Resources
Clear answers to the questions expansion, commercial, and real estate teams ask before they open, close, or relocate a store: which data to use, how to read it, and which mistakes to avoid.
Guide · Geomarketing
Geomarketing, also called location intelligence, is the use of location data to make business decisions: where to open, close, or relocate a store, who each location competes with, and where to market. It layers who lives in and passes through each area, which businesses are there, and how people move. For a retail chain, it is a way to compare options against the same criteria before investing.
8 min read
Guide · Site selection
To choose a new store location, compare every option against the same criteria: demand in its trade area, competition, access and visibility, costs, and cannibalization of your other stores. Then forecast its sales under several scenarios and validate your assumptions before you sign. The best site is not the one with the most people nearby, but the one that holds up best in that comparison.
8 min read
Guide · Trade area analysis
A store’s trade area, or catchment area, is the zone where most of its customers come from. It is best calculated with isochrones (drive-time or walk-time zones) rather than radius rings, and then refined with data on where visitors actually come from. Retail chains use it to forecast sales, measure cannibalization between their own stores, and plan local marketing.
8 min read
Guide · Expansion
Store cannibalization happens when a new store takes sales from another store in your own chain instead of attracting new customers. You estimate it before you open by looking at how much the trade areas overlap, how many visitors the stores share, and how much of the new store’s forecast would be incremental versus transferred from your existing locations. Some cannibalization is acceptable if total chain sales grow enough to pay back the investment.
8 min read
Guide · Predictive models
To forecast sales for a new store, you compare its location with similar existing stores, using variables from the surrounding area (population, competitors, visits) and from the store itself (format, size, services). Methods range from simple analogs to gravity models and machine learning. A good forecast always comes with its margin of error and from a model tested on stores it did not learn from.
8 min read
Guide · Comparison
Traditional market research, with surveys, interviews, or focus groups, explains why people buy and what they think of your brand. Location intelligence uses population, business, and mobility data to show where demand is, who competes in each area, and what changed, store by store. They are not mutually exclusive: research answers the why, and location intelligence answers the where and the how much.
7 min read
Guide · Retail strategy
Foot traffic is the number of visits a store or an area receives. Visit share is the percentage of an area’s visits that each store captures: yours and your competitors’. It is measured with aggregated, anonymized mobility data designed for comparisons and trends, and when read well it tells you who is winning visits, where, and when.
7 min read
Glossary
Our glossary explains, in a few words, the geomarketing and location intelligence terms we use in these guides.
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