Geogrid

A geogrid is a grid of geographic points laid over a service area, each used as the search origin point for a simulated local search query. The result is a map of how a business ranks for a given keyword at each point across its geography.

Definition

A geogrid overlays a grid of X×Y points over a geographic area. Each point runs a simulated local search from that location.

Example: A 7×7 grid = 49 points. Each point searches “plumber near me” from that specific coordinate. The result is 49 position values showing your rank at each location.

The output is a visual map: numbers at each grid point showing your position, often color-coded (green for 1-3, yellow for 4-7, red for 8+, gray for not ranking).

What a Geogrid Reveals

Geogrids expose the geographic dimension of local search that single-point rank checks miss.

Proximity dominance patterns: Strong rankings near your address, weakening at distance. Reveals the “proximity cliff” where your ranking falls off.

Ranking dead zones: Areas where you don’t appear at all while competitors do. These are geographic market segments you’re losing.

Geographic competitive advantages: Zones where specific competitors dominate, often due to their physical location or targeted local signals.

Market coverage assessment: What percentage of your service area actually sees you in results?

A traditional rank check from one location shows your position at that spot. A geogrid shows your position across your entire market.

Grid Size and Spacing Options

Grid sizes:

  • 3×3 (9 points): Quick check, limited detail
  • 5×5 (25 points): Standard analysis
  • 7×7 (49 points): Thorough analysis
  • 9×9 or larger: Detailed analysis for large service areas

Spacing between points:

  • 0.3-0.5 miles: Urban markets, dense competition
  • 0.75-1 mile: Suburban markets
  • 1.5-2+ miles: Rural areas or large service territories

Decision framework:

  • Use smaller spacing in competitive urban markets where rankings change quickly with distance
  • Use larger spacing for service area businesses covering wide territories
  • Start with 5×5 for initial analysis, expand to 7×7 for detailed work

How Geogrid Data Connects to Strategy

Different geogrid patterns indicate different problems:

Uniform low rankings (position 5-10 everywhere):

  • Diagnosis: Prominence issue
  • Action: Build reviews, citations, authority across the board

Strong near address, weak at distance:

  • Diagnosis: Proximity dominance, weak prominence to sustain ranking
  • Action: Build prominence signals, target outlying areas with content and citations

Quadrant-specific weakness:

  • Diagnosis: Local competitor advantage in that zone
  • Action: Analyze what competitor has in that area, target with local signals

Random patchwork:

  • Diagnosis: Inconsistent signals or algorithm volatility
  • Action: Build consistent prominence across all dimensions

The pattern tells you where to focus.

Tools That Generate Geogrids

LocalSEOData geogrid_scan:

  • On-demand scans
  • Returns ARP, ATRP, SoLV
  • Good for point-in-time analysis

Local Falcon:

  • Recurring scan campaigns
  • Historical trend tracking
  • Falcon Guard monitoring integration
  • Campaign-level reporting

What each provides: LocalSEOData is ideal for one-time audits and snapshots. Local Falcon adds the historical dimension for tracking progress over time.

Interpreting Geogrid with LocalSEOSkills

The geogrid-analysis skill transforms raw geogrid data into strategic recommendations:

"Run a geogrid for 'dentist Phoenix' centered on [Business Address].
Use 7×7 grid with 0.5 mile spacing.
Interpret the results and identify our biggest geographic opportunities."

What Claude provides:

  • ARP, ATRP, SoLV summary
  • Geographic zone breakdown
  • Dead zone identification
  • Competitor presence analysis
  • Prioritized actions by zone
  • Expected improvement timeline

Geogrid Best Practices

Consistency matters: When tracking progress, use the same grid size, spacing, and center point. Changing parameters makes month-over-month comparison meaningless.

Keyword selection: Run geogrids for your primary target keyword first. Additional keywords add value but increase complexity.

Timing: Run at the same time of month for trending analysis. Rankings fluctuate; consistent timing reduces noise.

Interpretation over data: Raw geogrid numbers need interpretation. A geogrid showing mostly 4s and 5s looks different than one showing 1s and 20s that averages to the same ARP.

  • ARP: Average Rank Position — primary geogrid metric
  • ATRP: Average True Rank Position — penalizes non-appearances
  • SoLV: Share of Local Voice — top 3 percentage
  • LocalSEOData: geogrid_scan endpoint
  • Local Falcon: Recurring geogrid campaigns
  • Proximity cliff: Where ranking falls off from address