Trade area data sources — population and spend
Population estimates and retail spend estimates are the two input layers that drive trade area statistics for each co-location cluster. Both are derived from publicly available data sources and applied at the H3 resolution-7 hexagonal grid level, per the distance-band methodology. Together they supply the population and spend axes used by the deterministic ranking system and the V3 catchment ranking methodology.
Population Data
Population estimates are sourced from the WorldPop 2026 100-metre population grid (worldpop.org). WorldPop produces modelled population estimates derived from census microdata, satellite imagery, and dasymetric redistribution. The 100 m resolution places population at the sub-block level, enabling precise trade area delineation.
Processing pipeline
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Spatial filter: Only grid cells within 150 km of at least one co-location cluster centroid are retained, reducing data volume by approximately 80% while preserving all cells relevant to catchment computation.
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H3 aggregation: Retained cells are assigned to their containing H3 resolution-7 hexagon and population values are summed. H3 resolution-7 cells have an average area of 5.16 km².
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Output: Population is aggregated to one record per H3 cell, giving each cell's coordinates, population, and country.
Countries covered
United States, Canada, Mexico, Great Britain, Germany, France, Netherlands, Austria, Portugal, Greece, Denmark, Iceland, and Poland — 13 countries as of the current pipeline version. This is the set with published per-capita spend multipliers. It is a subset of the platform's broader co-location footprint, which spans 24 countries as of the most recent full processing run (2026-08-06). See Retail co-location intelligence — overview for full country coverage.
Spend Data
Spend estimates are synthesised by applying annual per-capita expenditure multipliers by retail category to the population grid. The multipliers are proxies derived from national household expenditure surveys.
| Country | Grocery (p.a.) | Hardware (p.a.) | Wholesale (p.a.) | Currency |
|---|---|---|---|---|
| United States | $3,500 | $1,200 | $1,500 | USD |
| Canada | C$3,200 | C$1,100 | C$1,300 | CAD |
| Mexico | MX$18,000 | MX$3,500 | MX$2,500 | MXN |
| Great Britain | £2,800 | £850 | £900 | GBP |
| Germany | €2,900 | €950 | €1,000 | EUR |
| France | €3,100 | €900 | €1,000 | EUR |
| Netherlands | €2,700 | €1,000 | €1,100 | EUR |
| Austria | €3,000 | €950 | €1,000 | EUR |
| Portugal | €2,400 | €600 | €700 | EUR |
| Greece | €2,200 | €500 | €600 | EUR |
| Denmark | €3,500 | €1,200 | €1,100 | EUR |
| Iceland | €4,000 | €1,500 | €1,500 | EUR |
| Poland | PLN 8,000 | PLN 2,000 | PLN 2,500 | PLN |
Multipliers are expressed in local currency. Cross-country spend comparisons require foreign-exchange normalisation, which is not applied in the current pipeline. Rankings are most meaningful within a single country or within the eurozone.
Retail categories
- Grocery: Supermarkets, hypermarkets, food cooperatives, and food sections of general merchandise retailers.
- Hardware: Home improvement, building materials, and garden centres.
- Wholesale: Members-only warehouse clubs and cash-and-carry retailers.
Processing pipeline
Spend values are computed at the H3 resolution-7 level by multiplying each cell's aggregated population by the per-capita multipliers for its country, producing one record per H3 cell with population and estimated spend by category (grocery, hardware, wholesale) in local currency.
Catchment Aggregation
For each co-location cluster, primary and secondary catchment zones are defined by crow-flies distance rings (see: O-D Catchment Methodology). Population and spend for all H3 cells within each zone are summed to produce the cluster's trade area statistics. These aggregated values are the basis for cross-cluster competitive ranking.
Point-of-interest data
The retail anchor and secondary operator locations that form co-location cluster centroids are sourced from OpenStreetMap contributors under the Open Database Licence (ODbL). Point-of-interest data is distinct from the population and spend layers described above; it provides the geographic seed points from which catchment zones are measured. The full data-attribution statement covering all pipeline layers appears in Regional Markets intelligence system. [osm-odbl]
References
- Trade area — Wikipedia, accessed 2026-06-14
- WorldPop Global High Resolution Population Denominators Project — WorldPop, University of Southampton, accessed 2026-06-14
- H3: Uber's Hexagonal Hierarchical Spatial Index — H3 Geo, accessed 2026-06-14
Wikipedia content reproduced under CC BY-SA 4.0.
OpenStreetMap data © OpenStreetMap contributors, licensed under ODbL.
See also
- Distance-band methodology — primary and secondary demand zones
- catchment-ranking-methodology-v3
- Retail co-location methodology
OpenStreetMap data © OpenStreetMap contributors, licensed under ODbL.