. Useful for managing many locations with consistent rules. | Simplifies management for multi-location advertisers and enables consistent filtering (for example, only stores in a particular region for a campaign). | Create and apply sets using location groups and filtering in your account’s location manager and assets. |
| 4. Why some campaigns show outside your targets |
Performance-focused and AI-assisted campaign types can interpret intent more broadly, so some traffic outside strict boundaries is expected—especially when including interest-based reach.
Practical control steps:
|
Helps you recognize what’s normal versus a misconfiguration, and guides you to respond with tighter settings and exclusions instead of overreacting or restructuring too early. | Review how intent options behave in advanced location options, and use geo performance reports to identify low-value areas. |
| 4.1 Quick geo diagnostic checklist |
Before restructuring:
|
Ensures you fix real problems with minimal disruption, relying on data from reports rather than assumptions about where ads “must” be showing. | Combine location performance reports, matched locations and distance reports, and location exclusions to complete this checklist efficiently. |
| 4.2 Advanced: locations-of-interest at ad group level |
For AI-assisted Search setups that support ad group–level locations of interest:
|
Adds a second filter for destination-based queries, helping separate “destination interest” campaigns from general campaigns without losing control to overly broad automation. | Use advanced intent settings in advanced location options together with ad group–level geo interest controls where available in AI-powered Search campaigns. |
If you’re doing all of this geo work manually—checking matched vs targeted locations, validating “Presence” vs “Presence or interest,” tightening radius coverage, and carving out waste with exclusions—Blobr can help you stay on top of it without living in reports. It connects to your Google Ads account, monitors performance changes continuously, and translates best-practice checks into clear, prioritized actions you can review and apply when it makes sense for your goals, while you keep full control over which campaigns it analyzes and how often its agents run.
1) Start by diagnosing where your ads are actually showing (and why)
Separate “where you targeted” from “where you matched”
Before you touch settings, confirm whether you’re dealing with a true geo-targeting problem or a reporting misunderstanding. In location reporting, you’ll typically see a view for the locations you intentionally selected (your targeted locations) and a view for the locations that matched your ads (matched locations). The matched view can include both a person’s physical location and locations they’ve shown interest in, depending on your campaign’s location intent settings.
When advertisers tell me, “My ads are showing outside my target area,” the fastest reality check is comparing targeted locations vs matched locations, then drilling into the most specific level you can (postal code, city, airport, university, district—availability depends on the country and privacy thresholds). This quickly reveals whether the “leakage” is coming from interest-based matching, ambiguous searches (like “near me”), or genuinely irrelevant traffic.
Use distance reporting when you’re a local business
If you’re using location assets (your store or office locations attached to ads), you can evaluate performance by distance from the nearest location. This is one of the most practical ways to refine geo strategy because it ties performance to real proximity, not just city boundaries. If conversions fall off sharply beyond (say) 8 miles, you’ve found a clean optimization lever: tighten targeting, or reduce bids as distance increases.
2) Tighten geo-targeting without accidentally strangling volume
Choose the right location intent: “Presence or interest” vs “Presence”
Most campaigns default to a setting that can reach people who are in your targeted location, regularly in it, or have shown interest in it. This can be excellent for businesses where interest matters (travel, education, real estate, national brands), but it can be painful for businesses that only serve customers physically in-market (local services, in-person appointments, limited delivery zones, regulated/sensitive categories).
If your priority is “calls and leads from people who can actually be here,” switch your campaign’s location targeting intent to the option that only reaches people in or regularly in your targeted locations (“Presence”). Expect impressions to drop—sometimes noticeably—because you’re removing interest-based reach. That’s not a bug; it’s the tradeoff for precision.
Also note a key platform change: since March 2023, location intent options were standardized across the interface and tooling, with “Presence or interest” becoming the default positive targeting behavior and “Presence” becoming the default behavior for location exclusions. In plain terms, the platform is built to include interest by default unless you explicitly narrow it.
Use exclusions like a scalpel (and understand the hierarchy)
Excluding locations is often the cleanest way to refine geographic reach—especially when you want broad coverage but need to remove pockets of waste. Exclusions can be added one-by-one or in bulk, and they’re evaluated in a hierarchy where exclusions can override inclusions when they’re nested. For example, if you exclude a state but target a city inside that state, the city will be excluded because it sits within the excluded boundary. If you both target and exclude the same city, the exclusion wins and you get no traffic there.
