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Proxy Success Rate Comparison

Side-by-side success rate comparisons across proxy types and target categories.

Scorecard

Success Score
95.1
Composite score reflecting overall request reliability and consistency.

Methodology

  • • 5,000 requests per proxy-type and destination-category combination
  • • 7-day test window with requests distributed evenly
  • • Rotating user agents with realistic browser fingerprints
  • • Success defined as HTTP 200 with valid content structure
  • • Failures categorized: timeout, CAPTCHA, hard block, empty response

Metrics

Overall success rate: Percentage of requests returning valid HTTP 200 responses with expected content.
Retry multiplier: Average number of attempts needed per successful request.
Failure distribution: Breakdown of failure types: timeouts, CAPTCHAs, hard blocks.
Peak hour delta: Percentage point drop in success rate during peak traffic hours.
Last updated 2026-03-09 • 30-day window

Proxy Success Rate Comparison

Success rate is the most direct measure of proxy effectiveness. A proxy that delivers fast responses but gets blocked 30% of the time costs more in retries and missed data than a slightly slower proxy with a 98% success rate. This benchmark compares success rates across proxy types and destination categories.

What Counts as Success

We define success as receiving a valid HTTP 200 response with the expected content structure. Responses that return 403, 429, CAPTCHA challenges, empty bodies, or connection timeouts are classified as failures. Redirects to block pages are also counted as failures.

Test Design

We tested four proxy types (residential, ISP, datacenter, premium residential) against five destination categories: ecommerce, search engines, social media, news/media, and classified sites. Each combination received 5,000 requests over a 7-day period with rotating user agents and realistic request patterns.

Results by Proxy Type

| Proxy Type | Ecommerce | Search | Social Media | News | Classifieds | Overall | |-----------|-----------|--------|-------------|------|-------------|---------| | Hex Residential | 96.8% | 94.2% | 97.1% | 98.5% | 95.3% | 96.4% | | Hex ISP | 98.2% | 96.5% | 98.8% | 99.1% | 97.0% | 97.9% | | Hex Premium Residential | 98.9% | 97.8% | 99.2% | 99.5% | 98.1% | 98.7% | | Industry Avg Residential | 88.5% | 82.3% | 89.7% | 92.1% | 85.6% | 87.6% | | Industry Avg ISP | 93.0% | 89.5% | 94.2% | 95.8% | 91.0% | 92.7% |

Failure Analysis

Among Hex Proxies failures, 62% were connection timeouts (typically due to destination-side rate limiting), 24% were CAPTCHA challenges, and 14% were hard blocks. This distribution is healthier than the industry pattern, where hard blocks typically account for 35-40% of failures.

Retry Economics

With Hex Proxies 96-99% success rates, the average request requires 1.02 attempts. At industry-average success rates of 87-93%, the average request requires 1.10-1.15 attempts. Over a million requests, that difference translates to 80,000-130,000 fewer retry requests, saving bandwidth, time, and proxy consumption.

Time-of-Day Variance

Success rates dropped by 1-3% during peak hours for Hex Proxies, compared to 5-12% drops observed with other providers. This stability indicates effective IP pool management and rotation strategies that maintain fresh, unblocked IPs even under heavy industry-wide usage.

Recommendations

For maximum success rates, Hex Premium Residential proxies deliver near-perfect reliability across all destination categories. For cost-effective general use, Hex Residential proxies outperform industry averages by 8-10 percentage points. ISP proxies offer the best balance of speed and success rate for use cases that require both.

Steps

1
Define destination categories
Group targets by industry vertical for meaningful comparisons.
2
Distribute requests evenly
Spread requests across the full test window to avoid burst bias.
3
Classify failures
Categorize every non-success response by failure type.
4
Calculate retry economics
Compute the cost of retries at your observed success rate.

Tips

  • • Always test against the same destination versions to avoid bias from site changes.
  • • Track success rates per destination category, not just overall averages.
  • • Factor retry costs into your total cost-per-request calculation.

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