If you have run a Local Search Grid scan and noticed the point count is higher than you expected, this is by design. The platform uses a hexagonal ring layout, not a literal NxN square. A "5x5" setting in the grid size dropdown means five hexagonal rings around the centre pin, which works out to 91 scan points in total.
This guide explains the formula behind every supported grid size, what the point spacing value actually controls, and how to estimate the DataForSEO cost of a scan before you run it.
The short answer
The grid size value in the scan form is the number of rings around the centre pin, not the side length of a square. Each ring is populated with a number of evenly spaced points equal to ceil(6 multiplied by the ring index). Adding the centre pin gives the total scan point count.
The naming convention mirrors other geo-grid tools so the dropdown feels familiar, but the layout underneath is denser and gives more even geographic coverage than a square grid of the same name.
Formula: total_points = 1 + sum of ceil(6 multiplied by r) for r from 1 to gridSize.
Pin count for every supported grid size
Every grid scan starts with one centre pin at the business location and then places rings around it. The first ring has 6 points, the second has 12, the third has 18, and each new ring adds 6 more points than the one before it.
| Grid size | Centre | Ring breakdown | Total pins |
|---|---|---|---|
| 3x3 | 1 | 6 + 12 + 18 | 37 |
| 5x5 | 1 | 6 + 12 + 18 + 24 + 30 | 91 |
| 7x7 | 1 | 6 + 12 + 18 + 24 + 30 + 36 + 42 | 169 |
| 9x9 | 1 | 6 + 12 + ... + 48 + 54 | 271 |
| 11x11 | 1 | 6 + 12 + ... + 60 + 66 | 397 |
| 13x13 | 1 | 6 + 12 + ... + 72 + 78 | 547 |
| 15x15 | 1 | 6 + 12 + ... + 84 + 90 | 721 |
Why hexagonal rings instead of a square grid
A square 5-by-5 grid puts 25 points on a flat plane with even spacing in two directions. It looks tidy on paper, but it is a poor match for how Google Maps results actually change as a searcher moves around. A circle of customers around a business does not radiate out in neat rows. It radiates out in every direction.
Hexagonal rings give roughly equidistant coverage in all directions from the centre. Every pin in the same ring sits the same distance from the business, so the report shows how rankings degrade by distance rather than by which corner of a rectangle the point happens to fall in.
The density also matches how local pack results behave in practice. Rankings can shift over a few city blocks, and a denser layout catches those transitions instead of stepping over them.
What the point spacing setting actually controls
The point spacing (also called distance) value sets the radius of the outermost ring. Inner rings are spaced proportionally between the centre and that edge, so the radial distance between consecutive rings equals point spacing divided by grid size.
For example, a 5x5 scan with 5 mile point spacing has 1 mile between rings, with the outermost ring at the full 5 mile radius.
The pin count stays the same regardless of how the point spacing is set. A 5x5 scan with a half-mile radius and a 5x5 scan with a 10 mile radius both run 91 scan points. Point spacing only changes how spread out those points are.
Estimating the DataForSEO cost of a scan
The platform runs one DataForSEO Google Maps SERP task per scan point per keyword. The formula for total billable tasks is: total_tasks equals total_pins multiplied by keyword_count.
For a 5x5 scan with three keywords that is 91 multiplied by 3, which is 273 SERP tasks.
On the standard DataForSEO queue the per-task rate is $0.0006 at the time of writing, which means a 5x5 single-keyword scan costs roughly $0.055 and a 5x5 three-keyword scan costs roughly $0.164. Priority and Live queue tiers are more expensive. Always confirm the current DataForSEO rate against your account before relying on these figures.
| Grid size | Pins | 1 keyword | 3 keywords |
|---|---|---|---|
| 3x3 | 37 | $0.0222 | $0.0666 |
| 5x5 | 91 | $0.0546 | $0.1638 |
| 7x7 | 169 | $0.1014 | $0.3042 |
| 9x9 | 271 | $0.1626 | $0.4878 |
| 11x11 | 397 | $0.2382 | $0.7146 |
| 13x13 | 547 | $0.3282 | $0.9846 |
| 15x15 | 721 | $0.4326 | $1.2978 |
How to pick the right grid size
More points is not always better. Denser grids cost more, take longer to complete, and produce a busier report. Match the grid size to the actual service area, not to a default.
- 3x3 (37 pins): tight neighbourhood scans, single coffee shops, small dental practices, anything inside a 1 to 2 mile radius
- 5x5 (91 pins): the most common default, covers a 3 to 5 mile service area with enough density to catch transitions between neighbourhoods
- 7x7 (169 pins): wider metro coverage, service area businesses, multi-suburb plumbers, electricians, and HVAC operators
- 9x9 and above (271+ pins): large metro audits, regional firms, multi-city franchises, one-off upfront sales presentations
Where this math lives in the platform
The pin layout is generated by a single algorithm shared between the JavaScript front end and the PHP back end so that the same scan run from the UI and from the API produces identical coordinates. That means the snapshot timeline aligns correctly across reruns and the pin set is reproducible.