From ML to Construction: Top 10 Use Cases for Web Scraping 2024
As one of the most versatile categories of external data, web scraped datasets can be put to use by virtually anyone in business, technology, industry, finance and academia. In fact, many working in these sectors are yet to realize exactly how useful web scraping can be for their operations.
We’ve collected this top list to demonstrate just 10 of the most powerful use cases for web scraping today. See which of them is relevant to your projects and data needs, and discover example datasets which might cast light on how web scraping could be a game-changer for your 2024 strategy.
Publicly available datasets are leveraged to build highly detailed large language models. For example, code repositories are used to train GPT models for programming, and drug or medical datasets are utilized to build medication prediction models.
Large publicly available property datasets, including on and off-market homes from MLS sources, are aggregated by web scraping tools. This information can be used to predict market trends, and it is beneficial for real estate professionals and home improvement companies, such as solar businesses, who aim to reach homeowners.
Web scraping is essential for property valuation and investing as it allows the aggregation of large datasets of property listings and historical sale prices. This data can be analyzed to determine market trends, assess property values, and identify potential investment opportunities.
Web scraping solutions aggregatie large short-term rental datasets for STR market predictions. This can be used by funds looking to predict what areas to purchase properties in as well as application developers looking to build applications for smaller investors looking to gain insights into each individual market.
Web scraper and data aggregation tools collect information on current construction projects, which contractors work on each job site, and the material suppliers used. This also includes liens associated with specific job sites, which can be used to understand each city's current building projects for market predictions and risk management relating to liens.
Web scraping plays a crucial role in urban planning by collecting extensive datasets from various public sources about land use, zoning, population density, and transportation networks. This data points can be analyzed to predict urban growth, optimize transportation routes, and make informed decisions about the development and management of urban areas.
Web scraping can be used to gather data from commerce, consumer, and social media platforms to gain insights into consumer behavior, market trends, and public sentiment. This valuable information can be leveraged to identify promising alternative investment opportunities and make data-driven investment decisions.
By scraping open source sites, including local authority records, as well as commercial real estate sites, you can find out the quality of a build, its characteristics, and its intended use. This enables developers and construction companies to run background checks on properties they're interested in and evaluate whether or not a building is viable for intended use extremely efficiently.
Web scraping can be a powerful tool in enhancing consumer outreach and B2C marketing, by extracting vast quantities of data on consumer behavior, preferences, and purchasing habits from a variety of online sources. By analyzing this data, businesses can develop more targeted marketing campaigns, tailor interactions to individual customer preferences, and ultimately boost sales in B2C markets.
Web scraped data can be pivotal in training AI models in the healthcare industry. It can provide extensive datasets from various medical literature, patient forums, and health websites, which can be used to train AI algorithms for disease prediction, symptom analysis, and drug discovery.
As one of the most versatile categories of external data, web scraped datasets can be put to use by virtually anyone in business, technology, industry, finance and academia. In fact, many working in these sectors are yet to realize exactly how useful web scraping can be for their operations.
We’ve collected this top list to demonstrate just 10 of the most powerful use cases for web scraping today. See which of them is relevant to your projects and data needs, and discover example datasets which might cast light on how web scraping could be a game-changer for your 2024 strategy.
Publicly available datasets are leveraged to build highly detailed large language models. For example, code repositories are used to train GPT models for programming, and drug or medical datasets are utilized to build medication prediction models.
Large publicly available property datasets, including on and off-market homes from MLS sources, are aggregated by web scraping tools. This information can be used to predict market trends, and it is beneficial for real estate professionals and home improvement companies, such as solar businesses, who aim to reach homeowners.
Web scraping is essential for property valuation and investing as it allows the aggregation of large datasets of property listings and historical sale prices. This data can be analyzed to determine market trends, assess property values, and identify potential investment opportunities.
Web scraping solutions aggregatie large short-term rental datasets for STR market predictions. This can be used by funds looking to predict what areas to purchase properties in as well as application developers looking to build applications for smaller investors looking to gain insights into each individual market.
Web scraper and data aggregation tools collect information on current construction projects, which contractors work on each job site, and the material suppliers used. This also includes liens associated with specific job sites, which can be used to understand each city's current building projects for market predictions and risk management relating to liens.
Web scraping plays a crucial role in urban planning by collecting extensive datasets from various public sources about land use, zoning, population density, and transportation networks. This data points can be analyzed to predict urban growth, optimize transportation routes, and make informed decisions about the development and management of urban areas.
Web scraping can be used to gather data from commerce, consumer, and social media platforms to gain insights into consumer behavior, market trends, and public sentiment. This valuable information can be leveraged to identify promising alternative investment opportunities and make data-driven investment decisions.
By scraping open source sites, including local authority records, as well as commercial real estate sites, you can find out the quality of a build, its characteristics, and its intended use. This enables developers and construction companies to run background checks on properties they're interested in and evaluate whether or not a building is viable for intended use extremely efficiently.
Web scraping can be a powerful tool in enhancing consumer outreach and B2C marketing, by extracting vast quantities of data on consumer behavior, preferences, and purchasing habits from a variety of online sources. By analyzing this data, businesses can develop more targeted marketing campaigns, tailor interactions to individual customer preferences, and ultimately boost sales in B2C markets.
Web scraped data can be pivotal in training AI models in the healthcare industry. It can provide extensive datasets from various medical literature, patient forums, and health websites, which can be used to train AI algorithms for disease prediction, symptom analysis, and drug discovery.
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