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Location data adds geographic context to records, enabling use cases like proximity targeting, foot traffic analysis, and location-based audience building. At its core, location data maps coordinates to meaningful places—transforming raw latitude/longitude pairs into actionable insights.

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Why location context matters

Raw location data typically consists of latitude, longitude, and timestamp—coordinates that have limited meaning in isolation. The latitude 40.74576 and longitude -73.9848 tells you little on its own, but when mapped to “Narrative Headquarters in New York City,” the data becomes actionable. Location context enables:
  • Proximity targeting: Reach users near specific locations
  • Foot traffic analysis: Understand visitation patterns
  • Competitive intelligence: Analyze visits to competitor locations
  • Attribution: Connect ad exposure to physical store visits

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Location polygons

A location polygon is a shape that represents a place, point of interest, or geographic boundary using geospatial coordinates. Polygons are defined by the coordinates of their vertices (corner points), connected by edges.

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What polygons represent

Polygons can represent locations at any scale:
  • Individual buildings or storefronts
  • City blocks or neighborhoods
  • Entire cities or regions
  • Country borders

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Coordinate systems

Most location data uses the WGS84 (World Geodetic System 1984) coordinate reference system, which represents locations as latitude/longitude pairs:
  • Latitude: -90 to 90 (north/south of equator)
  • Longitude: -180 to 180 (east/west of prime meridian)
Coordinate order varies by format. GeoJSON uses longitude-first ([lon, lat]), while many other systems use latitude-first (lat, lon). Always verify the expected order when working with location data.

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Location data formats

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GeoJSON

GeoJSON is a JSON-based standard for encoding geographic data. It’s human-readable, easy to parse in most programming languages, and widely supported. 
{
  "type": "Polygon",
  "coordinates": [[
    [-122.389946, 37.7786],
    [-122.389095, 37.7786],
    [-122.389095, 37.7793],
    [-122.389946, 37.7793],
    [-122.389946, 37.7786]
  ]]
}
Narrative accepts:
  • .json, .geojson, and .parquet files
  • Polygon and MultiPolygon geometries
  • Does not accept GeoJSON embedded in CSV
Validate your GeoJSON using GeoJSONLint before upload.

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Well-Known Text (WKT)

WKT is a text-based format for representing geometry. It’s more compact than GeoJSON but less human-readable. 
POLYGON((-122.389946 37.7786, -122.389095 37.7786, -122.389095 37.7793, -122.389946 37.7793, -122.389946 37.7786))
Narrative accepts:
  • WKT in CSV format
  • Does not accept WKT in JSON format

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Shapefile

Shapefiles are a common GIS format, but they require specialized libraries to read and write. They consist of multiple files (.shp, .shx, .dbf) that must be kept together.

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Point-radius

For locations where exact boundaries aren’t known, point-radius defines a center point and a radius (typically in meters). While not technically a polygon, many systems convert point-radius to polygons by calculating vertices around the circle. 
-122.389521, 37.7789, 100
(longitude, latitude, radius in meters) Narrative accepts:
  • Point-radius in .txt, .json, .parquet, and .csv formats

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Supported file formats

FormatFile TypesNotes
GeoJSON.json, .geojson, .parquetPolygon and MultiPolygon only
WKT.csvWKT column with polygon geometry
Point-radius.txt, .json, .parquet, .csvlon, lat, radius

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Coordinate order

A common source of errors is mixing up longitude and latitude order. Different formats use different conventions:
FormatOrderExample
GeoJSON[longitude, latitude][-122.389, 37.778]
WKTlongitude latitudePOINT(-122.389 37.778)
Google Mapslatitude, longitude37.778, -122.389
For a comprehensive reference, see lonlat.info.

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Creating location data

If you need to define custom polygons:
  1. Drawing tools: Use Bounding Box Tool to draw shapes and export in various formats
  2. GIS software: Tools like QGIS (free) can create and edit complex geometries
  3. Existing datasets: Many POI datasets are available commercially or through open sources

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Related content

IP Addresses

Network-based location signals

Unix Time

Timestamp formats for location data