---
title: Build a Chain Store Locator | Plaza Docs
description: A Go CLI that finds all locations of a brand near you, calculates driving distances, and prints them sorted by travel time.
---

Type a brand name and your location, get back every matching store sorted by how long it takes to drive there. This is a Go CLI — no web server, no frontend.

## What you’ll use

- **Geocoding** to turn your location into coordinates
- **PlazaQL** to find all locations of a brand by OSM tags
- **Distance matrix** to rank results by driving time

## Key code

The interesting part is the PlazaQL query. OpenStreetMap has detailed brand tagging — a Whole Foods isn’t just `shop=supermarket`, it has `brand=Whole Foods Market` and a Wikidata link. We use a regex match to catch all variants:

```
query := fmt.Sprintf(
    `$$ = search(brand: ~"%s").around(distance: 25000, geometry: point(%f, %f));`,
    brand, lat, lng,
)
```

The `~` operator does regex matching — so “whole foods”, “Whole Foods Market”, and “WHOLE FOODS” all match. We search all element types (nodes and ways) by omitting the type argument, because stores can be mapped as either a point or a building outline. `distance: 25000` restricts results to within 25km.

Once we have the store locations, we feed them into the distance matrix API — one origin (you), many destinations (the stores):

```
matReq := MatrixRequest{
    Origins:      [][]float64{{originLat, originLng}},
    Destinations: destinations,
    Profile:      "car",
    Annotations:  []string{"duration", "distance"},
}
```

Then attach the results and sort:

```
for i := range stores {
    stores[i].DriveTime = matrix.Durations[0][i]
    stores[i].Distance = matrix.Distances[0][i]
}


sort.Slice(stores, func(i, j int) bool {
    return stores[i].DriveTime < stores[j].DriveTime
})
```

## How it works

1. **Geocode** your location to get lat/lng coordinates.
2. **PlazaQL query** searches OSM’s `brand` tag within a 25km radius. This catches every location that community mappers have tagged, which for major chains is comprehensive. The [Name Suggestion Index](https://nsi.guide/) is the canonical source for brand tags.
3. **Distance matrix** calculates real driving times from you to every store in one API call. This is much better than straight-line distance — a store 2km away across a river might be a 15-minute drive.
4. **Sort by drive time** and print a table.

## Full source

The complete working app is at [github.com/plazafyi/example-apps/store-locator](https://github.com/plazafyi/example-apps/tree/main/store-locator). It’s a Go CLI with a thin Plaza API client wrapper.

Terminal window

```
git clone https://github.com/plazafyi/example-apps
cd example-apps/store-locator
export PLAZA_API_KEY=your-key-here
go run . "Whole Foods" "Union Square, NYC"
```

## Variations to try

**Filter by what’s open.** OSM has `opening_hours` tags. Parse them to show only stores currently open.

**Add the nearest competitor.** Run a second PlazaQL query for a competing brand and show both in the output. “Nearest Whole Foods: 3 min. Nearest Trader Joe’s: 7 min.”

**Find specific services.** Many stores have extra tags like `organic=yes`, `bulk_purchase=yes`, or `wheelchair=yes`. Add these to the PlazaQL filter.

**Export to JSON.** Add a `--json` flag that prints the results as structured JSON for piping into other tools.