What is Real Estate Data?
Real estate data is information about properties, their purpose, their value, and their ownership. Its attributes include real estate data include property listings, sales records, rental prices, property characteristics, and market trends. It’s used by investors and property developers to decide where to invest most wisely, based on current real estate values.
Data Specialist
July 22, 2024
Datarade Marketplace
Best Real Estate Data Databases & Datasets
Here is Datarade's curated selection of top Real Estate Data. These trusted databases and datasets offer high-quality, up-to-date information.
Promoted
by Immobiliare.it Insights
Available for 2 countries
35M records
9 years of historical data
90% match rate
Available Pricing:
One-off purchase
Monthly License
Yearly License
Usage-based
Free sample preview
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Promoted
4.9(7)
by APISCRAPY
Available for 62 countries
100M Real Estate Listing Data from 100+ Sites
5 years of historical data
100% Delivery On Time
Available Pricing:
Monthly License
Yearly License
Usage-based
Free sample preview
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4.8(4)
by CrawlBee
Available for 1 countries
100M records
1 days of historical data
98% Accuracy
Available Pricing:
One-off purchase
Monthly License
Yearly License
Usage-based
Free sample preview
revenue share
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5.0(17)
by SafeGraph
Available for 3 countries
11M POI (Points of Interest)
3 years of historical data
Starts at
$0.10 / purchase
Free sample preview
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by BatchService
Available for 1 countries
258M Phone Numbers
3 years of historical data
100% Fill Rate
Starts at
$0.01 / API Call
Free sample preview
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4.9(7)
by APISCRAPY
Available for 62 countries
50M Real Estate Records
10 years of historical data
100% Customizable
Starts at
$25 / month
Free sample preview
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by Webautomation
Available for 1 countries
Pricing available upon request
Free sample preview
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by BIGDBM
Available for 1 countries
30M Records
Pricing available upon request
Free sample preview
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4.9(2)
by Factori
Available for 1 countries
340 + Million Profiles
1 years of historical data
97% fill rate
Starts at
$360,000 / year
Free sample preview
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5.0(1)
by Plugindata
Available for 240 countries
14M Company Data
4 years of historical data
98% Quality Rate
Starts at
€0.24 / record
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Top Real Estate Data Providers & Companies
When choosing real estate data providers, consider factors like data accuracy, coverage area, data sources, frequency of updates, data formats, pricing, customer support, integration options, data security, and reputation in the industry.
Immobiliare.it Insights is a proptech dedicated to the analysis and processing of Italian and foreign real estate market data. We offer highly detailed real ...
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For marketers with demanding audience and data-driven project requirements, Andrews Wharton is the proven direct response solutions provider with a long-stan...
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We aim to become the most reliable source of Geospatial data so companies can build profitable strategies to enhance operational efficiency. At the core of o...
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Popular Use Cases
Real Estate Data plays a pivotal role in various business applications, offering valuable insights and opportunities across industries.
Property ValuationReal Estate AnalyticsReal Estate InvestmentProperty ManagersUrban PlanningProperty InvestmentReal Estate IntelligenceReal Estate Insights
Real Estate Data Explained
Categories of Real Estate Data
Real estate data can be divided into the following four categories:
Residential real estate data
Data about areas that are designed for people to live in e.g. family homes, apartments, flats, lofts
Commercial real estate data
Data about properties which are designed to generate income for the owner e.g. shopping centres, hotels, offices
Industrial real estate data
Data about areas and buildings designed for company use, to research, design, produce and distribute physical goods e.g. warehouses, production facilities, logistical centres, laboratories
Land data
Data about ranches, farms and vacant land. Real estate investors buy vacant land with the view of the land being used for residential purposes in the future, which multiplies the value of the estate significantly.
So, whichever type of real estate you’re interested in, there’s data out there for you. Now let’s take a closer look at the attributes of this real estate data.
Attributes of real estate data
There are a number of factors which real estate data providers consider when compiling a land and ownership database. These include:
Geolocation data – Where the property is situated. The information can be presented in the form of an address, or through coordinates.
Site or building coverage – The percentage of the lot area that is covered by the building area, which includes the total horizontal area when viewed in plan.
