Real Estate and Housing United States

About this dataset

Real Estate and Housing of the United States at ZIP code level.

Dataset contents

What's included

At the Census Block level, this dataset includes some of the following key features: Buildings • Number Of Bedrooms: 0, 1, 2, 3, 4, 5+ • Year Of Construction: 1939 or before, 1940-1949...... 2010-2013, 2014 or later • Home Occupation: Vacant, Occupied Price and Rental Data • Monthly Mortgage: Under $200, $200-$499...... $3000-$3999, $4000 or over • Monthly Rent: Under $100, $100-$249...... $1500-$2499, $2500 or over • Real-Estate Value: Under $25K, $25K-$50K...... $500K-$1M, Over $1M • Home Ownership: Rented, Owned Vehicles • Number Of Vehicles In Household: 1, 2...... 4, 5+ What insights can be gained from this Housing data of the United States? • Buildings: Marketers can use the number of bedrooms to target specific household sizes, tailoring campaigns for families with more members or individuals seeking different accommodations. The year of construction provides insights into the age and potential condition of homes, guiding marketers in promoting renovation or modernization services. The home occupation variable allows for targeted messaging based on the status of the property, such as addressing the needs of vacant properties versus occupied ones. • Price and Rental Data: These data variables provide crucial insights for marketers in the real estate and financial sectors. For example, businesses offering mortgage services can tailor their promotions based on the financial capacity of potential clients, while real estate agencies may focus on specific price ranges or ownership statuses to match their property listings with the preferences of their target audience. • Vehicles: Marketers can use the number of vehicles in a household to target automotive-related products and services. For instance, companies offering auto insurance or vehicle accessories may customize their campaigns based on the number of vehicles in a household, tailoring their offerings to the specific needs of potential customers.