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Geo-Targeting Accuracy Benchmark

Measuring geo-targeting precision at country, state, and city levels across proxy pools.

Scorecard

Geo-Targeting Score
96
Composite score measuring geographic targeting precision and consistency.

Methodology

  • 20 countries, 50 US states, 30 cities tested
  • 500 requests per location target
  • Validated against 3 independent geolocation databases
  • Consensus required from at least 2 databases
  • 14-day test window with daily re-tests for consistency

Metrics

Country accuracy: Percentage of IPs that resolve to the requested country.
State accuracy: Percentage of US-targeted IPs that resolve to the correct state.
City accuracy: Percentage of city-targeted IPs that resolve to the correct city.
Consistency variance: Maximum accuracy deviation across repeated daily tests.
Last updated 2026-03-0614-day window

Geo-Targeting Accuracy Benchmark

Geo-targeting is critical for ad verification, localized pricing research, content access testing, and SEO monitoring. This benchmark evaluates how accurately proxy providers deliver IPs from the requested geographic location at country, state, and city granularity levels.

Test Design

We requested proxies from 20 countries, 50 US states, and 30 major cities worldwide. For each location target, we validated the actual IP location using three independent geolocation databases (MaxMind, IP2Location, and ipinfo.io) and required at least two databases to agree for a location to be confirmed.

Country-Level Accuracy

At the country level, Hex Proxies achieved approximately 100% accuracy across all 20 tested countries, because country targeting is port-based and requests exit through the selected country. Industry averages at the country level ranged from 94% to 97%.

State-Level Accuracy

State-level targeting in the US showed approximately 90% accuracy for Hex Proxies. Misses typically occurred at state borders where ISP coverage areas overlap. For example, IPs targeted to Kansas occasionally resolved to Missouri, and New Hampshire targets sometimes appeared as Massachusetts. The industry average for state-level accuracy was 85-90%.

Geo LevelHex ProxiesProvider BProvider CIndustry Average
Country~100%97.1%95.8%95.5%
State (US)~90%89.2%85.6%87.3%
City~90%78.5%72.1%75.2%
City (Top 20)90-100%84.2%79.8%82.0%

City-Level Accuracy

City-level targeting is the most challenging tier. Hex Proxies delivered approximately 90% city-level accuracy overall, rising to 90-100% for the top most-requested US cities. Industry averages hovered around 75% for city-level targeting, with some providers dropping below 70% for smaller cities.

Coverage Depth

Beyond accuracy, coverage depth matters. Hex Proxies offers targeting in 195 countries, all 50 US states, and 500+ cities. Available IPs per location ranged from 50 (small cities) to 50,000+ (major metros), ensuring sufficient pool depth for rotation without repeating IPs.

Consistency Over Time

We re-tested the same locations at 24-hour intervals over 14 days. Hex Proxies geo accuracy varied by less than 1.5 percentage points across all test runs, indicating stable pool management. Some competing providers showed 5-8% variance, suggesting IP pool composition changes that affect targeting reliability.

Impact on Use Cases

For ad verification, geo accuracy directly affects whether you see the correct regional ad. A 5% miss rate means 1 in 20 verification checks could return incorrect data. Hex Proxies ~100% country accuracy and ~90% city accuracy minimize false readings in geo-dependent workflows.

Steps

1
Define target locations
Select countries, states, and cities relevant to your use case.
2
Multi-database validation
Use at least two geolocation databases for consensus-based verification.
3
Measure across granularities
Test country, state, and city accuracy independently.
4
Track consistency
Re-test daily to detect pool composition changes.

Tips

  • City-level accuracy varies by region; test your specific target cities before committing.
  • Use multiple geolocation databases to avoid single-source bias.
  • Larger cities generally have better accuracy due to deeper IP pools.

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