I learned the hard way that $/GB is a terrible way to compare rotating residential proxies. The use case was to monitor public product prices across a few regional e-commerce sites. Pool A looked like the obvious winner at $1.60/GB. Pool B was almost twice the price. Pool A was producing far more CAPTCHAs, 403s, and empty responses. Every failure triggered another request, which meant more bandwidth and longer jobs. So I stopped comparing price per GB and calculated: effective cost = price per GB / success rate Example from my test model: $1.60 / 0.40 = $4.00 per useful GB $3.00 / 0.95 = $3.16 per useful GB Suddenly the “expensive” pool was cheaper. The biggest variable wasn’t bandwidth pricing. It was IP reputation. Now before scaling a rotating pool, I sample exit IPs and check ASN, geolocation, proxy classification, blacklist status, and fraud/reputation signals. Then I run a small workload and measure CAPTCHA rate, retries, and successful responses. Cheap proxies aren’t expensive because they’re cheap. They’re expensive when bad IP quality turns bandwidth into failed requests.   submitted by   /u/appcyberyozh [link]   [comments]