Evaluate opportunities using consistent criteria relevant to your format, customers, and operating model.
Examine catchments, demographic patterns, employment, competitors, and complementary destinations where suitable data is available.
Identify coverage gaps and overlapping service areas to inform expansion and portfolio decisions.
Adjust the factors to see how their importance changes the illustrative result. A project-specific study uses agreed business criteria and suitable data.
Toggle factors on or off and set their importance. Lock a factor to hold its share while you adjust the rest. The weights always total 100%.
Try it: send a single factor to the top and watch the best-fit area jump. When one detail moves the answer that far, guessing gets expensive. That gap is what location analysis closes.
The two white squares are locations you already run. Weight Existing locations up and their shadow deepens. Existing-location overlap highlights shared geographic coverage. It does not, by itself, predict customer behaviour or sales transfer.
Each of these is a scope a team has asked for. Yours is agreed with you before any work starts.
Spatial analysis can identify factors relevant to performance. A sales forecast requires suitable business data and a separately scoped, validated model; a site score alone is not a revenue forecast.
Overlap identifies potential shared catchments. Actual sales transfer also depends on customer behaviour, store format, capacity, and other commercial factors.
Candidate addresses, existing locations, your target customer, and business priorities are a useful start. Customer and performance data can strengthen the analysis where available and appropriate.
