Examples of Realistic Web Scrapping Projects

Realistic web scraping projects

Web scraping projects have been used in both real-world and virtual world environments. They are known for being the perfect solution for data extraction. As this is the case with every technology, there are success and failure stories of realistic web scraping projects without proper knowledge of how they can be implemented.

On the other hand, many examples of successful implementation have allowed organizations to improve their performance in their target market.

Here are some examples of realistic web scraping projects that have used web scraping as a data extraction tool.

1. Price monitoring in Ecommerce

So, when you buy a product on e-commerce websites, there is a fixed price. The price can change anytime due to market forces and other reasons. So, you may want to know when is the best time to buy this product.

This is a crucial alert that the site owner has to give to their customers. This alert can be a small popup or a banner.

The price alert on e-commerce websites is really confusing, and since its price is fixed, it gives you little chance to buy the product when you don’t know about the discount. The solution is to scrape this page and put your own code in to notify users of an upcoming price change.

2. Conduct customer sentiment analysis from social media channels

Sociologists and market researchers are analyzing online social media channels to determine customer sentiment. This data can be used to make changes in a brand’s marketing strategy. For example, one of the brands in e-commerce already gathers this information by using the Facebook Page Insights API.

There is no other way than scraping this page to gather this data since there is no official API for it. You can use this API to get some information about a specified time range for any Facebook Page.

3. Generate sales leads from directories

There are many directories about products and services that you can find on the web. A sales lead generator is used to find the direct company information from these directories. Sales leads are actually your own customers, so you need accurate data from these websites.

If you use any of those directories, you have noticed that they take almost a week to update their information. This is a time bomb to webmasters and brand managers (that’s why they use scraping). So there is no other way than to make a program to scan these websites (maybe in a web crawler) to get the latest information.

4. Mass product listing for e-commerce sites

The e-commerce site owners can use this script to scrape thousands of product catalogs or prices of this site and create a product listing on their website in a short time with limited resources. This plays an important role in the website because the e-commerce site owner has to keep updating the product catalogs from all their suppliers.

For example, there are thousands of blogs on e-commerce sites with hundreds of new products each time. To prevent data loss and save time for your team, you can choose to scrape this blog to collect all the latest products and prices from that blog.

5. Collect real estate housing info

Real estate is one of the most important industries in the real market. The real estate information is also available online, but it is unstructured data, and there are many small brokers competing for the same information and listing these properties at all times.

The main goal of web scraping for this industry is to obtain information about current housing needs, which can be done by scraping the listings on different sites and gathering them into a single database.

6. Extract search results pages from search engines

The search results page is a valuable source for answering many questions, but most people don’t realize that these pages are available. Google and other search engines are adding new features daily, making the search results page very rich in content.

One of the best ways to get these search results is by scraping the search engine’s website. This is an important task if you want to improve your site or develop a new one.

Conclusion

There are so many other ways to extract data from websites for your future realistic web scraping projects. If you have your own ideas, feel free to contribute them to others.

Agents like Facebook or Twitter have started working with web scraping tools to get the data they need in their APIs (application programs interface). That means that they are now sharing their data with anyone who wants it. Twitter released a scraper tool on GitHub, which was used in this project.

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