Applied Intelligence Briefing
Edge Analytics / Applied Intelligence BriefingCase study
Defining new store catchments
JD Sports used HUQ mobility data to examine consumer flows, profile potential customer populations and strengthen the evaluation of new store locations in the UK and internationally.
- Client
- JD Sports
- Data
- HUQ mobility data
- Purpose
- Site evaluation
Observed consumer flows for evidence-led store development
The business challenge
What can observed customer flows reveal about a potential new store?
Context
With an extensive programme of store openings in the UK and internationally, JD Sports needed a clearer view of the customer opportunity surrounding potential locations, including catchment scale, demographic fit and overlap.
Requirement
Accurately predict likely customer flows across a catchment area, establish the size and profile the potential customer base and measure the likely impact on existing locations.
Method
- 01
Observed movement
Analysed HUQ mobility data to define detailed new store catchments based on observed consumer flows.
- 02
Catchment profiling
Measured 50% and 80% catchment thresholds and profiled their size and demographic characteristics.
- 03
Network overlap
Enabled better understanding of the competitive influence of surrounding retail venues and potential impacts on neighbouring stores.
Outputs & significance
Observed flows reveal catchments
50/80%
Accurate data-driven catchments
Provided consumer flows, proven to be highly correlated with actual customer catchments.
Target-customer profile
Identified catchments with strong concentrations of the demographics most relevant to the brand.
Overlap evidence
Quantified catchment overlap and fed the findings directly into site and store evaluation.
Significance
Catchment potential became measurable before a store opened
Combining observed consumer flows with demographics provided a granular, consistent basis for assessing and comparing potential store locations and understanding their impact on the existing network.