Two geogrid settings affect the quality of your ranking diagnosis more than any others: grid density and radius. Get them wrong and your heatmap will show you a misleading picture. A grid that is too sparse will hide dead zones. A radius that is too wide will show red areas that are not actually relevant to the business’s service area.
To learn more about building local authority with scan data, visit Run a Local Ranking Heatmap and Find Dead Zones. How to Read a Geogrid and Build a Local SEO Action Plan and Turn 10 GBP Scans Into a Publishable Industry Report cover adjacent steps in detail.
This article explains what grid density and radius control, how to set them correctly for different market types, and how to use multiple geogrid runs at different settings to triangulate a precise ranking diagnosis.
In This Article
What Grid Density Controls
Grid density is the number of points in the grid, expressed as a grid size: 3×3 (9 points), 5×5 (25 points), 7×7 (49 points), or 9×9 (81 points). More points means finer resolution and more API calls.
Grid size options and their appropriate use cases.
| Grid Size | Points | Best For |
|---|---|---|
| 3×3 | 9 | Quick overview scan; initial prospect diagnosis |
| 5×5 | 25 | Standard diagnostic for most markets |
| 7×7 | 49 | Detailed diagnosis for urban markets or complex dead zone patterns |
| 9×9 | 81 | High-resolution analysis for competitive urban markets; before/after tracking |
Start with a 5×5 for any new client. Move to a 7×7 if the 5×5 shows a complex dead zone pattern you cannot fully explain from 25 data points. Use 9×9 only for monthly tracking in highly competitive urban markets.
What Radius Controls
Radius is the distance between grid points. A 0.5 mile radius means each grid point is 0.5 miles from its neighbor. The radius does not change the center of the grid, which is always the business address. It changes how far the grid extends and how granularly it covers that area.
- A small radius covers a small area in fine detail. Use this for businesses in dense urban markets where the competitive landscape changes significantly within a few blocks.
- A large radius covers a wide area in coarse detail. Use this for businesses in suburban or rural markets where the service area is large and ranking differences are measured in miles rather than blocks.
Recommended Settings by Market Type
Grid density and radius recommendations by market type.
| Market Type | Recommended Grid | Recommended Radius | Rationale |
|---|---|---|---|
| Dense urban (NYC, Chicago, San Francisco) | 7×7 | 0.3-0.5 miles | Competitors change every few blocks; fine resolution needed |
| Urban (Columbus, Austin, Denver) | 5×5 | 0.5-1 mile | Standard competitive density; 5×5 captures the key patterns |
| Suburban | 5×5 | 1-2 miles | Service area is larger; no need for block-level resolution |
| Rural or large service area | 3×3 or 5×5 | 2-5 miles | Searchers are far apart; wide radius reflects actual service geography |
Using Multiple Grids to Triangulate
- Two keywords, same grid. Run the same 5×5/1 mile grid for “HVAC repair Columbus” and “furnace installation Columbus.” Different dead zone patterns for the two keywords point to service-specific profile gaps rather than general authority problems.
- Same keyword, two radii. Run a 5×5 at 0.5 miles and a 5×5 at 2 miles. If the business shows green at 0.5 miles but red at 2 miles, the profile authority does not project beyond close proximity.
- Client vs competitor, same grid. Run the grid centered on your client’s address and then centered on the dominant competitor in their dead zone. Comparing the two heatmaps shows exactly what the competitor has that your client does not.
For how to interpret the patterns these multi-grid runs reveal, see How to Read a Geogrid Result and Build an Action Plan.
Common Configuration Mistakes
- Using a 5 mile radius in a dense urban market. Your grid ends up covering areas completely outside the business’s competitive set. Use 0.5 miles in dense markets.
- Using a 0.5 mile radius for a rural service business. The entire grid fits within a few blocks of the business. Use 3 to 5 miles.
- Running a 3×3 grid and drawing conclusions about a specific dead zone. Nine points are not enough resolution to confirm a dead zone pattern. A cluster of red points in a 7×7 grid is a confirmed dead zone. A single red point in a 3×3 grid could be a data anomaly.
- Changing the radius between tracking runs. If you run a 5×5/1 mile grid in month one and a 5×5/2 mile grid in month two, the maps are not comparable. Lock in the settings for any client you are tracking over time.
How F! Insights Handles Grid Configuration
F! Insights presents grid size and radius as configurable fields in the Near Me Visibility tool inside the Client Workspace. The grid configuration is saved per-client so that tracking runs always use the same settings. Claude generates the 5-pillar action plan from whichever grid result you run, adjusting its analysis based on the market density context the grid settings imply.
Run a free GBP scan first to establish the client’s GBP health baseline, then configure the Near Me Visibility tool with the market-appropriate settings from the table above. For the full dead zone identification workflow, see How to Run a Local Ranking Heatmap and Find Dead Zones.
Related reading: This guide assumes you have already completed running the full local ranking heatmap. After adjusting the configuration, reading the geogrid output and building an action plan explains how to use the results. Grid configuration problems often mask the real issues described in why a business disappears from the Google Map Pack.
Frequently Asked Questions
- Does a larger grid always give a better diagnosis?
- Not always. A larger grid costs more API calls and takes longer to process. For most diagnostic purposes, a 5×5 grid gives you enough resolution to identify the patterns that matter. Use a 7×7 or 9×9 only when you need to confirm a specific pattern identified in the 5×5 or when tracking fine-grained ranking movement in a competitive urban market.
- Should I run geogrids before or after fixing the GBP profile?
- Before, to establish the baseline. After, to confirm the fix worked. The before geogrid is your diagnostic. The after geogrid, run 60 to 90 days after the fixes are complete, is your proof of progress. Both are equally important for client reporting.
- What grid size should I use for an initial diagnostic scan?
- A 7×7 grid at 0.5-mile spacing works for dense urban markets and gives you enough resolution to see directional dead zones. For suburban and rural markets, increase the spacing to 1 mile or 1.5 miles. Tighter spacing in low-density areas just shows the same dead zone pattern repeated across adjacent points. Start with a medium configuration and adjust the follow-up scan based on what the first one shows.
- What does it mean if the geogrid shows high ranking variance across adjacent grid points?
- High variance between adjacent grid points, such as ranking 1 at one point and ranking 8 at the next point 0.5 miles away, usually indicates a configuration issue in the scan rather than actual ranking instability. Run the scan again. If the variance persists, it means Google’s algorithm is producing genuinely inconsistent results for that keyword in that area, often because two or more competitors with similar authority are clustered in the same zone.
- How does adjusting the grid radius change the diagnostic output?
- A smaller radius shows detailed ranking behavior close to the business address, good for diagnosing why a business is not winning the Map Pack for customers who are physically nearby. A larger radius shows you the outer boundary of the ranking envelope, how far from the business address does it rank before falling off the Map Pack entirely. Use the smaller radius to diagnose profile-level problems and the larger radius to measure how far the current optimization work has extended the ranking footprint.