Investment Data Table
Analyze 6,720 laundromat opportunities in spreadsheet format
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| Opp Score ↓ | Location | State | ZIP | Rating | Reviews | Traffic | Market Position | Predicted Tier | Claimed | Verified | Area Indicators |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 76 | Roxbury | MA | 02119 | 3.4 | 191 | - | Struggling | - | ✗ | ✗ |
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| 76 | Augusta | GA | 2.7 | 51 | - | Struggling | - | ✗ | ✗ |
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| 76 | Columbia | MD | 3.2 | 151 | - | Struggling | - | ✗ | ✗ |
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| 76 | Pensacola | FL | 32504 | 3.0 | 61 | 31,500 | Struggling | - | ✗ | ✓ |
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| 76 | Indianapolis | IN | 2.8 | 70 | - | Struggling | - | ✗ | ✗ |
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| 76 | Salem | OR | 2.7 | 50 | - | Struggling | - | ✗ | ✗ |
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| 76 | Everett | MA | 2.9 | 90 | - | Struggling | - | ✗ | ✗ |
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| 76 | Valley Stream | NY | 11580 | 3.7 | 275 | 21,776 | Average | - | ✗ | ✓ |
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| 76 | Bakersfield | CA | 93306 | 3.1 | 130 | - | Struggling | - | ✗ | ✗ |
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| 76 | Orlando | FL | 3.0 | 109 | - | Struggling | - | ✗ | ✗ |
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| 76 | Shirley | NY | 11967 | 4.2 | 492 | 14,878 | Established | - | ✗ | ✗ |
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| 76 | Keene | NH | 3.4 | 188 | - | Struggling | - | ✗ | ✗ |
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| 76 | Cedar Rapids | IA | 3.4 | 188 | - | Struggling | - | ✗ | ✗ |
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| 76 | Waukesha | WI | 3.2 | 147 | - | Struggling | - | ✗ | ✗ |
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| 76 | Grand Prairie | TX | 75051.0 | 3.4 | 187 | - | Struggling | - | ✗ | ✗ |
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| 76 | Pittsburgh | PA | 3.1 | 127 | - | Struggling | - | ✗ | ✗ |
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| 76 | Grand Rapids | MI | 2.9 | 86 | - | Struggling | - | ✗ | ✗ |
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| 75 | Greeley | CO | 2.9 | 84 | - | Struggling | - | ✗ | ✗ |
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| 75 | Beaverton | OR | 3.2 | 144 | - | Struggling | - | ✗ | ✗ |
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| 75 | Seattle | WA | 3.0 | 104 | - | Struggling | - | ✗ | ✗ |
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| 75 | Portland | OR | 3.2 | 144 | - | Struggling | - | ✗ | ✗ |
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| 75 | Tempe | AZ | 3.4 | 182 | - | Struggling | - | ✗ | ✗ |
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| 75 | Columbia | SC | 29210 | 2.9 | 82 | - | Struggling | - | ✗ | ✗ |
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| 75 | Mount Pleasant | SC | 2.9 | 81 | - | Struggling | - | ✗ | ✗ |
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| 75 | Charleston | SC | 2.9 | 81 | - | Struggling | - | ✗ | ✗ |
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| 75 | Lewiston | ID | 3.5 | 209 | - | Average | - | ✗ | ✗ |
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| 75 | Tempe | AZ | 3.5 | 362 | - | Average | - | ✗ | ✗ |
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| 75 | Seattle | WA | 3.5 | 239 | - | Average | - | ✗ | ✗ |
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| 75 | Lafayette | IN | 3.5 | 280 | - | Average | - | ✗ | ✗ |
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| 75 | Crescent City | CA | 95531 | 3.5 | 201 | - | Average | - | ✗ | ✗ |
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| 75 | Broken Arrow | OK | 2.9 | 80 | - | Struggling | - | ✗ | ✗ |
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| 75 | Bartlesville | OK | 3.5 | 219 | - | Average | - | ✗ | ✗ |
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| 75 | Honolulu | HI | 3.5 | 377 | - | Average | - | ✗ | ✗ |
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| 75 | Columbia | MD | 3.5 | 240 | - | Average | - | ✗ | ✗ |
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| 75 | Shoreline | WA | 3.5 | 239 | - | Average | - | ✗ | ✗ |
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| 75 | St. Paul | MN | 3.5 | 202 | - | Average | - | ✗ | ✗ |
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| 75 | Minneapolis | MN | 3.5 | 202 | - | Average | - | ✗ | ✗ |
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| 75 | Lafayette | IN | 3.5 | 281 | - | Average | - | ✗ | ✗ |
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| 75 | Orem | UT | 3.5 | 222 | - | Average | - | ✗ | ✗ |
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| 75 | Mesa | AZ | 3.5 | 362 | - | Average | - | ✗ | ✗ |
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| 75 | Hot Springs | AR | 3.5 | 256 | - | Average | - | ✗ | ✗ |
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| 75 | Benton | AR | 3.5 | 214 | - | Average | - | ✗ | ✗ |
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| 75 | Kelso | WA | 98626.0 | 3.5 | 251 | - | Average | - | ✗ | ✗ |
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| 75 | Reading | PA | 3.3 | 157 | - | Struggling | - | ✗ | ✗ |
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| 75 | Indianapolis | IN | 3.4 | 176 | - | Struggling | - | ✗ | ✗ |
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| 75 | Federal Way | WA | 3.3 | 155 | - | Struggling | - | ✗ | ✗ |
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| 75 | Kansas City | MO | 2.8 | 55 | - | Struggling | - | ✗ | ✗ |
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| 75 | Gastonia | NC | 3.3 | 155 | - | Struggling | - | ✗ | ✗ |
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| 74 | Centennial | CO | 3.5 | 194 | - | Average | - | ✗ | ✗ |
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| 74 | St. Paul | MN | 2.9 | 74 | - | Struggling | - | ✗ | ✗ |
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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.