Vintage Clothes
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Business Contact
Erik Añvarea Cabrera
ConstructionContact Information
Business Description
Vintage Clothes is located in North Hollywood, Los Angeles, and was founded in 1999. At this location, Vintage Clothes employs approximately 4 people. This business is working in the following industry: Clothing stores. Annual sales for Vintage Clothes are around USD 566,200.
Employees: 4
Revenue: USD 566,200
Founded: 1999
Industry
Shopping » Clothing stores
Shopping » Clothing stores
Engaged in:
Retail sale of clothing, footwear and leather articles in specialized stores
Retail sale of clothing, footwear and leather articles in specialized stores
ISIC Codes
4771
NAICS Codes
448
4771
NAICS Codes
448
Questions & Answers
Q1
How big is Vintage Clothes?
Vintage Clothes generates approximately USD 566,200 in revenue annually, and employs around 4 people at this location.Q2
Where is Vintage Clothes located?
Vintage Clothes is located at 11114 Magnolia Blvd, North Hollywood, CA 91601.Q3
Are there other contacts associated with Vintage Clothes?
We have 1 additional contact(s) for Vintage Clothes. They include: Rinus Van Beek.Q4
What are the annual sales for Vintage Clothes?
Vintage Clothes has annual sales of approximately USD 566,200.Q5
How many people are employeed at Vintage Clothes?
Vintage Clothes has around 4 employees at this location.Similar Companies Nearby
Additional Businesses at this Address
11114 Magnolia Blvd, North Hollywood, CA 91601
Kathy's E Boutique
Business at this address
Business at this address
Businesses in Zip Code 91601
Businesses in 91601: 9,326
Population: 38,698
Categories
Shopping: 19%
Professional Services: 17%
Other: 64%
Price
Inexpensive: 51%
Moderate: 41%
Expensive: 5%
Very Expensive: 3%
Other: 0%
Area Codes
818: 89%
Other: 11%
Neighborhoods
North Hollywood: 91%
Other: 9%
Stats and Demographics for Zip Code 91601
Race
White: 37%
Hispanic or Latino: 34%
Black Or African American: 6%
Asian: 4%
American Indian Or Alaskan Native: 1%
Native Hawaiian & Other Pacific Islander: 0%
Other: 19%
Gender
Male: 51%
Female: 49%
Other: 0%