What is geo-grid (map-grid) tracking?
Geo-grid tracking samples your map-pack position from many points laid out across a geographic area, producing a grid of rankings rather than a single figure. The output looks like a heat map: strong near your verified location, typically weakening with distance, with local exceptions where a competitor is dominant.
Why does a single map ranking number mislead?
Map position is proximity-sensitive, so “we rank #3 in Atlanta” is close to meaningless. You might be #1 within two miles and absent past six. A city-level average hides exactly the neighbourhoods worth acting on, which are usually the ones where you are invisible rather than the ones where you already win.
| What you are reading | One city-level number | A geo-grid |
|---|---|---|
| Output | A single figure | A grid of rankings rather than a single figure |
| Distance falloff | Not visible | Strong near your verified location, typically weakening with distance |
| Competitor pockets | Averaged into the one number | Local exceptions where a competitor is dominant |
| Neighbourhoods worth acting on | Hidden | Readable point by point |
How does Mindflow use geo-grid tracking?
Mindflow uses a geo-grid as a measurement input, not as the report. It is one of the inputs to Search Visibility Share, reported city by city rather than blended. It also makes the proximity constraint legible: if the grid shows a clean distance falloff and nothing else, the honest conclusion may be that no marketing work closes that gap.
How can you check your own grid without a tool?
A rough version needs only a browser. Even without a tool, you can approximate this: run the same query from four or five points spread across your market, signed out, with location set explicitly each time. The pattern that emerges, where you hold and where you vanish, is the same information a grid gives you, at lower resolution.
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