Geo-Grid Rank Tracking Algorithm

Concept

Geo-grid rank tracking simulates Google Maps searches from multiple GPS coordinates around a business to show how rankings vary across a geographic area. The output is a heatmap revealing where the business ranks well (green) and where competitors dominate (red).

Grid Generation (Haversine-Based)

Algorithm

Take center coordinates (business location): center_lat, center_lng
Define grid size (e.g., 7x7 = 49 points) and radius in km
Calculate spacing: step = (2 * radius_km) / (grid_size - 1)
Generate grid points using offset formula:

For each row i (0 to grid_size-1) and column j (0 to grid_size-1):
  dy = (i - center_index) * step_km
  dx = (j - center_index) * step_km
  new_lat = center_lat + (dy / 111.32)
  new_lng = center_lng + (dx / (111.32 * cos(center_lat * pi/180)))

Where center_index = (grid_size - 1) / 2 and 111.32 km = 1 degree latitude.

Grid Sizes and Use Cases

Grid	Points	Typical Radius	Best For	Est. Cost (Live)
3x3	9	2 km	Quick snapshot, low budget	$0.018/keyword
5x5	25	3 km	Standard urban audit	$0.050/keyword
7x7	49	5 km	Default. Best balance of coverage and cost	$0.098/keyword
9x9	81	8 km	Suburban/wide service area	$0.162/keyword
13x13	169	15 km	Rural or large metro	$0.338/keyword

Radius guidelines: Urban dense = 2-5 km, suburban = 5-10 km, rural = 10-25 km.

DataForSEO Integration

Use the Google Maps SERP API with location_coordinate parameter:

{
  "keyword": "dentist",
  "location_coordinate": "30.2672,-97.7431,15z",
  "language_code": "en",
  "device": "mobile",
  "depth": 20
}

For each grid point, fire one API call with the point's lat/lng. Parse the items array to find the target business rank (position in results).

Rate optimization: DataForSEO allows up to 100 tasks per POST. For a 7x7 grid, batch all 49 tasks into a single request to minimize HTTP overhead.

Metric pioneered by Local Falcon. Measures visibility across the grid.

Calculation

SoLV = (points_in_top_3 / total_grid_points) * 100

Interpretation

SoLV	Interpretation
80-100%	Dominant. Business owns the local area.
60-79%	Strong. Visible in most of the service area.
40-59%	Moderate. Significant gaps in coverage.
20-39%	Weak. Competitors dominate most areas.
0-19%	Critical. Nearly invisible in maps results.

Extended Metrics

Average Rank: Mean position across all grid points (lower = better)
Visibility Score: Weighted average where top 3 = 3pts, 4-10 = 1pt, 10+ = 0pts
Worst Quadrant: Identify which compass direction has weakest rankings

ASCII Heatmap Rendering

For terminal/Markdown output, render a grid using rank-position symbols:

Format

Geo-Grid: "dentist" (7x7, 5km radius, center: 30.267, -97.743)

     W -------- E
  N  1  1  2  3  5  8  -
  |  1  1  1  2  3  6  9
  |  2  1  [1] 1  2  4  7
  |  3  2  1  1  1  3  5
  |  5  3  2  1  2  4  8
  |  8  5  3  2  3  6  -
  S  -  8  5  4  5  9  -

Legend: [1]=center, 1-3=top 3 (strong), 4-10=visible, -=not ranked
SoLV: 57% (28/49 grid points in top 3)
Avg Rank: 3.4 | Weakest: NE quadrant (avg rank 7.2)

Color Mapping (for enhanced output)

Position	Symbol	Meaning
1	`1`	#1 ranking (best)
2-3	`2`, `3`	Top 3 (strong local presence)
4-10	`4`-`9`	Visible but not dominant
11-20	`+`	Buried in results
Not found	`-`	Not ranking at this point

Multi-Keyword Grid

For comprehensive analysis, scan 2-3 keywords on the same grid:

Primary service keyword (e.g., "dentist")
Brand + location (e.g., "Smith Dental Austin")
Long-tail intent (e.g., "emergency dentist near me")

Cost for 3-keyword 7x7 scan: 147 API calls = ~$0.29 (live) or ~$0.088 (standard)

Cost Warning Template

Before running a geo-grid scan, display:

Geo-Grid Scan Estimate:
  Grid: 7x7 (49 points)
  Keywords: 3
  API calls: 147
  Estimated cost: $0.09 (standard) - $0.29 (live)
  Proceed? [DataForSEO credits will be consumed]