Why Google Maps Caps You at ~20 Results (and How to Actually Cover a Whole City or State)

Try this: search "cafe" in any mid-size city on Google Maps. You'll get a list — and it will feel complete. It isn't. Google Maps search caps how many results it returns for a given query and location, and that cap holds regardless of how many cafes actually exist in that city. Zoom out, and you'll see the map fill with more pins as you scroll the list, but you're still capped per search; you're just trading which businesses show up.

Why the cap exists in the first place

Google Maps search is built to answer "what's near me right now," not "list every business of this type in this region." For that use case, showing the 20 or so closest, most relevant results is exactly right — nobody wants to scroll through 400 cafes to find one to walk into. The side effect is that the same interface, used for prospecting instead of personal navigation, silently under-delivers: you see a small, geographically-biased slice of what's actually out there.

What this means for lead generation

If you're building a list of every plumber in a state, or every independent cafe in a metro area, a single search from the city center will only ever surface a small fraction of them — typically the ones closest to wherever your search was centered, or the ones with the strongest existing Maps presence. Businesses on the edges of the city, or in a less map-prominent area, simply don't show up, not because they don't exist, but because the search never reached that far.

The fix: grid search

The practical solution is straightforward in concept: instead of one search centered on the city, generate a grid of points spread across the whole area — spaced closely enough that each point's search radius overlaps its neighbors — and run one search per point. A city might need 10-30 grid points; a whole state or country needs many more, spaced further apart to match the larger area.

Because grid points overlap at the edges, the same business will often appear in results from more than one point — which means deduplication has to happen automatically afterward, matching businesses by their unique place identifier or by name-and-address, so the final list has each business exactly once regardless of how many grid points found it.

Why this needs to run in the background

Running dozens of searches sequentially, each waiting on the last, takes real time — a whole state's worth of grid points is not a sub-second operation. That's why a proper implementation queues the whole area as a background job: you start the search, it works through the grid at a sensible pace (so as not to hammer the underlying search provider), and the results populate as they come in rather than making you wait on a blocked browser tab.

Choosing the right grid density for your search

A tight grid (closely spaced points) over a small area like a single city gives near-complete coverage but is unnecessary — and slower — for something the size of a whole country. The right approach scales grid spacing to the search type: dense for a city or district, progressively coarser for a state, and coarser still for a whole country, so a country-level search still finishes in a reasonable time while still finding businesses spread across the map rather than clustered around a handful of major metros.

How many grid points does a search actually need

There's no single right number — it depends on the physical size of the area and how densely the category you're searching is distributed. A single city typically needs a modest number of points (a handful to a few dozen) to get solid coverage. A whole state needs meaningfully more, spaced further apart, since the goal shifts from "find every match" to "find a representative, comprehensive sample across the whole area" within a reasonable run time. A well-built grid search caps the total number of points per search type specifically so a country-wide search doesn't take hours — trading a small amount of theoretical completeness for a search that actually finishes.

What happens to businesses right on the edge of two grid points

This is exactly why deduplication isn't optional in a grid search — it's a structural requirement. A business sitting near the boundary between two adjacent grid points' search radius will often appear in results from both. Left unmerged, that inflates your list with the same business counted twice; merged correctly (matching on a stable identifier or normalized name-and-address), it's counted once, and you keep the coverage benefit of overlapping search radii without the duplicate-counting downside. See our full guide on lead deduplication for how that matching actually works.