Google applies the same relevance-distance-prominence framework to both business types, but the location input feeding the distance calculation differs structurally. A storefront business has a public, verified physical address that’s used directly and visibly for distance calculations, since customers travel to that location. A service area business declares a service area (a set of cities, ZIP codes, or a radius it serves) and may hide its actual street address from public view, with Google instead using an address on file, provided during setup but not necessarily displayed, combined with that declared service area, to determine eligibility and estimate distance for a given search.
The mechanism: two different location-input models under one framework
Google’s Business Profile documentation is explicit that both business types are evaluated under the same three named local ranking factors: relevance (how well the business matches what’s being searched for), distance (how far the business is from the location relevant to the search), and prominence (how well-known and reputable the business is generally). Neither business type gets a separate algorithm; both feed into the same underlying local ranking system. What differs is how each type provides the location data that the distance factor consumes.
For a storefront, the address is meant to be public because that’s the real point of physical interaction with customers, and it functions straightforwardly as the fixed reference point from which distance to a searcher is calculated. There’s no separate “declared area” step; physical proximity to the storefront’s actual, disclosed address is essentially the input.
For a service area business, Google’s setup documentation for SABs explicitly permits hiding the public-facing address, since the business model doesn’t involve customers visiting a location, service happens at the customer’s site instead. But an address is still required internally during profile setup and verification, and Google uses that address on file, whether or not it’s shown publicly, as an anchor point for distance estimation. On top of that, the SAB also declares a service area, and eligibility to appear for a given search additionally depends on whether the searcher’s location falls within or reasonably near that declared area, an additional filter that storefronts don’t have in the same form, since a storefront’s relevant “area” is essentially defined by its actual physical location and normal proximity considerations rather than by a separately declared boundary.
Why this isn’t two separate algorithms
It’s worth being precise that the difference here is in inputs, not in the underlying evaluation logic. Both business types still compete on the same three factors, and Google hasn’t published or implied a fundamentally different local ranking system running for one type versus the other. The distinction is entirely in how the distance/location half of the relevance-distance-prominence trio is fed for each type: direct, public address for storefronts; address-on-file plus a declared service area for SABs. Framing this as “SABs use a totally different, separate algorithm” overstates a difference that’s really about location-input mechanics within one shared framework.
This also means eligibility outcomes can look different in practice even under identical underlying logic. A storefront’s eligibility ties fairly directly to its actual physical proximity to a searcher, regardless of any additional declared boundary. An SAB’s eligibility is filtered by whether the searcher falls inside its declared area in addition to the raw distance calculation from the address on file, meaning an SAB can be filtered out of eligibility for a search that falls outside its declared area even if the raw distance from its address on file would otherwise be comparable to a nearby storefront’s distance from the same search point.
A worked comparison of how the two models resolve the same search
Consider a plumber operating as a storefront with a public shop address in the eastern part of a metro area, alongside a competitor operating as a service area business with a genuine base of operations in the same eastern part of the metro, but who has chosen to hide that address publicly and has declared a service area covering the entire metro, including the western suburbs. For a search originating in the western suburbs, the storefront plumber’s distance calculation runs directly from its disclosed, physical eastern address, a real, fixed, and fairly substantial distance from the searcher. The SAB plumber’s eligibility for that same western-suburbs search depends first on whether the western suburbs fall within its declared service area (they do, in this example), and its distance calculation still runs from its own address on file, which is also in the eastern part of the metro, so the raw distance component is comparably disadvantaged to the storefront’s in this case. Neither business gets a structural proximity break just because one is an SAB; the SAB’s declared-area inclusion determines eligibility to be considered at all, while the underlying distance math for both businesses is still anchored to wherever their real operating base actually sits.
Now consider a search originating from the eastern part of the metro, close to both businesses’ actual operating base. Here both the storefront and the SAB benefit from being genuinely close to the searcher, and whatever ranking difference emerges is more likely to come down to relevance and prominence than to any structural distance advantage tied to business type. This comparison illustrates the core point: the SAB/storefront distinction changes how location data is input and whether an additional service-area eligibility filter applies, not which business type gets a fundamentally easier or harder distance calculation in the abstract.
Practical implication
For SAB profile setup specifically, accuracy on both inputs matters independently: the address on file should be genuine and precise (since Google’s verification process is designed to catch inconsistencies, and using it to inflate proximity rather than reflect the real operating base risks a guideline violation and possible suspension), and the declared service area should honestly reflect where the business actually serves customers rather than being inflated to chase broader search volume, since an overly broad declared area dilutes relevance for the searches that fall within it without genuine capacity or reason to serve that area well. For storefronts, the equivalent accuracy concern is simpler, keep the public address current and precisely geocoded, since that’s the direct input driving the distance calculation with no additional declared-area layer involved. Neither business type should assume there’s a specific, published eligibility radius number at play; Google hasn’t disclosed exact distance thresholds for either model, and the practical lever in both cases is ensuring the location inputs are accurate and letting relevance and prominence do the remaining competitive work distance alone can’t guarantee.
