Case study
Naperville Retail Leakage
Civic & economic development
Where is local spending leaking, and which retailers should the city recruit back?
Retail leakage analytics revealed lost spending categories and gave leaders a targeted tenant recruitment roadmap.
Problem
What was at stake?
Naperville needed to quantify how much resident spending was flowing into neighboring Aurora and which categories were most affected.
MapZot.AI work
How the decision was modeled.
Outcome
What became clearer?
Cost of being wrong
$25M annual leakage
Unmeasured leakage weakens local tax revenue, business ecosystems, and the city's ability to recruit the right retailers.
The goal was not more data. The goal was a cleaner decision before capital, lease commitments, buildout time, and leadership attention were locked in.
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Automotive & car wash
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before investment
Which locations will perform before we invest?
Sales forecasting and high-performing site prioritization before capital deployment.
Emerging restaurants
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right location
We may only open one store. Can we forecast it accurately?
Precision site modeling for one high-confidence opening over 12–18 months.