Residential Proxy | ScrapeRouter

A residential proxy routes your requests through IP addresses assigned by consumer internet providers, so the traffic looks like it is coming from a normal home user instead of a data center. In scraping, people use them because they get blocked less often on sites that score IP reputation aggressively, but they cost more and add another thing that can fail.

Examples

A simple example is rotating requests through a residential pool when a target starts blocking datacenter IPs after a few pages.

import requests

proxies = {
    "http": "http://user:pass@residential-proxy.example:8000",
    "https": "http://user:pass@residential-proxy.example:8000",
}

resp = requests.get(
    "https://httpbin.org/ip",
    proxies=proxies,
    timeout=30,
)

print(resp.status_code)
print(resp.text)

If you do not want to manage proxy vendors directly, you can push the problem into a scraping API that handles proxy selection and retries for you.

curl -X POST "https://www.scraperouter.com/api/v1/scrape/" \
  -H "Authorization: Api-Key $api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://example.com/products",
    "render": false
  }'

Practical tips

Use residential proxies when the target is actually filtering hard on IP reputation. If a site works fine from datacenter IPs, paying residential rates is just waste.
Expect tradeoffs: higher cost, slower response times, more variability between exits.
Rotate with some control. Randomly changing IP on every request can look worse than keeping a short-lived session.
Pair proxy choice with the rest of the request shape: headers, cookies, TLS fingerprint, rate limits. A residential IP does not fix obviously bot-like traffic.
Watch for provider quality issues: overloaded peers, geo mismatch, sticky sessions that are not really sticky, and surprise bandwidth bills.
Be careful with login and account flows: changing IP too often can trigger more checks, not fewer.
If you are doing this at scale, measure block rate, success rate, cost per successful page, and median latency. Those numbers matter more than provider marketing pages.

Use cases

Scraping retail, travel, ticketing, and classifieds sites that block datacenter ranges quickly.
Collecting search result pages or localized content where IP geography affects what you see.
Running session-based flows that need a more believable consumer IP footprint.
Reducing maintenance when your current setup keeps turning into a proxy rotation project instead of a data collection system.