Geo targeting in ads is not a checkbox you tick and forget. In real projects, the difference between burning budget and multiplying conversions usually lies in details that don’t appear in the Google Ads interface or in basic tutorials. Here are specific cases, mistakes I’ve seen repeated, and limitations you should accept before segmenting by location.
A case of poorly calibrated radius in a dental clinic chain
I worked with a clinic with three locations in the same metropolitan area. The initial setup was simple: one campaign per location with a 15 km radius around each address. The problem appeared when we reviewed the geographic locations report: more than 40% of the downtown location’s spend was going to users who lived less than 2 km from the other two locations. The ads were competing with each other and the cost per click was rising because three campaigns were bidding for the same audience.
The solution was not to reduce the radius, but to use location groups combined with cross-exclusion. In Google Ads you can create a location group with a radius and exclude it in the other campaigns. It’s a feature that has existed for years, but many advertisers still ignore it because the interface hides it under “Locations” → “Exclude.”
The result after the adjustment: spend was redistributed to areas where there was no overlap, and cost per lead dropped notably at the downtown location. I can’t give an exact figure because the project changed budget mid-quarter, but the proportion of clicks from duplicate locations fell drastically.
The mistake of relying only on “physical presence or interest” location
Google Ads offers two options: physical presence (people in the area) and interest (people showing interest in the area). The default option is usually “presence or interest,” and that’s where the problem begins for local businesses.
A restaurant with home delivery limited to its neighborhood doesn’t want to advertise to someone searching for “pizza in [city]” from another province because they’re planning a visit. That person consumes budget and doesn’t convert. On the other hand, an online furniture store may indeed want to capture someone interested in their city even if they’re traveling.
The lesson: for services with physical presence (plumbers, dentists, gyms), select physical presence only. For brands with national shipping or events, interest makes sense. There’s no universal answer, and anyone who tells you otherwise is oversimplifying.
Geo targeting in Meta Ads: when the radius isn’t what it seems
On Meta (Facebook and Instagram), the minimum radius is 1 mile (approximately 1.6 km) in many countries, but postal code targeting in Spain, for example, is not natively available on all accounts. I’ve seen advertisers try to target specific districts of Madrid or Barcelona and discover that Meta only allows them to select the entire city or a radius centered on a point.
An alternative that works in certain cases is using custom location targeting with hand-drawn polygons, but the interface only offers it in Ads Manager with the map tool, and it’s not always available depending on the account type. When it isn’t, the option is to create custom audiences by postal code from a customer list, although that excludes anyone who has never purchased.
The case of the franchise with territorial licenses
A cleaning services franchise had a legal problem before an advertising one: each franchisee had exclusive rights over their area. The central campaign couldn’t advertise in areas assigned to a franchisee without their permission, but the franchisee didn’t have the budget to manage their own account either.
The solution was a structure of campaigns by area with location exclusions at the account level, managed from the parent account (MCC). Each franchisee contributed a minimum budget and the parent controlled the targeting. The technical challenge: account-level location exclusions don’t always propagate correctly to old campaigns, and you have to verify them one by one. It’s manual work that nobody documents well, and in large accounts it becomes an hours-long audit.
Here there’s a clear limitation: if the franchisee changes areas or the contract is renegotiated, the exclusions have to be redone. There’s obviously no automatic synchronization with legal contracts, but it’s worth keeping an updated map outside the platform.
Geo targeting and seasonality: the tourism mistake
In tourism businesses, the user’s location and their origin location rarely coincide. A hotel on the coast may want to advertise to residents in Madrid or Bilbao during the booking season, not to someone who is already at the beach looking for a restaurant.
The common mistake is to segment by the hotel’s location and wonder why the CTR is high but bookings don’t come in: the clicks come from people who are already in the area, often staying somewhere else. The solution involves separate campaigns: one with physical presence to capture those who are already nearby (restaurants, activities), and another with interest or origin location targeting to capture advance bookings.
At this point it’s worth being honest: Google’s “interest” targeting doesn’t distinguish between someone looking for a hotel for three months from now and someone looking for reviews of a hotel where they’re already staying. Geo targeting helps, but it doesn’t replace good intent-based keyword segmentation.
What doesn’t work well with geo targeting
- Businesses with irregular service areas: if your delivery area isn’t a circle, radii will always be too much or too little. Custom polygons exist on some platforms, but not all.
- 100% online services: segmenting by location usually inflates CPC without improving conversion, unless you sell something with territorial legal or tax implications.
- Products with geographic seasonality: location targeting doesn’t capture well people who travel for vacations, and platforms don’t offer a filter for “usual residence” versus “temporary location.”
- Areas with VPNs or imprecise mobile data: IP-based location isn’t exact. According to official platform documentation, accuracy varies and isn’t guaranteed at 100%. In rural areas or with roaming, the data can be misleading.
Metrics that are actually worth reviewing
Beyond CTR, there are reports that reveal whether geo targeting is working:
- Geographic locations report in Google Ads: check what percentage of spend is going to unwanted locations. It’s common to find leaks of 10-20% in poorly configured accounts.
- Distance to location in the segments report: it tells you whether clicks come from the target area or from farther away.
- Conversions by location instead of just clicks: a high CTR in an area that doesn’t convert is a warning sign.
- In Meta, the breakdown by region and city within the results report, which sometimes reveals that the radius is capturing traffic from unprofitable bordering cities.
A warning: these reports have privacy thresholds. In areas with few users, data is aggregated or hidden, which makes analysis difficult in rural or low-density areas. It’s a real limitation worth knowing before obsessing over geographic detail.
How to approach geo targeting without dying in the attempt
My recommendation after several projects: start with a simple structure and add complexity only when the data justifies it. It’s tempting to create dozens of campaigns by postal code, but fragmentation multiplies optimization work and sometimes dilutes the algorithm’s learning.
A reasonable starting point:
- Define whether your business is physical presence, remote service, or mixed.
- Configure the appropriate location option (physical presence vs. interest) according to the case.
- Review the geographic locations report two weeks after launch.
- Exclude locations with spend and zero conversions, but carefully: sometimes an area needs more time or a different message.
- Document the exclusions in a spreadsheet. The interface doesn’t warn you if an exclusion conflicts with an inclusion.
And a final warning: geo targeting doesn’t fix a bad ad or an uncompetitive offer. I’ve seen accounts with impeccable geographic targeting and a sky-high cost per conversion because the landing page took eight seconds to load. Location is one more layer of the system, not the silver bullet.