If your site serves more than one country, a single rank position per keyword is close to meaningless, even when it looks precise to the decimal. Position 5 for a keyword checked from a default, unspecified location might reflect the US result set, the results Google happens to serve from whichever data center handled that particular request, or some blend that doesn’t correspond to what any actual visitor in your target markets sees. The fix isn’t a separate international tracking system bolted onto the side of your regular rank tracker — it’s the same rank tracker, checking the same keywords, with an explicit location parameter attached to each check so that the position it returns corresponds to a real market rather than an ambiguous default.
That’s the mechanism location settings in AutoSchedulePost are built around — a gl parameter (gl=in for India, and the equivalent code for whichever markets you’re tracking) attached at the keyword or site level, so a check explicitly requests results as they’d appear to a searcher in that country rather than wherever the request happens to resolve by default. It’s a small addition to the existing tracking setup, not a parallel system, which is exactly why it fits cleanly alongside the rest of the daily or weekly checks you’re already running.
Why "Rank" Without a Location Is an Incomplete Question
Search results are localized by default almost everywhere Google operates, and the localization isn’t limited to obviously geographic queries like “plumber near me.” Even broad, apparently location-agnostic keywords return different result sets, different local pack insertions, and sometimes entirely different top-ranking domains depending on the country the search is attributed to — local competitors who don’t show up at all in a US-attributed check can dominate an India-attributed one, and vice versa.
Asking “what’s our rank for this keyword” without specifying a location is really asking an underspecified question that happens to return a confident-looking number anyway. The number isn’t wrong, exactly — it’s a real position for a real check — but it’s a position for an unstated market, and treating it as representative of performance in every country your site targets is where the real distortion creeps in.
Per-Keyword Versus Per-Site Location Assignment
The practical decision most multi-market sites face is whether to set location at the site level — every keyword checked from one default country — or at the keyword level, where individual keywords or keyword groups carry their own location regardless of what the rest of the site defaults to. Both are legitimate depending on structure. A site with genuinely separate country subdirectories or subdomains, each targeting a distinct market with distinct content, often maps cleanly to keyword-level location assignment, since a keyword tracked under the /in/ path should logically be checked with gl=in regardless of what other keywords on the same account default to.
A site that serves a single set of pages to multiple countries without geographic URL segmentation — relying on hreflang or just serving the same content globally — has a harder problem, because there isn’t a natural one-to-one mapping between a page and a location. In that case, the more useful approach is usually tracking the same keyword multiple times, once per target market’s location parameter, so you get separate position data for the same URL as it performs in each country rather than a single blended number that averages across markets you may be serving very differently.
The Same Keyword, Multiple Positions, One Page
It takes some adjustment to get used to seeing a single URL show up with several different rank positions in the same dashboard, one per location, but that’s the accurate representation once multiple markets are in play. A page might sit at position 3 in an in-market check and position 19 in another market’s check for what’s nominally the identical keyword string, and both numbers are correct simultaneously — they’re just answering different questions about different audiences.
This is where the Rank Movers widget’s gaining and losing thresholds become genuinely important to apply per-location rather than in aggregate, because a keyword that’s flat overall but gaining in one market and losing in another is actually two separate stories being flattened into one, and averaging them together erases the more useful signal — that something specific changed in one country’s competitive landscape or search behavior that hasn’t affected the other.
Country Parameters Aren't the Whole Localization Story
The gl parameter controls which country’s result set a check is attributed to, but it’s not the only variable that affects what a real searcher in that market sees. Language, device type, and even the specific city or region within a large country can shift results further, and gl=in on its own doesn’t account for the difference between a search attributed broadly to India versus one attributed to a specific city within it, where local pack results and region-specific competitors can look meaningfully different.
For most content-driven SEO tracking — the kind aimed at organic, non-local-pack rankings — country-level location settings are usually sufficient granularity, and chasing city-level precision on every keyword adds tracking overhead without a proportional increase in decision-useful information. But it’s worth being explicit with yourself about what gl=in is and isn’t accounting for, particularly if a client or stakeholder is asking why a tracked position doesn’t match what they personally see when they search from a specific city — the discrepancy is often exactly this granularity gap, not a tracking error.
