# City-Level vs Country-Level Mobile IP Targeting Compared A team running ad verification campaigns in Dallas kept noticing something weird. Their **city-targeted proxy pool** was showing sessions appearing as Houston instead. The problem wasn't bad routing from their proxy provider. It was **carrier IP allocation behavior** that most geolocation databases just can't track in real time. **IP targeting** seems simple enough until budget starts disappearing on **geo-restricted content** tests or compliance checks that fail because a mobile carrier routed that "Los Angeles" connection through a regional gateway 200 miles away. **Country-level targeting** sidesteps most of these issues, but **city-level geotargeting** offers precision that performance teams actually need for [ad verification](/blog/geo-targeted-proxies-ad-verification) and market-specific automation. Which approach delivers reliable results when **mobile carrier routing** doesn't follow neat geographic boundaries? ## Why City-Level IP Targeting Fails More Often Than Documentation Suggests Mobile carriers don't assign [IP addresses](https://www.cloudflare.com/learning/dns/glossary/what-is-my-ip-address/) based on physical location. They allocate from **regional pools** that serve entire metro clusters or states. A **T-Mobile connection** in Phoenix might pull an IP that geolocation services tag as Tucson because the carrier's IP block was originally registered there. When testing sessions in Miami using different mobile proxy providers, sessions commonly geolocate to nearby cities like Fort Lauderdale or Orlando. Some return only state-level data with no city information at all. **Country-level accuracy** typically hits **98-100%**, while **city accuracy** sits in the **70-80% range**. Carrier routing adds another layer of complexity. When mobile networks experience congestion, they route traffic through **alternate gateways** that might sit in different cities. That Seattle connection could temporarily exit through a Spokane gateway, and suddenly the ad verification session thinks it's 280 miles east. **IP geolocation accuracy** depends on databases that update weekly at best (monthly for most providers). Carriers reassign IP blocks constantly. [MaxMind's documentation](https://support.maxmind.com/hc/en-us/articles/4407630607131-Geolocation-Accuracy) notes that mobile IPs often return only state-level data without city information because cellular networks span large geographic areas. Accuracy drops further in countries with fewer carriers or less granular data. Some carriers use [CGNAT (Carrier-Grade Network Address Translation)](https://blog.cloudflare.com/detecting-cgn-to-reduce-collateral-damage/) that funnels thousands of users through shared IP pools. Geolocation services see the **exit node**, not the actual user position. ## When Country-Level Targeting Actually Makes More Sense **Geo-restricted content** checks work fine with **country-level precision**. Testing whether a streaming service blocks UK users doesn't require a London IP specifically. Any British mobile IP confirms the restriction logic. **Compliance verification** for GDPR or data residency rules cares about national borders, not cities. Validating that European users see cookie consent banners? A German IP from any city satisfies the test case. Performance marketing at scale favors **country targeting** because session consistency matters more than pinpoint accuracy. Running hundreds of automated checks daily means **reliability** is critical. City-level drift creates false positives that waste analyst time. Automation teams targeting **local search results** or verifying city-specific ad placements can't compromise, though. A campaign checking "plumber near me" results in Brooklyn needs **Brooklyn IPs**, not just New York state. ## How to Improve City-Level IP Targeting Reliability Start by checking which **geolocation database** the verification tool uses. MaxMind, IP2Location, and Digital Element all show different city results for the same mobile IP. Testing the same carrier IP across multiple databases commonly returns different cities or varying levels of geographic specificity. Use **sticky sessions** when city accuracy matters. Rotating IPs every request multiplies the chance of hitting a gateway in a different metro. Longer sticky sessions from a quality [mobile proxy](/proxies) give consistent geolocation for that window. Before running large-scale ad checks, manually verify sessions from the proxy pool against the geolocation API that the target platform actually uses. Google's geolocation differs from Cloudflare's, which differs from MaxMind. Real mobile proxies with actual SIM card infrastructure outperform **datacenter proxies labeled as "mobile"** for city targeting. [Datacenter providers](https://datadome.co/learning-center/what-are-data-center-proxies/) sometimes market IPs as mobile without genuine carrier connections, and geolocation databases flag these inconsistently. Carrier selection impacts results. In the US, some carriers' IP allocation tends to be more geographically clustered than others' regional pools. **AT&T mobile IPs** typically show higher city match rates compared to carriers using broader regional pool allocation. For critical city-level work, validate geolocation in real time. Hit an IP geolocation API before running the main task. If the result doesn't match the target city, rotate to another IP. This adds 200-400ms latency but prevents wasted sessions. ## Country-Level Setup for Consistent Performance **Country targeting** through mobile proxies requires less babysitting. Configure the proxy connection to pull from a national pool and let carrier routing handle the rest. As long as the IP geolocates to the right country, minor city variations don't matter. API-based proxy services make this straightforward. Instead of managing individual IP lists, request a connection with **country parameters** and receive a working endpoint. Platforms like VoidMob provide **mobile proxies** with country-level pools that pull from real carrier infrastructure. Actual 4G/5G connections, not datacenter IPs labeled as mobile. This matters because **geo-restricted content** increasingly checks for genuine mobile carrier patterns beyond just IP geolocation. Country pools also cost less. City-specific IP inventory is smaller and commands premium pricing. If the use case doesn't absolutely require city precision, there's a **30-50% savings** on proxy costs with national targeting. ## Common Pitfalls and How to Avoid Them Assuming "mobile IP" means accurate geolocation is the first mistake. Mobile IPs drift more than residential or datacenter IPs because **carrier routing** changes constantly. Caching geolocation results creates stale data. That IP verified as Chicago yesterday might route through Milwaukee today. Always verify fresh if city accuracy is critical. Ignoring IPv6 causes headaches. Many mobile carriers now default to IPv6, and geolocation databases have less comprehensive IPv6 data. If automation only handles IPv4, sessions get missed or forced into fallbacks that hurt accuracy. Over-rotating IPs tanks city targeting success. Rotating every few requests for "better anonymity" can drop city match rates significantly because each rotation hits different carrier gateways. For more on balancing rotation with reliability, see our guide on [mobile proxy vs datacenter proxy performance](/blog/mobile-proxy-vs-datacenter-proxy). ## FAQ ## Wrapping Up **City-level IP targeting** delivers precision when it works but introduces drift from **carrier routing** realities. **Country-level targeting** sacrifices granularity for reliability, which ends up being the right trade-off for most automation and verification workflows. Match targeting precision to actual requirements. **Geo-restricted content** and compliance checks rarely need city accuracy. **Local ad verification** and hyperlocal SEO can't function without it.

#Carrier Routing

City-Level vs Country-Level Mobile IP Targeting