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CASE STUDY
Modeled Site Selection Data to Uncover $2.7B Market Opportunity for Global Supermarket
Challenge
A global supermarket retailer lacked insight into its existing customer base, hampering its ability to identify new market opportunities.
The company needed help to analyze customer data to predict the viability of new locations and identify market sites for profitable expansion.
Approach
- Geocoded 7.5 million existing customer addresses to create a better understanding existing customer base and identify areas for potential targeted marketing campaigns
- Processed satellite and digital imagery using algorithms to classify commercial versus residential areas and estimate population and demographics at a block-by-block level
- Leveraged web-scraping to gather every listed apartment / house price in the target country together with their sizes to serve as a proxy for localized income
Results
I.
Identified locations to launch new stores forecasted to generate $2.7B in annual revenue
II.
Created dashboard summaries for each prospective location, shared with the Investment Committee and Board for capital allocation approval
III.
Developed 3-year store forecasts (updated over time) to identify operational weaknesses and coach store managers before earnings were materially at risk
Results
I.
Identified locations to launch new stores forecasted to generate $2.7B in annual revenue
II.
Created dashboard summaries for each prospective location, shared with the Investment Committee and Board for capital allocation approval
III.
Developed 3-year store forecasts (updated over time) to identify operational weaknesses and coach store managers before earnings were materially at risk
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