Critical Scraping Challenges and Their Solutions

As we discovered, extracting data from websites is a complex process that includes various challenges faced gathering the data. Due to website owners and admins aiming to keep their data maximum untouchable, it requires using specific approaches to overcome the obstacles. So, let’s discover what can violate typical web parsing and find efficient solutions for each issue. 

Widespread Difficulties of Data Mining

Scraping is a creative process, and using standardized methods is usually inefficient. Each website requires getting the specific data, so each case provides unique challenges that are solved with the help of experience and a dedicated approach. 

Human Perception 

The numerous disputes about the admissibility of the scraping are spreading nowadays. The ethical and legal aspects have always been controversial – those with a negative attitude doubt using the data safely and demand blocking the websites providing it. As a result, the strict legality conditions make each site decide if the data can be gathered from it by others. And this crucial issue determines the others listed below. 

Parsing Bot Block 

Web developers can prudently set up limitations for data mining by inserting “robot.txt” while coding. The primary problem is that even if a site’s admin agrees to give access, it will require code changing, that’s impossible without proficient programming knowledge. Also, the invisible links, so-called “bot traps,” are used to detect the machine gathering the data. 

Terms & Conditions 

Sometimes, to extract the information from the site, the registration and accepting “Terms & Conditions,” in which the parsing prohibition is indicated. However, the rules may include the limitations for specific data types, and taking them doesn’t violate the site using laws. 

IP Address Block   

If the site acquires too many requests from one address, it will regard it as “harmful” and establish a permanent access block. Moreover, in request abundance, the site may provide false information that may negatively affect the results. For instance, if data extraction is provided for the actual prices of the company, the site may give you its supplier’s values.  

Complicated Site Structure and Dynamic Design

Most web pages are based on HTML, and the structure of one web page can be very different from the other. Therefore, when you need to parse several websites, you must create several scraping bots for each (which may cause financial difficulties). Also, the “smart content” implemented on various modern sites is provided expressly for human interaction, making the extraction of information impossible.


The most popular method to avoid the access of scraping bots is placing a picture task that helps distinguish a machine from a person. However, modern automated parsers can overcome this issue and gather data without problems. 

Low Page Loading Speed 

Too many requests may decrease loading the web page time, and the data mining process may stop. As a result, the scrapers don’t provide the results in time, and data gathering becomes uninformative. 

Different Data Formats 

Data analytics is based on gathering files, and some may be saved in different formats such as .pdf or .docx. Therefore,  grouping and segmenting the information and its export to Google require a more complicated approach.  

Solutions for the Scraping Issues 

Overall, the growing popularity of web scraping led to the appearance of efficient solutions to provide convenient data gathering and extraction. The essential tips to follow are: 

  1. Maintain CSS properties with the commands “visibility: hidden” to avoid traps for parsing bots. 
  2. Use a headless browser to load only the necessary parts of HTML code, not the entire site. 
  3. Schedule data scraping sessions so they do not start during peak traffic on websites (using random intervals for requests is also efficient).
  4. Don’t gather personal information to follow the GDPR rules and do the parsing legally. 
  5. Use proxy servers and send requests through different IP addresses to avoid blocking. 
  6. Detect the site changes and maintains the bot for unstoppable work even if the page has changed its structure. 
  7. Set up “User-Agent” to avoid blocking for the parser. 
  8. Use captcha solving methods (optical recognition or sending text requests to people) to pass the picture tests. 

The listed tips are necessary for convenient and resultative web scraping, and modern parsers use these obstacle-overcoming rules. 


Overall, parsing has challenges like each modern web procedure, and each is guaranteed to meet during the process. Therefore, it’s necessary to implement modern solutions to provide a comfortable and resultative information gathering.