I’ve spent enough time looking at SEO tools to know that the phrase “just scrape the search results” usually means the opposite of just.
At first, it sounds easy. Send a query, collect the results and move on. Then the number of searches grows, different locations become important and suddenly the IP address behind every request starts becoming a pretty big deal.
That’s why, if I were setting up a SERP scraper today, I wouldn’t start by looking at the cheapest API or the biggest advertised number of IPs. I’d start with the residential side of the setup.
Search results aren’t identical everywhere, after all. And if I’m trying to understand what people in a particular market actually see, I want the requests to look geographically relevant too.
The thing I noticed about SERP data
One of the first things that stood out to me is how much location can affect search results.
A person searching for “plumber near me” in London isn’t necessarily getting the same results as someone searching for it in Birmingham. The same goes for restaurants, estate agents, shops and pretty much anything else with a local angle.
That makes location incredibly important for SEO agencies and businesses tracking rankings.
It’s also where residential proxies start making sense.
When I looked at providers for this kind of work, I paid much more attention to residential IP coverage than I did to flashy feature lists. A residential IP is associated with an ISP connection rather than a typical datacenter server, which can make it a better fit for certain search workloads.
GoProxies stood out to me here because its residential network is built around geographic flexibility, including targeting by country, state and city.
That’s useful when the objective isn’t simply to get a search result, but to get a result that makes sense for a particular market.
Why I wouldn’t rely on one IP
Imagine checking a few hundred keywords from exactly the same address.
It doesn’t take much imagination to see why that could become problematic.
For a serious SERP scraper, I’d want some way of distributing requests across residential IPs and changing them when necessary. I don’t expect any proxy provider to make automated traffic invisible — that’s not realistic — but I do want the infrastructure to avoid putting every request through one obvious point.
This is one of the reasons GoProxies interests me for SERP work.
Its residential proxy offering is designed around rotating IPs and geographic targeting, which fits the requirements of large-scale search collection rather nicely.
It’s not particularly glamorous stuff. Nobody is putting “IP rotation” on a coffee mug. But when a scraping job is running at scale, these boring details are exactly the ones that suddenly become important.
Where the API comes in
I also wouldn’t want to build the entire system from scratch.
A SERP scraping api can take a lot of the repetitive work out of collecting search results. Instead of maintaining every part of the infrastructure independently, the API can handle the search request while the underlying proxy network deals with the connection.
That’s a much more attractive setup when hundreds or thousands of searches are involved.
GoProxies offers a SERP scraping API designed for this type of workflow, with search collection combined with its residential proxy infrastructure.
For me, that combination is more interesting than an API viewed in isolation. A fast API is useful, but the IP behind the request still matters.
What I like about the residential approach
The more I look at SERP scraping, the more I think residential IPs deserve to be treated as part of the core setup rather than an optional extra.
SEO data is often geographic. Local rankings, competitor visibility and regional search behaviour all depend on where the search originates.
If I’m collecting that information, I want the infrastructure to reflect that reality.
That’s where GoProxies has an advantage in my view. Its focus on residential IPs and location targeting lines up naturally with the way I would want to collect SERP data.
Could another provider be better for a particular project? Absolutely.
But if residential coverage is near the top of my list, I’d put GoProxies high on the shortlist.
My final take
If I were building a SERP scraping workflow in 2026, I’d stop thinking about speed as the only important metric.
I’d look at the whole picture: residential IP quality, location targeting, rotation, reliability and the API itself.
The goal isn’t just to collect search results quickly. It’s to collect useful search results that actually represent the market being researched.
That’s why I find the residential approach particularly compelling.
There are plenty of providers worth comparing, and Bright Data, Oxylabs and Smartproxy all have reasons to be considered. But for a project where residential IPs and geographic flexibility are central, GoProxies makes a strong case.
Have you ever compared SERP results from two different cities and wondered why they looked completely different? That’s exactly the kind of situation where the infrastructure behind the scraper starts to matter.
And once you notice that, it’s surprisingly hard to ignore.