Testing location data with edge cases, not just happy paths
An address in a well mapped city center tells you almost nothing about how your system handles a rural route, a disputed border, or a query near the poles. Test the hard cases deliberately.
The difference between rooftop and street-level geocoding
Two geocoded points sitting a few meters apart on a map can represent fundamentally different kinds of match, and the difference between them, rooftop versus street-level geocoding, is one of the more important distinctions hiding behind a single dot on a screen.
Rooftop geocoding places the returned coordinate at the actual location of the specific building matched to the address, generally derived from real building or parcel data that records where that structure actually sits. This is the most precise category of match available, and it is what the house precision level in a response is meant to represent, a coordinate that corresponds to an identified physical building, not an estimate of where one probably is.
Street-level geocoding works differently. Rather than matching to a specific known building, it interpolates a position along a road segment based on where the requested house number would statistically be expected to fall within the known range of numbers on that segment, assuming a roughly even distribution of addresses along the street's length. This produces a coordinate that sits on or near the correct road and in approximately the right stretch of it, but it is fundamentally an estimate based on typical numbering patterns, not a confirmed location for that specific building.
The gap between the two matters more than it might initially seem, because street-level interpolation assumes numbering is reasonably even and sequential along a segment, an assumption that does not always hold. Where a street has been developed unevenly, where numbering has gaps, or where a long segment covers a wide range of addresses unevenly distributed across its length, an interpolated point can land a meaningful distance, sometimes a full building or more, away from the actual structure, even though the underlying method is working exactly as designed.
This is precisely the distinction the precision field is built to surface, so it should always be checked rather than assumed from the coordinate alone, since a rooftop match and a street-level interpolation can produce visually similar-looking points on a map while carrying meaningfully different real accuracy. For any use case where the difference actually matters, dispatching a service call to an exact building rather than a nearby one, for instance, checking for house precision specifically, rather than accepting any result that resolved somewhere on the correct street, is the difference between relying on a confirmed match and relying on a statistical estimate.
Our forward geocoding endpoint reports the actual precision achieved for every match, specifically so your application can distinguish a confirmed rooftop result from a street-level interpolation before deciding how much to trust it for your particular use case.