How do I set up geo-targeting for Meta Ads lead campaigns?

How Meta Ads Geo-Targeting Works

Meta's geo-targeting system uses multiple data signals to determine a user's location: GPS data from the mobile device, IP address, self-reported location data in the user's profile, and check-in behaviour on Facebook. This multi-signal approach means Meta's location targeting is generally quite accurate for users who access Facebook and Instagram via their mobile devices — which is the majority of Meta's daily active users.

Geo-targeting is configured at the ad set level in Meta Ads Manager, meaning you can have different location targeting for different ad sets within the same campaign. This structure is particularly useful for multi-location businesses or for advertisers who want to test different geographic markets with the same creative but analyse results separately by location.

Meta allows targeting by country, state/region, city, designated market area (DMA, US-specific), postcode/zip code, and radius around a specific address or pin. You can combine multiple location types within a single ad set (e.g., targeting three specific postcodes plus a radius around a store address), and you can exclude specific locations within a broader targeted area.

Location Type Settings: Residents vs. Visitors

One of the most impactful — and most overlooked — geo-targeting settings in Meta Ads Manager is the Location Type dropdown. When you add a location, Meta offers several options for which users within that location to target: "People living in this location," "People recently in this location," "People travelling in this location," and the default option "People living in or recently in this location."

For service businesses where the value of a lead depends on the person actually living in the service area (home renovation, lawn care, local professional services), using "People living in this location" is almost always superior. This restricts delivery to users whose primary residence is within the targeted area, excluding tourists, business travellers, and commuters who happen to be physically in the location temporarily but have no intention of becoming local service customers.

• People living in this location: Best for local service businesses; excludes tourists and transient visitors
• People recently in this location: Includes recent visitors; useful for tourist attractions, hospitality, or event-based businesses
• People travelling in this location: Targets only non-residents; use for travel, hotel, or tourist-facing campaigns
• Living in or recently in: The default; wider reach but includes non-residents who are poor lead prospects for most local businesses

Radius Targeting for Local Service Businesses

Radius targeting allows you to draw a circular geo-fence around a specific address, postcode, or map pin and target all users within that radius. In Meta Ads Manager, the minimum radius is 1 mile (or 1 km) and there is no official maximum limit, though very large radii effectively become regional or national targeting.

Choosing the right radius for your business depends on your service area and the realistic travel or delivery distance for your offering. A residential cleaning service might use a 10-mile radius, understanding that their team travels within that range. A specialist dental practice might use a 15-mile radius in a suburban area but a much tighter 3-mile radius in a densely populated urban area where prospects are unlikely to travel far for dental services.

For businesses with multiple service locations, create separate ad sets with separate radius targets rather than combining all locations in one ad set. Separate ad sets allow you to analyse CPL and lead quality by location independently, optimise bidding and budget by location performance, and tailor ad creative (images, copy) to be location-specific ("Serving [City Name] since 2010") for greater relevance and conversion rate.

Multi-Location Geo-Targeting Strategy

Businesses with multiple physical locations face a specific geo-targeting challenge: how to efficiently allocate budget across locations while maintaining attribution clarity and enabling location-specific optimisation. The recommended approach is a dedicated ad set per location — or per geographic cluster of locations if budgets are limited.

Each location-specific ad set should use radius targeting around that location's address (or postcode targeting for the location's service area), have location-specific creative that mentions the city or area name to increase ad relevance, and send leads to a location-specific landing page or lead form that captures which location the lead is inquiring about — information that is critical for routing the lead to the correct team in your CRM.

Use exclusion zones between locations if your service areas overlap. If two of your locations are 12 miles apart and each has a 10-mile service radius, the 8-mile overlap zone will receive ads from both ad sets. Add exclusion zones in each ad set to prevent the same postcode from being targeted by two different location campaigns, which would otherwise cause internal competition between your own ads and inflate CPMs for those overlapping postcodes.

Excluding Low-Quality Locations and Budget Drains

Just as important as targeting the right locations is excluding locations that are likely to drain budget without generating quality leads. For most local service businesses, a few specific exclusion strategies significantly improve campaign efficiency.

First, exclude areas that fall within your radius but are unlikely to contain your target customer profile. If your service targets homeowners in residential suburbs, adding postcodes covering commercial districts, industrial zones, or university campuses within your radius as exclusions can reduce wasted impressions on people who are physically in your radius but are not residential homeowners.

Second, if you have historical data showing that leads from certain postcodes or areas within your target radius consistently fail to convert to paying customers — perhaps due to price sensitivity, distance from service points, or demographic mismatch — add those areas as excluded locations. This progressive exclusion approach, refined over multiple campaign cycles with CRM data, compounds into significant CPL improvements over time.

Review your lead-to-sale data in your CRM by postcode quarterly and feed the insights back into your geo-targeting exclusions. This data-driven geographic refinement is one of the most underdeveloped optimisation tactics in Meta lead campaign management.