Retail Footprint, Reimagined by City.
How a global retail chain used World Data Lab's city-level consumer data to find its next 14 stores, and validate a 10-year expansion plan.
80+
Markets operated in
$5B+
Annual revenue
10K+
Stores worldwide
The challenge
Is the store network in the right cities?
The retailer needed to know whether its global store network matched the size of the local market and the spending power of consumers in each city, and how that picture would shift over the next 10 years. Without a consistent way to compare cities across very different markets, that question was impossible to answer with confidence.
The approach
Five steps from raw store data to an expansion shortlist
- 01
Standardize the geography
Every store was matched to WDL's city boundaries, creating one consistent definition of a city across all markets, so a city in the UK could be compared fairly with a city in Mexico or Korea.
86% / 92% / 38%
UK / Korea / Mexico cities matched
- 02
Correlate sales with consumer variables
City-level sales and transactions were tested against WDL's consumer metrics. Restaurant spending and the size of the target consumer group emerged as the strongest predictors of store performance.
0.75
correlation: restaurant spend to transactions
- 03
Map performance against potential
Plotting store sales against target-group population by city surfaced clear over-performers (often tourism-led) and under-performers relative to their size.
3 vs 1
over-performers vs. under-performers flagged
- 04
Go deep on a single city
An Edinburgh deep-dive confirmed the pattern at a granular level: wealthier, younger cities with more tourism and students consistently outperform the national average.
15.5
stores per 100K in Edinburgh vs. 8.4 UK avg
- 05
Classify cities for expansion
The traits of over-performing cities were used to flag markets with strong consumer fundamentals but too few stores, producing a ranked shortlist ready for the network planning team.
14 cities
high-potential for expansion across 2 markets
The outcome
The outcome
1 dataset
A single, consistent view of cities and consumers made every market instantly comparable, replacing market-by-market guesswork.
14 cities
Identified across two priority markets as ready for expansion within the next five years.
0.8 R²
Strength of the correlation found between target-group spending and store success within a city.
50%+
Potential increase in store count over 10 years in the retailer's top priority country.
Take it with you
Download the full case study
The complete PDF of Retail Footprint, Reimagined by City, ready to share with your team.
