View some of our work and case studies for clients. We will work to deliver that strategy by building out your existing campaigns, or establishing accounts at new networks. It’s important to us that you own the accounts, and that you have a relationship with the network owners.
Best Real Estate Datasets
What is Real Estate Data?
Real Estate Data refers to the housing market data. It provides the “Real Property” data information such as land, building, etc. It includes four types of data as Residential real estate data, Commercial real estate data, industrial real estate data, and land data.
It is used by many investors, who invest in Real Estate for making investment decisions. All persons who are involved with real estate, need the real estate data to identify market trends. So they can sell and buy real estate properties at the best price. The data collected from the commercial records, tax records, house-flipping reports, and other multiple listing services.
For property selling and buying activities, the person must have sufficient knowledge of market trends, so he/she sells or buys at a reasonable price. We gather a huge amount of Real Estate Data with enormous speed and provide you accurate data in your required format. You can buy a Real Estate database at a reasonable price from our data store. Web Scrape helps you to gather the Real Estate APIs and datasets and databases.
Subcategories of Real Estate Data:
- Construction Project Leads Data
- Coworking Data
- Flexible Workplace Data
- Mortgage Data
- Property Data
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Best Real Estate Data Providers
What are the Most Common Types of Real Estate Data?
Construction Project Leads Data
Construction Project Leads Data is the data that includes the information of all infrastructure and construction with the key aspects such as budget, timeliness, and production stages. These data are used by Contractors, Subcontractors, and product manufacturers to evaluate their current capabilities.
Coworking Data is the set of information about coworking places in certain areas as well as price and performance reviews of coworking sites. With the help of these data, the development process becomes easy. It is useful for predictive analysis, monitoring work performance, and also helps you to choose the best location.
Flexible Workplace Data
Flexible Workplace Data is the data of several types of workspaces/ shared office space data. It provides deep insight into the creative-designed offices to the firms. With the help of this data, all types of employees monitor and measure the performance of the workplace.
Mortgage Data refers to that type of property data, which is refinanced by the banks and lending institutions. It is used by the bank, lenders, and real estate business to analyze the creditworthiness of an individual before granting a loan. It includes the information of purchase value, loan amount, lender, interest rate, interest date, owner, borrower, lender, and other aspects.
Property Data provides the information of landed buildings or landed properties in the real estate market. It includes the property cost, local prize, recent capital growth, place of property, growth rate, etc. This data helps sellers, buyers, investors to decide on buying, renting, leasing, and investing.
Top Uses of Real Estate Data:
Example of the Most Common Use Cases for Real Estate Data
Real Estate Data is important to all those people who are involved in real estate. Real estate marketers need this data for future predictions and also for making decisions on construction. With this accurate data, real estate investors can decide on investing in the real estate sector.
Residential people, buyers, investors, sellers, renters need this data to determine the area. Governments also use this data to determine the number of land and assets, so they use that property for the public service also. Real Estate Data is also used in real-time monitoring of properties and assets so the future market price and future development decision can be taken.
It provides transparency in the business process, therefore utilizing the real estate data process becomes easy and all related people and industries, and others can make new strategies for future Real Estate valuation.
Examples of Real Estate Data Attributes
Typical Real Estate Data Attributes:
Real Estate Data categorized into three attributes – the first is Land and ownership data, the second is real estate listing data, and the third is real estate demographic data. Land and Ownership Data is the physical characteristics of real estate. In this data there is geolocation data, site or building coverage data, plot density, site area, local authority, tenure, flood-risk, property type, financing, and taxes are included.
Real Estate Market Data is giving better ideas to the property agents, buyers, investors to understand market trends. In this data price, price asked, the price paid, rent asking, condition of properties, days on market, local housing allowances, public housing, rental listing, sales listing, sales history & transactions, yield, gross yield data, and net yield data included.
Real Estate demographic data is focused on seller characteristics and property locations. In this data median income of the area, unemployment rent in that area, homelessness level, education level, crime rates in the area, the median age of inhabitants, population size and density in the surrounding area of the property, in-building mobility, and local amenities are included.
Similar Data Types
- Environmental Data
- B2B Data
- Energy Data
- Geospatial Data
- Commerce Data
Most Common Use Cases For Real Estate Data:
- Property Valuation
- Real Estate Analytics
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