Plot density – A calculation which expresses the number of dwelling units per acre based on the gross lot area, factoring in thoroughfares, public parks or other public areas. City authorities often refer to plot density to express the minimum and maximum amount of land which is to be devoted to residential purposes.
Site area – The floor area ratio of the site in question. It’s calculated by dividing the total gross building floor area (square feet) by the land area of the lot. In cases where a project site encompasses several buildings on several lots, the floor area ratio may be combined and averaged over the entire project site.
Local authority – The local authority is the city or county in which the property is situated. Some land or assets are owned by federal, state, or local governments as well.
Tenure – Land tenure is the legal term for ‘ownership’: where land is owned by an individual, who is said to ‘hold’ the land. It determines who can use land, for how long, and under what conditions. Tenure can be based both on official laws and policies or on more informal arrangements.
Flood risk – Some properties are at greater risk than others of flooding. When a property is located in a confirmed floodplain, it can have a serious effect on the cost of property ownership, so it’s an important part of land and ownership data.
Property type – The property type refers to whether the property is intended to be used as a house, apartment, industrial facility, or for commercial real estate.
Financing – Property financing refers to the means used by the buyer when the property was purchased, including whether there is an outstanding mortgage.
Taxes – Property taxes are paid on property owned by an individual or corporation depending on the property’s value. It is calculated by the local government where the property is located and paid by the owner of the property.
Use Cases
As we’ve seen, real estate data can be an asset whether you’re buying, selling or investing in property and land. It’s an especially versatile data type.
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Here’s some of the use cases which can inform your decisions and optimize your spending:
1. Predictive analytics
In real estate, companies can analyze the total condition of the building, its age, how solid it is, all reconstructions that were made before, and information about the current owner to get a correct property estimation. As reported by McKinsey & Company, machine learning was recently used to forecast the three-year rent per square foot for multifamily buildings in Seattle with an accuracy rate of over 90%.
2. Increased industry transparency
Real estate data provides transparency in business processes. As a result, real estate companies can make important decisions faster because they are provided with accurate, current and objective data.
3. Real time monitoring and communication
Agents can contact potential buyers at the right time when people are going to buy or sell real property. In turn, agents can also monitor trends and actual prices because real estate data provides them with the opportunity to offer clients more profitable variants.
4. Customised strategization
Real estate data tells real estate insurance companies what type of insurance people in their region need in advance, meaning they can then create custom plans.
These use cases aside, real estate data, like all data types, comes with its own set of challenges. Here is what you should look out for when investing in a third-party dataset.
- Does the provider have good reviews?
- Does the dataset cover the locations you’re interested in?
- Can the data be integrated readily into your company and software?
- Is the data priced in a way that’s feasible for your company?
Real Estate Data Pricing
Real estate data providers provide data either through software packages or bulk downloads. In addition, there are subscriptions or pay as you go plans. These costs vary depending on the breadth and depth of data requested. Real estate data that has been aggregated, cleaned, and updated frequently is widely available on data marketplaces like Datarade, but such data products can carry a higher ticket price. Like any commercial product, with real estate datasets, some options are more cost effective or higher quality than others. The right data for you depends on your data budget and intended use case.
Frequently Asked Questions
Where can I buy Real Estate Data?
Data providers and vendors listed on Datarade sell Real Estate Data products and samples. Popular Real Estate Data products and datasets available on our platform are , , and CrawlBee | Realtor.com Dataset | Property Listings | MLS Data | Real Estate Data | Residential Data | Realtime Real Estate Market Data by CrawlBee.
How can I get Real Estate Data?
You can get Real Estate Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Real Estate Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time Real Estate Data APIs, feeds and streams to download the most up-to-date intelligence.
What are similar data types to Real Estate Data?
Real Estate Data is similar to Telecom Data, Environmental Data, Weather Data, B2B Data, and AI Training Data. These data categories are commonly used for Property Valuation and Real Estate Analytics.
What are the most common use cases for Real Estate Data?
The top use cases for Real Estate Data are Property Valuation, Real Estate Analytics, and Real Estate Investment.