One more “gotcha” that matters operationally: as of March 31, 2024, campaigns that target “all countries and territories” have a limit of 122 country-level exclusions. If you’re running global reach with a long exclusion list, you may need a different structure (for example, separate regional campaigns with positive targeting) rather than relying on ever-growing country exclusions.
Fix the “country targeting still brings in outsiders” scenario
There’s a common edge case when you target at the country level: you can still see activity that appears to come from outside the country. Some of that is legitimate (travelers, people “regularly in” the country, imperfect location signals, and users whose location can only be resolved broadly). If you must be strict, do two things: keep your location intent on “Presence,” then consider targeting the country’s regions/states/provinces instead of the country as a single target. This approach can reduce mismatches where the system can’t confidently place a user beyond the country level.
3) Build precise geo coverage: radius targeting, bulk locations, and location groups
Proximity (radius) targeting: powerful, but follow the rules
Radius targeting (also called proximity targeting) is ideal when your service area is “X miles from this address,” not “these specific cities.” In the interface, you set a center point (address) and a radius distance. A crucial constraint: radius targets must be at least 1 km due to privacy thresholds. Very tight radii can also cause intermittent serving if the audience size is too small to meet thresholds consistently.
From a scaling and governance standpoint, be aware of limits: campaigns can include up to 10,500 total location targets (targeted + excluded) and up to 500 proximity targets per campaign. If you’re managing multi-location brands, you’ll want to plan structure early so you don’t hit limits mid-growth.
Location assets + “optimize by distance” is the best local refinement loop
If you have physical locations and you’re already attaching them via location assets, you gain two major advantages: you can evaluate performance by distance, and (for U.S.-only location sets) you can build radius strategies around those locations. Once you see the conversion curve by distance, you can refine in a way that’s defensible: either tighten the radius, or use bid multipliers/adjustments to bid higher close to the store and lower farther away.
This is the closest thing to a “data-driven geo fence” inside the platform because it aligns bidding with proven conversion density rather than arbitrary city borders.
Bulk-add locations when you need precision at scale
When precision means “hundreds of zip codes” or “every city except these 30,” manual clicking is both slow and error-prone. Bulk location entry lets you paste up to 1,000 locations at a time (one per line), and you can repeat the process to go beyond 1,000. Keep the entries consistent and explicit—include the state/region for cities and the state for zip codes—to avoid mismatches.
4) Common geo-targeting problems (and the fastest fixes)
Why performance campaigns can show “outside your targets”
Some campaign types are designed to expand and interpret intent more broadly. Even when you’re confident your targeting is correct, you may still see some traffic outside the exact boundaries you selected. That can be normal behavior, especially if you’re using interest-inclusive settings. The practical response isn’t panic—it’s control: tighten to “Presence” when appropriate, then add exclusions based on what the location reports show is wasting budget.
Quick diagnostic checklist (use this before you restructure anything)
- Check location intent: Confirm whether your campaign is set to reach people “in or regularly in” your targets (Presence) versus also including “interest in” those targets.
- Review matched locations: Identify the exact cities/zip codes/districts generating spend with weak conversion rate, then exclude those areas.
- Validate exclusion logic: Make sure you didn’t exclude a parent region that unintentionally blocks your intended sub-locations.
- Use distance data (if available): If conversions drop after a certain radius, tighten targeting or reduce bids beyond that threshold.
- Expect imperfect signals: Location is determined by multiple signals (settings, device behavior, network signals), so 100% accuracy is not guaranteed—optimize to outcomes, not assumptions.
Advanced refinement tip: locations-of-interest at the ad group level (when available)
If you’re using AI-assisted Search features that support ad group–level “locations of interest,” you can add a second layer of control: the user must meet the campaign’s geo rules and also demonstrate interest in the ad group’s selected geography. This is especially useful for queries like “hotels in Madrid” from users physically located elsewhere, where you want to separate “interest in Spain” campaigns from your general campaigns without letting the system guess too broadly.
The key is to use this intentionally: treat it as a precision tool for destination-based intent, not as a replacement for solid campaign-level geo strategy.
