Query from the city you are ranking in
Proxies for SERP and rank monitoring
The same keyword returns different organic results, local packs and shopping units in Los Angeles and in Miami, and a data-center IP collects an average that belongs to no city at all. ZapIP issues each query from a residential line inside the market you track, so rankings, featured snippets and ad slots come back the way a local searcher sees them.
- City-level SERP data
- Rotation 1–360 min
- Unlimited concurrency
- 99.9% request success
How it works
Rankings are local, so collection has to be
Local packs, shopping units and featured snippets all shift with the location a query comes from, and results pulled through hosting ranges tend to collapse into one generic version. Querying from a residential line inside the target city means the SERP you store matches what a local user sees, so a ranking movement corresponds to something that actually happened in that market.
- 195 countries and regions; city targeting in 33 markets
- ASN targeting to query from a specific local carrier
- US state-level tracking to compare one keyword across regions
- Residential exits, not hosting ranges, so results stay localized
How it works
Holding up once the keyword list runs long
Rank tracking is not hard once; it is hard every morning, at the same hour, across a few hundred thousand queries. Rotating residential proxies switch per request, place no cap on concurrency, respond in under 0.6s on average and succeed 99.9% of the time — which is what makes today's snapshot comparable to yesterday's.
- Rotate per request or on a 1–360 minute schedule
- No concurrency cap, so the crawl window stays short
- under 0.6s average response keeps run times predictable
- Bandwidth plans meter Mbps, not GB, for daily full refreshes
How it works
More than ten blue links
The same residential exits serve ad-slot monitoring, share-of-voice work, marketplace site search and app-store charts. Wherever the question is what a local user sees, the collection method is identical — there is no reason to buy separate proxy capacity per data type.
- Paid search and shopping ad placement checks
- Competitor visibility and keyword overlap by market
- Marketplace site-search ranking and placement data
- App-store charts and localized keyword tracking
Coverage
One network behind all four products — changing the billing model does not change how you connect or how you target.
All 33 markets- 195 countries & regions
- Available
- All 50 US states
- Available
- City-level targeting
- Precise
- ISP & ASN targeting
- Supported
4 billing models
How this is billed
All four billing models share one network. Short bursts go per GB, pipelines that run continuously go per Mbps, and anything tied to an account identity goes per IP-day or per IP-month.
FAQ
Questions about this solution
Can I scrape SERPs with data-center proxies?
Small and occasional, yes. At scale, no. Hosting ranges are the easiest traffic class for a search engine to identify, and once identified you get either constant challenges or a genericised result set — both of which quietly corrupt the rank history you are building. Residential exits draw far less of that, and they can be pinned to a city, which a data-center IP cannot.
Rotating or static proxies for rank tracking?
Rotating. A rank check is read-only — there is no identity to preserve — and spreading queries across many exits keeps per-IP request density low. Per-GB billing suits it too, since a SERP response is small and a few hundred thousand of them cost less traffic than people expect. Static IPs only enter the picture when you are logging into a dashboard rather than reading public results.
How do I verify a result really came from the city I targeted?
Pin the city or ASN when you pull the IP, then check twice on your side: resolve the exit's geolocation before the request, and afterwards look for localization tells in the page itself — local-pack businesses, currency symbols, delivery hints. ZapIP targets by where the address is actually registered rather than by spoofing a parameter, so those two checks normally agree.
At a few hundred thousand queries a day, is per-GB or per-Mbps cheaper?
Work out the average response size first. A SERP page is usually tens to a few hundred KB, so 200k queries lands in the tens of GB per day — comfortable on a traffic plan from $0.8/GB. The moment you start pulling landing pages or rendering screenshots alongside the results, payload multiplies several times over, and a bandwidth plan at $32/day for 100Mbps with unmetered traffic wins.
Get one request working. Scale after that.
Test before you commit, with an engineer on your integration.