Geolocation and proxy targeting: city-level vs ASN-level
Geolocation and proxy targeting: city-level vs ASN-level
when you rent a proxy, the provider usually asks where you want the exit IP to appear. you can often choose a country, a state, sometimes a city, and sometimes something called an ASN. most people pick a country and move on. that works fine until it doesn’t, which is usually when a site starts rejecting your requests for no obvious reason.
city-level and ASN-level targeting solve different problems. understanding the difference will save you money and debugging time. this explainer covers what both terms mean, how the underlying mechanics work, and which one you actually need for common use cases.
what it is
geolocation targeting means selecting proxy IPs based on where they appear to be located, according to a geolocation database. when a website sees your request, it queries something like MaxMind GeoIP2 to figure out your country, region, city, and sometimes postal code. city-level targeting means you are buying IPs that MaxMind (or a comparable database) maps to a specific city.
ASN targeting is different. ASN stands for Autonomous System Number. an AS is a collection of IP prefixes controlled by a single organization, usually an ISP, a university, a cloud provider, or a large company. the formal definition from RFC 1930 is “a connected group of one or more IP prefixes run by one or more network operators which has a single and clearly defined routing policy.” practically speaking, when you connect through an IP in ASN 7922, you look like you are on Comcast. when you connect through ASN 16509, you look like you are on Amazon AWS.
these are two different axes of targeting. a proxy can be in Chicago (city-level) and on ASN 7922 (Comcast, Illinois) at the same time. or it can be in Chicago but on a datacenter ASN. those two IPs will behave very differently on sites that care about network type.
how it works
city-level geolocation
geolocation databases build their city-level mappings by combining multiple signals: BGP routing tables, whois registration data, network latency measurements, and user-submitted corrections. MaxMind publishes accuracy statistics for GeoIP2 City, and the numbers are more honest than most vendors admit. at country level, accuracy is around 99%. at city level within the US, it drops to roughly 80% within a 50-mile radius. that figure is better in densely networked countries and worse in places with sparse infrastructure.
proxy providers that sell “city-level” targeting are mostly matching their IP inventory against one of these commercial databases, then letting you filter by city. the actual physical location of the IP may or may not match the database record. a residential IP is geolocated based on the ISP’s assignment, which can lag by months if the ISP shuffled address blocks.
ASN-level targeting
every IP block on the public internet is announced by an AS. you can look up any IP’s ASN using tools like whois or public databases maintained by CAIDA. regional internet registries like RIPE NCC and ARIN assign ASNs to organizations and maintain public records of which IP prefixes belong to which AS.
when a site wants to block datacenter proxies, it typically checks whether the connecting IP’s ASN is a known hosting provider. AWS, Google Cloud, DigitalOcean, OVH, and a few hundred others have well-known ASN ranges. residential and mobile ISPs have different ASNs. by targeting a specific ISP’s ASN, you ensure your requests arrive from an IP that looks like a home internet subscriber on that network, not a server in a data center.
some proxy providers let you filter by ASN directly. others let you filter by “ISP name,” which is functionally the same thing since each ISP operates one or more ASNs.
why it matters
1. localized content and pricing some e-commerce sites and streaming platforms serve different content, prices, or product catalogs depending on city or even neighborhood. if you are doing price comparison work across US cities, country-level targeting is not granular enough. you need an IP that the site maps to Dallas or Seattle specifically.
2. residential vs datacenter detection this is probably the more important axis for most operators. a site’s fraud detection stack does not primarily care whether you are in Chicago or Denver. it cares whether your IP is a residential Comcast subscriber or an AWS us-east-1 server. ASN targeting is how you control that signal. if you are running automation on sites with aggressive bot detection, getting your ASN right matters more than getting your city right.
3. platform-specific restrictions a handful of platforms geo-fence features at the city level. some local ad platforms and classifieds sites serve listings only to IPs in the same metro. for those cases, city-level targeting is load-bearing and ASN is secondary.
4. cost efficiency residential IPs are more expensive than datacenter IPs. if city-level targeting is all you need (because the site doesn’t check ASN) then there is no reason to pay for residential. understanding what each targeting dimension actually changes lets you match the proxy type to the task and avoid overpaying.
common misconceptions
“city-level targeting means the IP is physically in that city” it means the geolocation database says the IP is in that city. the physical server or device could be anywhere. for residential IPs, the device is usually in the right area, but geolocation database records lag ISP address reassignments. for datacenter proxies marketed as city-level, the exit node might be in a different city altogether. always verify with a test request to an IP geolocation API before assuming.
“ASN targeting is only for enterprise use cases” not really. any self-serve residential proxy dashboard with ISP filtering exposes ASN-level control. providers like Oxylabs and Brightdata have offered ISP/ASN filtering in their standard plans for years. you do not need a custom contract to use it.
“if the country matches, city targeting doesn’t affect detection” some platforms fingerprint the ISP name or ASN independent of geolocation. a request from a US IP on a German hosting ASN will fail detection checks even if the GeoIP city says New York. the country check and the network-type check are separate lookups in most fraud stacks. passing one does not mean you pass the other.
“residential proxies always have accurate city-level geolocation” residential IPs get their geolocation from the ISP’s WHOIS records and MaxMind’s periodic re-scoring. if an ISP reassigns an address block, the database might take 3-6 months to update. the proxy provider has no control over this. if you need a very specific city match and accuracy matters, test the IP against multiple databases (MaxMind, ip-api.com, ipinfo.io) before running your job.
where to go from here
if this was new territory, the next logical topics are:
- residential vs datacenter proxies: what actually differs covers the full comparison of proxy types and when each makes sense, including the ASN implications
- how to choose a proxy provider walks through what to look for in a provider’s filtering options, pool size, and city-level inventory claims
- IP rotation strategies explained gets into session vs rotating proxies, and how rotation interacts with city and ASN targeting when you need sticky sessions in a specific location
- if you are using proxies for multi-account or farming workflows, the guides at multiaccountops.com/blog/ go deeper on how fingerprinting layers sit on top of what proxy-level targeting can solve
the proxyscraping.org blog has more explainers on proxy mechanics if you want to keep building from here.
Written by Xavier Fok
disclosure: this article may contain affiliate links. if you buy through them we may earn a commission at no extra cost to you. verdicts are independent of payouts. last reviewed by Xavier Fok on 2026-05-19.