Data forBusinesses
Clean, correctable datasets for faster location decisions, fewer gaps, and lower total cost.The qualitative work required to build niche, decision-grade data is done in-house.
Customer proof
Data quality compounds over time.
“It is impressive how MapZot.AI tracks more than 50 Chick-fil-A locations in Chandler, Arizona, while Placer was tracking only around 30.”
Key signal
50+ vs. ~30 tracked locations
What changed
POI coverage accuracy
CEO
Emerging fast-casual chain
Industry-specific data views
Data views by industry.
Each industry view surfaces the most relevant datasets, imagery, use cases, and market signals for that category.
Find better restaurant locations with demand, traffic, and daypart data.
Understand where customers move, when demand peaks, which corridors convert, and how nearby competition shapes sales potential.
Related datasets
Use cases
Connected coverage
A unified data layer for location decisions.
Traffic, consumers, real estate, risk, and trade areas in one operating model.
Data layers
Understand each layer before you connect the stack.
Start with the layer you care about. Then see what it explains, why it matters, and how it supports a decision.
Current layer
POI Data
What it includes
Retail, restaurants, healthcare, logistics, services, entertainment, and public infrastructure.
Why it matters
Shows what is already in-market and what competes nearby.
How teams use it
Use it to benchmark competition, co-tenancy, and demand generators.
Browse the stack
Select any layer to see the business meaning behind the dataset, not just the label.
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Searchable data dictionary
Search datasets the way buyers think.
Turn a broad dataset catalog into a searchable buying surface. Users can filter by category, geography, or keyword and immediately see what is available.
Results
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Traffic Counts by State and City
Traffic count search coverage by state, city, corridor, road, trade area, and site with hourly, daily, weekly, monthly, AM/PM, and seasonal views where supported.
Primary use
Answer searches such as traffic counts in Texas, traffic counts in Dallas, hourly traffic in Phoenix, and AM/PM traffic near a proposed site.
Industries served
Search intents covered
POI coverage
Category and chain coverage built for search.
Browse category depth and representative chain coverage without forcing users through oversized static grids.
Business categories
Representative chain coverage
Grocery
Solution-to-data mapping
Connect each solution to its underlying datasets.
Replace bulky card walls with a compact, navigable view that is easier to scan and easier to parse.
Current solution
Site Selection / AccuSite
MapZot.AI vs. Legacy Site Selection
Why MapZot.AI outperforms legacy workflows.
Legacy site selection depends on fragmented vendors, static reports, and limited control. MapZot.AI connects the full stack into one decision-grade system, with the qualitative work required to build niche data done in-house.
Request a demo
Turn your dataset catalog into a structured conversion surface.
Show what data exists, who it serves, how it maps to solutions, and why it outperforms fragmented alternatives.