Web Scraping: How to Use It and Become an Absolute Market Leader

Web scraping can be used for various purposes. It can be used to transfer data from one place to another in any situation. The basics of web scraping are easy to understand.

WHAT IS WEB SCRAPING?

Web scraping is a term for a range of methods for collecting data from the Internet.

Typically, this involves using third-party software or programs created by web developers that simulate human web surfing in order to collect specific data from various sites. Web scrapers are programs or software that handle this task.

HTML is used to write web pages, and it is primarily designed for human readability. Scraper bots extract the underlying HTML code. Therefore, when creating such programs, it is necessary to focus on logic and ensure that the bot collects only the required data.

Before using the collected data for commercial purposes, it must be analyzed. Therefore, before analysis, the extracted data should be saved in a suitable tabular format. For future use, data can be stored in CSV, Excel, JSON, or any database.

The web scraping process is not illegal. However, it can affect a site's ability to serve its users. As a result, some sites block web scraping bots. In some cases, solutions such as using proxy servers may be necessary.

DATA SCRAPING USE CASES

Let's consider the main use cases for web scraping.

COMPETITIVE MARKET RESEARCH

In a market of new ventures that are not reinventing the wheel, there are several competitors. They offer various services at different prices with different approaches. Keeping track of them can be tedious.

By using a scraper bot across all relevant URLs, a report on each competitor can be generated using a web scraper (their landing pages, prices, and features).

NEWS DATA OR FINANCIAL TREND MONITORING

Businesses can stay ahead of competitors by continuously monitoring news and financial trends. Analyzing news articles from thousands of news sources can be time-consuming, and many companies lack the resources to collect public data and financial trends.

With news scraping, news releases and updates can be automatically extracted from news sites and articles.

REAL ESTATE

Data helps brokerage firms and real estate agents make informed decisions. Real estate businesses can now scrape and maintain their listings worldwide.

Manual research of large volumes of data is challenging. Even if data is collected manually, analyzing disorganized information can lead to wasted time and money. With web scraping, real estate professionals can easily access available information, and their possibilities are limitless.

LEAD GENERATION

Lead generation can help companies attract new customers. Marketers start this process by sending messages to relevant potential clients. To fill the sales funnel, companies need to obtain new leads.

Purchasing lead lists from specialized companies can be expensive. Instead, web scraping can be used to collect publicly available data, such as webmaster emails or a list of real estate agents that are publicly accessible.

MACHINE LEARNING

Machine learning models require source data for improvement and development. Scraping tools can extract a significant amount of images, text, and data points in a short time.

Today's technological marvels, such as speech and image recognition, space travel, and driverless cars, are built on machine learning. To enhance the reliability and accuracy of machine learning models, web scraping must be used.

SOCIAL MEDIA SENTIMENT ANALYSIS

Although social media posts have a short shelf life, interesting trends can be identified when examined collectively.

While most social media platforms provide APIs that allow third-party programs to access their data, this is not always sufficient. In such cases, scraping these sites allows real-time access to data such as trending topics, phrases, sentiments, etc.

SEARCH ENGINE OPTIMIZATION

Planning a campaign from the start is crucial. Before spending money, you can obtain all important search terms and keywords using web scraping, allowing you to start optimizing immediately.

When it comes to SEO, it is sometimes better to invest in a few less common keywords than to overpay for those used by everyone.

HOW TO SCRAPE A WEB PAGE

Web scraping is simply a bot that navigates through various pages of a website and copies and pastes the needed information. When you run the code, it sends a request to the server and includes data in the response. The next step is to parse the received response and extract the desired data.

Here are the basic steps for extracting data using web scraping:

1. Identify the source from which data needs to be extracted.
2. Select the parameters to be extracted and exported.
3. Run the web scraping tool with the correct configuration to extract those parameters.
4. Save the data in an appropriate format (CSV, JSON, etc.).

Various open-source frameworks can be used to create a web scraper. Here is a short list:

• Scrapy — Scrapy is a collaborative open-source Python framework for extracting information from web pages. It is one of the most popular and advanced frameworks specifically designed for scraping.
• Puppeteer — Puppeteer is an open-source Node library developed and maintained by Google Chrome. Using the DevTools Protocol, you can control Chromium or Chrome. Puppeteer comes with a headless browser that can scrape web page content using HTML DOM selectors.
• Selenium — Selenium is a free open-source web testing framework. It automates browser functions (scrolling, clicks, etc.) to help obtain the needed information. Selenium's best feature is its support for various programming languages.
• Kimura — Kimura is another open-source web scraping framework for Ruby developers. It is designed to work with regular GET requests and headless browsers.
• BeautifulSoup — BeautifulSoup is a Python library for parsing HTML and XML files. It creates parse trees that can be used to quickly extract data. It converts HTML or XML documents into human-readable text and allows you to search for specific elements in the documents, making it easier to find the needed information.

On the other hand, web scraping is a complex task because websites are constantly changing.

For example, suppose you create a shiny new web scraper that picks only the information you need from the source of interest. The first time you run the script, it works flawlessly. However, when you run the same script later, you get a long and disappointing chain of tracebacks!

Since the Internet is constantly changing, you will almost certainly need to update your scripts regularly. Continuous integration can be used to run tests on the main script regularly, ensuring it doesn't break without your knowledge.

All of this involves purely technical issues that can take a significant amount of time and resources. There are a number of open-source tools for scraping data from the Internet, but each has its limitations. As a result, many companies have turned to automated scraping tools that greatly simplify the work.

WHY USE AN AUTOMATED SCRAPING TOOL

Anyone can create their own web scraper, just as anyone can create their own website.

However, the tools available for creating your own web scraper still require advanced programming skills. The amount of information expands as the number of things you want in your scraper increases.

To create web scrapers, you need to learn specific frameworks like BeautifulSoup or Scrapy. You also need to focus on applying the correct logic to extract the needed data. Sometimes you have to consult experts, which can be expensive.

Knowledge of proxy server management is also required. Another problem is that many sites block scraper bots. Therefore, creating your own web scraper can be time-consuming.

There are several web data collection platforms that provide a cost-effective solution for large-scale public web data collection, easy conversion of unstructured data into structured data, and excellent customer service while maintaining regulatory compliance and full transparency.

The best web scraping tools provide automatic and customized data flow on a single dashboard, regardless of the collection scale.

In some cases, you may not even need to collect data yourself; you can use pre-existing datasets.

Such datasets range from e-commerce trends and social media data to competitive intelligence and marketing research, aligning with your business needs. You can focus on your core business by gaining automated access to reliable data in your industry.

With the ability to access hard-to-reach public websites, data collection tools are part of industry-leading network technology. Using a web data collector, you can overcome obstacles related to web scraping.

The structure of popular sites can change constantly. Data collection tools adapt to changes in site structure and obtain clean data ready for analysis.

The algorithms of such tools clean, map, synthesize, analyze, and organize unstructured site data before output, resulting in relevant data ready for analysis.

CONCLUSION

Keep in mind that not everyone wants open access to their web server data. Always read the terms of service before scraping a website.

Whether you plan to use data scraping to grow your business or not, it is worth familiarizing yourself with this topic, as it will only become more relevant in the coming years.

Finally, writing your own data scraping program takes time and is not cost-effective. Therefore, you should always look for the simplest solution: use an automatic web scraper.