> 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/brand-rankings.md).

# Brand Rankings

A Brand ranking tells you how a location performs against comparable businesses.

<figure><img src="https://2595087262-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FjYLFGKmaRxwLlrdFzDm2%2Fuploads%2FrlWRB2LTliSatNDnGj4Z%2Fimage.png?alt=media&amp;token=e2c2c017-7f92-4bc0-a245-cbf5b41f43c2" alt=""><figcaption></figcaption></figure>

{% hint style="info" %}
**Beta Feature:** Foot traffic rankings are currently in beta. Data accuracy continues to improve as we refine our models. Please contact support if you encounter unexpected rankings.
{% endhint %}

***

### Choosing a Ranking Source

Click a business on the map and its popup carries a **Rankings** block. Brands can be ranked based on two data sources:

* **Popularity** ranks the location on its Dataplor popularity score. The block reads **Powered by Dataplor**.
* **Foot Traffic** ranks it on visits. The block reads **Powered by Unacast**.

Popularity is the default. Your pick is saved in your browser and applies to every business popup you open, in every study and on Site Analysis.

Both sources rank a location two ways, against its **Brand** and against its **Category**. Both break out **Local**, **State**, and **National**.

When only one source can rank a location, the block names that source and shows no toggle.

***

#### Reading Brand Rankings

Rankings appear as percentiles with color coding:

| Ranking        | Color  | Meaning                                         |
| -------------- | ------ | ----------------------------------------------- |
| **Top 25%**    | Green  | Strong performer; outperforms 75%+ of the brand |
| **Top 26–50%** | Yellow | Average performer for the brand                 |
| **Bottom 50%** | Red    | Underperforms compared to most locations        |
| **N/A**        | Gray   | Insufficient data to calculate ranking          |

**Small chains:** For brands with fewer than 5 locations, rankings display as "X of Y" (e.g., "2 of 4") instead of percentiles.

#### Ranking Levels

Click any business to see performance across three geographic scopes:

| Level        | Comparison Set                               |
| ------------ | -------------------------------------------- |
| **Local**    | Other brand locations within \~15 miles      |
| **State**    | All brand locations within the same state    |
| **National** | All brand locations across the United States |

A location might rank Top 10% locally but only Top 50% nationally—strong for its market but average compared to the brand's best nationwide.

#### Why Rankings Matter

Rankings provide context that raw visit numbers cannot:

* **A Starbucks with 8,000 monthly visits** in the Bottom 25% suggests something about that site is underperforming.
* **A cluster of Top 25% performers** nearby signals strong retail fundamentals.
* **Multiple Bottom 50% competitors** may indicate location challenges worth investigating.

***

### Category Performance

Category Performance compares a location against *all businesses in its category*, not just its own brand.

| Comparison Type | What It Tells You                                             |
| --------------- | ------------------------------------------------------------- |
| **Brand**       | How this location performs vs. other stores in the same chain |
| **Category**    | How this location performs vs. all businesses in the category |

**Example:** A Target ranking Top 45% within Target but Top 30% in Department Stores nationally indicates an average Target but a strong department store—the location has solid fundamentals.

***

### Popularity Rankings

Popularity Rankings compare a location's Dataplor popularity score against other businesses, either in the same brand or the same category.

#### What the Popularity Score Measures

The popularity score runs 0–100 and reflects how frequently a location is visited relative to other businesses. Several signals feed it:

* Aggregated, anonymized consumer survey data from enterprise partners
* How many datapoints exist for the location
* Place history, such as temporary closures
* Operating hours and available amenities

The score updates monthly, so a location's popularity rankings move as the underlying signals change.

#### How Locations Compare

| Comparison Type | What It Tells You                                            |
| --------------- | ------------------------------------------------------------ |
| **Brand**       | How this location compares to others in the same brand       |
| **Category**    | How this location compares to all businesses in its category |

Each comparison breaks out into the same three scopes as Brand Rankings — **Local**, **State**, and **National** — and reads on the same color-coded percentile scale. Each card also shows where the location sits in that set, like **3 of 7**.

Popularity reaches locations that visit data doesn't. A business with no foot traffic match still carries popularity rankings, and its popup leads with them.

An independent business has no brand to rank against, so it shows a **Category** ranking only.

{% hint style="info" %}
Popularity rankings come from Dataplor. Data may be limited for some locations.
{% endhint %}


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.growthfactor.ai/data-and-analytics/brand-rankings.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
