Investment Data Table
Analyze 9,861 laundromat opportunities in spreadsheet format
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Showing 50 of 9,861 results
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| Opp Score ↑ | Location | State | ZIP | Rating | Reviews | Traffic | Market Position | Predicted Tier | Claimed | Verified | Area Indicators |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 49 | Santa Barbara | CA | 93101.0 | 3.8 | 0 | - | Unproven | - | ✗ | ✗ |
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| 49 | Abilene | TX | 79601.0 | 3.8 | 0 | - | Unproven | - | ✗ | ✗ |
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| 49 | Chicago | IL | 60651 | 4.8 | 502 | - | Strong | - | ✗ | ✗ |
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| 49 | Chula Vista | CA | 91911 | 4.8 | 323 | - | Strong | - | ✗ | ✗ |
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| 49 | Arvin | CA | 93203 | 3.9 | 20 | - | Average | - | ✗ | ✗ |
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| 49 | Visalia | CA | 93277 | 4.8 | 410 | - | Strong | - | ✗ | ✗ |
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| 49 | Davenport | IA | 3.9 | 20 | - | Average | - | ✗ | ✗ |
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| 49 | Tucson | AZ | 4.8 | 232 | - | Strong | - | ✗ | ✗ |
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| 49 | Philadelphia | PA | 4.8 | 686 | - | Strong | - | ✗ | ✗ |
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| 49 | Boise | ID | 4.8 | 1,065 | - | Strong | - | ✗ | ✗ |
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| 49 | Boise | ID | 4.8 | 421 | - | Strong | - | ✗ | ✗ |
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| 49 | Tucson | AZ | 4.8 | 711 | - | Strong | - | ✗ | ✗ |
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| 49 | Tucson | AZ | 4.8 | 881 | - | Strong | - | ✗ | ✗ |
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| 49 | Tucson | AZ | 4.8 | 723 | - | Strong | - | ✗ | ✗ |
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| 49 | Tucson | AZ | 4.8 | 280 | - | Strong | - | ✗ | ✗ |
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| 49 | Mesa | AZ | 4.8 | 404 | - | Strong | - | ✗ | ✗ |
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| 49 | Dallas | TX | 75229 | 4.8 | 555 | - | Strong | - | ✗ | ✗ |
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| 49 | Allentown | PA | 4.8 | 922 | - | Strong | - | ✗ | ✗ |
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| 49 | Brooklyn | NY | 11223 | 4.5 | 40 | 10,086 | Average | - | ✗ | ✗ |
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| 49 | Mesa | AZ | 4.1 | 61 | - | Established | - | ✗ | ✗ |
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| 49 | Allentown | PA | 4.2 | 81 | - | Established | - | ✗ | ✗ |
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| 49 | Joliet | IL | 4.4 | 121 | - | Established | - | ✗ | ✗ |
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| 49 | Springfield | IL | 4.4 | 121 | - | Established | - | ✗ | ✗ |
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| 49 | Sumter | SC | 4.2 | 81 | - | Established | - | ✗ | ✗ |
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| 49 | Myrtle Beach | SC | 3.9 | 21 | - | Average | - | ✗ | ✗ |
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| 49 | San Francisco | CA | 4.1 | 61 | - | Established | - | ✗ | ✗ |
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| 49 | Oakland | CA | 4.0 | 41 | - | Average | - | ✗ | ✗ |
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| 49 | Queens | NY | 11004 | 4.4 | 71 | 19,518 | Established | - | ✗ | ✓ |
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| 49 | Waterbury | CT | 4.1 | 61 | - | Established | - | ✗ | ✗ |
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| 49 | Dallas | TX | 4.2 | 81 | - | Established | - | ✗ | ✗ |
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| 49 | Fort Worth | TX | 4.6 | 161 | - | Strong | - | ✗ | ✗ |
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| 49 | Jacksonville | FL | 4.7 | 181 | - | Strong | - | ✗ | ✗ |
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| 49 | Ruston | LA | 4.3 | 101 | - | Established | - | ✗ | ✗ |
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| 49 | Orlando | FL | 4.7 | 181 | - | Strong | - | ✗ | ✗ |
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| 49 | Springfield | MA | 4.1 | 61 | - | Established | - | ✗ | ✗ |
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| 49 | Springfield | MA | 4.0 | 41 | - | Average | - | ✗ | ✗ |
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| 49 | Springfield | MA | 4.0 | 41 | - | Average | - | ✗ | ✗ |
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| 49 | Atlanta | GA | 3.9 | 21 | - | Average | - | ✗ | ✗ |
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| 49 | Mount Vernon | NY | 3.9 | 21 | - | Average | - | ✗ | ✗ |
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| 49 | Honolulu | HI | 3.9 | 21 | - | Average | - | ✗ | ✗ |
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| 49 | Biloxi | MS | 4.1 | 61 | - | Established | - | ✗ | ✗ |
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| 49 | Minnetonka | MN | 4.6 | 161 | - | Strong | - | ✗ | ✗ |
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| 49 | Wheeling | WV | 4.3 | 101 | - | Established | - | ✗ | ✗ |
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| 49 | Elkins | WV | 4.3 | 101 | - | Established | - | ✗ | ✗ |
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| 49 | Haltom City | TX | 76117.0 | 3.7 | 81 | - | Average | - | ✗ | ✓ |
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| 49 | North Las Vegas | NV | 4.1 | 61 | - | Established | - | ✗ | ✗ |
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| 49 | Philadelphia | PA | 4.0 | 41 | - | Average | - | ✗ | ✗ |
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| 49 | Allentown | PA | 4.3 | 101 | - | Established | - | ✗ | ✗ |
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| 49 | Ithaca | NY | 14850 | 4.2 | 33 | 14,834 | Average | - | ✗ | ✓ |
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| 49 | Elgin | IL | 4.0 | 42 | - | Average | - | ✗ | ✗ |
|
Understanding the Data
Opportunity Score
Higher scores indicate better acquisition potential based on ratings, claim status, traffic, and market positioning.
Market Position
Calculated from review count and rating. "Struggling" businesses have many reviews but low ratings.
Area Indicators
P=Pawnbrokers, C=Check Cashing, D=Dollar Stores, G=Gas Stations. Higher counts indicate working-class demographics.
Traffic (AADT)
Annual Average Daily Traffic on nearby roads. Higher traffic = better visibility and walk-in potential.