Backlinks and Schema Don't Need the Same Multi-Location Treatment
It’s worth being clear about which parts of the monitoring stack actually need to be duplicated per market and which don’t, since over-applying the multi-location pattern everywhere adds unnecessary overhead. Rank position is inherently location-dependent and needs the gl parameter attached per market. Backlink monitoring, by contrast, is tracking the link graph pointing at a URL or domain, which doesn’t change based on which country’s search results you’re comparing against — a backlink either points at your page or it doesn’t, regardless of geography, so there’s no equivalent need to run backlink checks once per target market.
Schema markup sits somewhere similar — the structured data on a page is what it is regardless of which country’s search results are being evaluated, though it’s worth noting that publisher and organization fields should still reflect the correct regional entity if your site legally operates as separate entities per market, which is a content-accuracy issue rather than a location-tracking one.
Fallback Providers Across Locations
The fallback provider option that covers primary ranking API failures matters somewhat more for international tracking than single-market tracking, simply because there are more checks running and more location-specific requests that could individually hit a rate limit or outage window. It’s worth confirming, if you’re tracking several markets simultaneously, that a fallback event on one location’s checks doesn’t quietly skip or delay checks for other locations in the same run — a partial outage that only affects certain markets is easy to miss if the dashboard is being read at the aggregate, all-keywords level rather than broken out by location.
Checking that each location’s data is current independently, rather than assuming the whole account refreshed successfully because most of it did, is a small habit that avoids acting on stale data for whichever market happened to be affected by a temporary provider issue.
Setting Expectations for New Markets
A newly added location — say, expanding tracking to include gl=in for a site that previously only tracked a US market — starts with no historical baseline, which means the flat/gaining/losing thresholds that rely on trailing comparison won’t have meaningful data to compare against for the first several check cycles. Treating the first few weeks of a new location’s data as a baseline-building period rather than expecting immediately actionable gaining or losing signals avoids over-reacting to what’s really just the system establishing what normal looks like for a market it hasn’t watched before.
This matters more than it might seem, because the temptation with a newly expanded market is to watch it closely and react to every early fluctuation, when the more useful move is usually patience — letting a few weeks of checks accumulate before drawing conclusions about whether performance in the new market is actually trending in a direction worth acting on.
Auto-Enrollment and Multi-Location Sprawl
Rank Tracker’s default behavior of auto-enrolling every published page is convenient for a single-market site, where it means new content gets picked up for tracking without anyone remembering to add it manually. Applied naively across a multi-location setup, though, that same default can produce a lot of tracking sprawl — if auto-enrollment attaches every new page to every configured location rather than the locations relevant to that specific page, you end up checking a page written for one regional audience against markets it was never intended to rank in, generating position data for keyword-location pairs that don’t correspond to anything a real content or SEO decision hinges on.
It’s worth reviewing how auto-enrollment interacts with your location configuration once more than one market is active, and scoping it deliberately — pages under a specific regional path enrolling only into that region’s location, for instance — rather than letting the convenient default quietly multiply the number of checks running without a corresponding increase in useful information.
Reporting Across Markets Without Flattening the Differences
Once you’re tracking several locations for overlapping keyword sets, there’s a natural pull toward summarizing performance as a single blended metric for stakeholder reporting — one average position, one overall trend line, one number that’s easy to put in a slide. That instinct is understandable but it reintroduces the exact problem multi-location tracking was set up to solve, because an average across markets performing very differently tells you less than either market’s number told you on its own, and can mask a market that’s declining behind one that’s improving.
Reporting by market, even when it’s more numbers on the page than a single blended figure, keeps the underlying reality visible — a keyword set that’s genuinely strong in one country and weak in another is a different strategic situation than one that’s moderately fine everywhere, and collapsing the two into a lookalike average removes exactly the information that would tell you where to focus next.
Where to Go Next
Multi-location tracking is one piece of a broader monitoring approach that also covers backlink velocity, schema eligibility, and competitive positioning — signals that are more useful read as a connected system than checked separately. For the complete picture, see Rank Tracking and SEO Monitoring: The Complete Guide.
