> For the complete documentation index, see [llms.txt](https://docs.growthfactor.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.growthfactor.ai/data-and-analytics/foot-traffic.md).

# Foot Traffic

Foot traffic data transforms site analysis from theoretical to empirical. Instead of assuming how busy a location might be, you can see actual visitor patterns—both for the site you're evaluating and for the businesses surrounding it.

Foot traffic intelligence runs throughout the platform, helping you understand not just *what* businesses are nearby, but *how well* they're performing. For how a location compares to others in its brand or category, see [Brand Rankings](/data-and-analytics/brand-rankings.md).

***

### Foot Traffic Heatmaps

Enable the **Foot Traffic** layer from the Layers panel to visualize visitor density. The heatmap displays warmer colors (reds, oranges) in high-traffic areas and cooler colors (blues, purples) in lower-traffic areas.

**Use foot traffic heatmaps to:**

* Identify high-activity zones within a market
* Validate that a site sits within the traffic flow
* Compare relative activity between potential sites
* Spot emerging retail corridors or declining areas

***

### Foot Traffic Trade Zones

Foot Traffic Trade Zones show *where visitors come from* using anonymized mobile location data to map home and work locations of people who visit an area.

#### Coverage Percentages

The percentage slider (50–100%) controls how much of the visitor population to include in your trade zone boundary.

| Coverage   | What It Shows                                                                  |
| ---------- | ------------------------------------------------------------------------------ |
| **50%**    | Core zone—most concentrated, frequent visitors. Your primary customer base.    |
| **60–70%** | Balanced view capturing regular visitors while excluding pass-through traffic. |
| **80%**    | Broader catchment including most customers. Useful for demographic analysis.   |
| **100%**   | Full extent of all observed visitors, including outliers.                      |

#### Visitor Origin Types

Toggle between two views:

**Home Locations** — Where visitors reside. Best for evening/weekend retail, grocery, restaurants serving dinner.

**Work Locations** — Where visitors are employed. Best for lunch-driven restaurants, convenience retail near offices, weekday daytime traffic.

Comparing both views reveals whether a site serves local residents, the daytime workforce, or a blend—critical for understanding peak hours.

{% hint style="info" %}
Not every location has foot traffic data. If a site has no visitor tracking coverage — common for new developments or areas outside typical retail patterns — a **No foot traffic data for this location** message appears.
{% endhint %}

***

### Tracked Businesses Panel

The **Tracked Businesses** section lists competitors and complements with foot traffic intelligence.

**Features:**

* **Unique Brands Only** toggle shows one location per brand (nearest)
* **Rankings** display with color-coded badges. See [Reading Brand Rankings](/data-and-analytics/brand-rankings.md#reading-brand-rankings)
* **Distance** shown for each business
* **Click any business** to highlight on map and see full details

**Quick interpretation:**

| Pattern                      | Signal                                           |
| ---------------------------- | ------------------------------------------------ |
| Multiple green badges nearby | Strong retail corridor, proven customer draw     |
| Mixed colors                 | Typical market with varied performance           |
| Predominantly red badges     | Potential warning sign; investigate site factors |
| Several N/A rankings         | Smaller chains or newer locations without data   |

***

### Best Practices

**Combine heatmaps with rankings.** A site in a high-traffic zone surrounded by underperforming competitors is worth investigating further.

**Check both brand and category performance.** Weak brand ranking but strong category ranking suggests the brand struggles while the location has merit.

**Use visitor origin data to validate demographics.** If your trade zone shows visitors from high-income areas, demographics data should confirm this.

**Look for patterns.** One underperforming competitor doesn't condemn a site; a pattern of weak performers across multiple brands suggests systemic issues.


---

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