The data boom in the real estate market has transformed the industry. Potential investment opportunities, market forecasting, competition monitoring, online engagement, brand management, deals, accurate appraisals, etc. are managed through data. The amount of data being generated in the industry and the way it is revolutionizing the industry, methods to acquire data need serious thought. 

Extracting relevant data is a challenge the industry faces, and the solution is web scraping APIs. The advanced technology helps extract data from websites using bots known as APIs. Every real estate business need data collection services to stay competitive and make data-backed informed decisions. 

Key benefits of web scraping to the real estate industry 

Web scraping solutions empower the industry by giving access to huge volumes of data, both traditional and non-traditional, like location, amenities, appraisals, crime rate, shopping areas, valuation, etc. 

Some of the benefits include the following:

• Real-time data collection - Real estate market fluctuates at a fast pace; valuations change, location preferences change, new amenities like a shopping mall, schools, etc. come up in the area, crime rates also affect the property valuation and buyer preference, etc. In such a scenario, a web scraping API or software can give you updated and accurate information to improve revenue and grow profitably. 
• Use of updated strategic data - Easy access to all relevant, current, and real-time information helps build property intelligence and find better and more effective solutions. A good idea of the current market, buyers’ preferences, etc. helps you develop improved selling strategies and engage better with prospects. 
• Effective home buyer sentiment analysis - Data on home buyer reviews, requirements, reasons for moving out, etc. helps homeowners and real estate agents to better understand current customer requirements and expectations. They can use it to optimize marketing and advertisement strategies accordingly.
• Forecast the real estate market - Web scraping helps in forecasting economic direction, important in the real estate industry. The historical and current intelligence on properties provides data-backed predictions on market trends, pricing, etc. that helps realtors to adjust pricing and strategize better. 
• Engage better online - You engage better with buyers through online platforms with effective content in the form of blogs, videos, social media postings, etc. Information related to the trending topics, what buyers want to read, what postings get clicked more etc. helps you develop relevant content. It makes simpler to tap leads and convert.
• Competition monitoring - Knowing the pulse of your competitors by gathering data on their activities, strategies, promotional activities, etc. helps you frame better strategies and stay ahead in the competition.
• Helps you maintain a good brand image - Bad reviews over social media and other online platforms can damage your brand image and hit your business hard. The critical review could be a deliberate or genuine experience of your buyers. Regular web scraping helps you scrape through all such data and take action before any damage is done. 

Techniques for Web Scraping

Web scraping is a must for the real estate industry, but one needs to use the right techniques for the best results. These are some techniques used for extracting data from online sources.

1. Manual scraping

Manual scraping is the simplest form of web scraping where the data is manually copied and pasted into a spreadsheet or text file. Though this is a time and labor-intensive process, but often may be the only solution as sometimes human intervention is required despite the best of web scraping technology. Especially when websites set up blockades, machine automation cannot be enabled. The process is simple to learn and allows for manual monitoring of irrelevant and erroneous records. But slow speed can prove detrimental to your business and may not be cost-effective. But again, since the process is slow, the chances of getting blocked by the websites are low. 

2. DOM parsing

A Document Object Model (DOM) parser creates an internal structure in memory, enabling the client applications to extract information from the original XML documents. This programming API for XML documents is simple to use and supports both read and write. The contents of the web page are parsed into a DOM tree. Then the information can be retrieved from the tree by embedding a program into the web browser. Data can be accessed randomly that continues to stay in the memory. However, it may create an issue concerning memory space because the entire XML document needs to be loaded into memory. It may not work with very large XML documents. 

3. Recognizing semantic annotation

This technique helps in data extraction, recognizing the context of the need of the user. Extracting data from a huge number of unstructured documents is a challenge. Searches based on keywords without understanding the actual requirement of the user are not fruitful. Here, semantic annotation strategy helps retrieve and extract relevant information. Semantic search denotes search of meaning in contrast to lexical search, where search engines look for literal matches. Most web pages have semantic annotations or metadata that can be retrieved. Web scrappers use the annotations in the semantic layer before scraping the data.

4. HTML code review

This is done with JavaScript, allowing you to target linear or nested HTML pages to collect text and other resources. However, for efficient HTML parsing, you will require sockets and pre-made codes that will let you extract data from dynamic and static pages. The quick and robust process is used for text extraction, screen scraping, etc.  

5. Other techniques

There are several other techniques available for effective data extraction like Text Pattern Matching. It involves the use of the UNIX grep command and is used with popular programming languages like Perl or Python; Vertical Aggregation which runs on cloud and bots, is used to extract high-quality data; Google Sheets scraping is another popular web scraper where, with the help of IMPORT XML, you may scrape as much data as you need. However, this tool has its limitations.

Conclusion 

The real estate industry highly depending on data needs ways and means to extract relevant data from multiple sources. A huge amount of data surrounds the market but extracting the relevant data from credible sources in an appropriate format is a challenge. This is where the role of web scraping comes in which has revolutionized the real estate industry. The dynamic real estate data gets constantly updated through web scraping APIs. 

There are various web scraping tools available, but they require automation and technical expertise. To survive the competition, leveraging data and adopting technology gets mandatory. Outsourcing the services to scraping service providers is a good idea as they are well-equipped for handling codes and website layouts.

Author

Snehal Joshi spearheads the business process management vertical at Hitech BPO, an integrated data and digital solutions company. Over the last 20 years, he has successfully built and managed a diverse portfolio spanning more than 40 solutions across data processing management, research and analysis and image intelligence. Snehal drives innovation and digitalization across functions, empowering organizations to unlock and unleash the hidden potential of their data.