Price prediction is the forecasting of prices based on historical data, market trends, competitors’ prices, social media influence, reviews, and economic tendencies. Besides being handy for adjusting prices in real-time, price prediction also allows for optimizing pricing strategy to get more profit and adjusting inventory level and supply chain. However, with the overwhelming amount of data today, it is impossible to do manually, and AI-based tools greatly help. They can also analyze trends and patterns, such as discount data that is hard for other apps to analyze. AI models only need relevant data to learn and work for you.

Here, web scraping comes into play as an irreplaceable means of getting data. On the other hand, huge websites like eBay implement strict anti-scraping policies today. On top of that, developers focus on delivering first-rate UX and UI, which is oriented toward humans and is hard for bots to deal with. So it is pretty much a challenge to hunt for data now. Still, it is possible, and in this article, we break down all the dos and don’ts regarding scraping product listings from e-commerce websites. 

Scraping strategy to get product listing data

Developing a web scraper? Or deciding on a particular tool? Then what tool to choose? To answer those questions and get data, you need to analyse the target website. 

How to scrape websites with a complex structure  

Website structure means the site’s organization – how pages are arranged, grouped, and linked. It may sound easy, but there are a lot of websites with complex structures that go beyond several related pages, and e-commerce sites are usually on the list. While there is no single criterion that determines whether a website is simple or complex, there are some features that have proved to be challenges for web scrapers. For example, there are four main types of structure; however, they are not mutually exclusive, and developers often mix elements of different structures to create a convenient and easy website for customers to navigate. For crawlers, though, multiple levels of navigation or subcategories make it harder to identify a path to scrape information. It means the necessity to use a recursive function to navigate through pages. There are also other hurdles: 

• Dynamic content loading 

E-commerce websites rely heavily on rendering dynamic content with JavaScript. The problem is that such content is generated directly in a browser and may not be in the initial page’s HTML. Basic scrapers only fetch a site’s HTML code, so they simply can’t grasp this data. On top of that, Single-Page Applications (SPAs) often modify content without reloading the page, making it harder to get data.

Solution: Use headless browsers. These special browsers don’t load graphic content and save sources, positively affecting scraping speed. They simulate a real browser environment, can execute JavaScript, and wait for content to load fully. You can also program a browser to perform specific actions to mimic user behavior. It is also helpful in terms of overcoming antibot measures. Selenium, Playwright, and Puppeteer are the most commonly used options with vast functionality. 

• Inconsistent HTML markup

Different pages may have different HTML structures. For example, one page would use an <h1> tag for titles, while the other implements a <div> tag. Some elements may only appear under a specific condition, like user login, or only for particular locations. Sometimes class names or element IDs are also generated dynamically. Because of this, developers face hardships when creating scrapers, as the same code with the same selectors won’t work for all pages. 

Solution: use a combination of selectors and fallback strategies so that if one selector doesn’t work, your scraper tries another instead of stopping. 

• Anti-scraping systems 

CAPTCHA, rate limiting, and IP blocking are among the most used strategies for dealing with scrapers. Websites monitor traffic patterns and block suspicious requests and addresses. If you use a scraper only, such obstacles may be a dead end. 

Solution: Use additional tools to mimic user behaviour, such as proxies. Rotating proxies will help you mask your scraping to a website; it will look like requests from different IPs and locations. Combine proxies with anti-detect browsers to modify your fingerprints and cookies -and it will help you stay incognito. 

• Unclear code

Minified or bundled JavaScript or CSS is harder to read and scrape. 

Solution: navigate to Developer Tools (Fn+F12 or Ctrl+Shift+I for Windows and Linux or Cmd+Option+I for macOS) > Elements. Inspect HTML code and find common classes or patterns you can target. You can simplify the process using AI tools. Then, try extracting data based on those patterns, not selectors. 

How to scrape websites with complex navigation 

Complex structure and complex navigation aren’t the same, though they often go together. Complex navigation has a lot of forms, for instance:

• Multilevel menus – e-commerce websites often have menus that require multiple clicks to reveal all the subcategories. 
• Infinite scrolling – pages load a new portion of content as the user scrolls down.
• Dynamic filters and sorting – a user applies a filter, and a website reloads the product listing in real time without changing the URL.

There are other forms, though in this article, we only pay attention to the ones you are likely to encounter on an e-commerce website. Fortunately, the solution to it exists: old, good headless browsers can manage complex navigation. Again, combined with proxies, they will further protect you from CAPTCHA and blocks while not requiring too much time to implement them. To better understand how to do it, visit our step-by-step tutorial on configuring Selenium in Python with proxies. 

Another tip is to regularly revise and update your scraping structure. Developers often update websites, add new product categories, use new elements, and implement anti-scraping mechanisms, so it is important to keep up with them and adjust your algorithms and tools as well. 

What language or tool to choose for web scraping? 

You have two ways: develop a web scraper or use a tool. Generally, building a scraper allows for more flexibility and customization, yet requires more human resources, time, and coding knowledge. If you opt for a tool, you usually experience some limits in customization; however, you need less time and resources. Also, ready pre-built tools are a way to go if you do not understand coding, as you can choose a no-code option. Your use case defines what is better for you. You also have to pay attention to different criteria while choosing both the tool and the language.

What to consider while choosing a scraping language:

• Ease of use – opt for languages with readable syntax, like Python, that simplify writing and updating code.
• Performance – go with languages that can handle multiple scraping tasks while consuming relatively less system resources. It is especially important if you deal with large datasets. 
• Compatibility – scraping complex websites often requires additional libraries, proxies, etc., to get data. Choose a language that offers powerful libraries and allows for easier implementation of third-party tools. Also, pay attention to the technologies your target website leverages (like JavaScript rendering) and opt for a language that goes well with them. 
• Documentation – the more detailed and up-to-date documentation and tutorials a language comes with, the better for you. An active community is also important. This way, you will have to invest less time to learn and build a scraper. If something goes wrong, you can easily find a solution or ask for advice or tips instead of developing one from scratch. 

For more details, please check out our dedicated blog post about choosing the best language for web scraping. 

What to consider while choosing a pre-built tool:

• Form – includes desktop apps, browser extensions, APIs, IDEs, SDKs, and scraping browsers. If you want a no-code option, usually it is better to go with an app, as other options require coding knowledge. 
• Features – pay attention to antibot bypass options, JavaScript rendering, and additional tools (like proxies) integration capabilities.
• Customization – as many websites do not fall into the most popular layout or structure scenarios, you should choose a flexible tool to handle not only a few popular e-commerce websites. 
• Price – plan your budget to see how much you are ready to invest in scraping tools. On the other hand, remember that good tools with numerous features and customization options may be costly. Many instruments offer you a trial plan or even a free probation period so you can test them and see which one fits you better. Free options may seem tempting to use; however, their possibilities are limited, and no one can guarantee privacy and safety of the data, as well as stable performance.
• Reliability – prioritise options with high uptime, success rate, and short response time. Look for a tool that can handle traffic spikes, too. 
• Support – e-commerce websites change and receive updates; you should look for tools that receive regular upgrades too. The support team should also be present and available, preferably 24/7, and have a short response time if you need help or unexpected issues arise. 
• Legal compliance – check whether your potential choice sticks to international regulations such as GDPR. Providers that use KYC (Know Your Customer) forms are decent candidates to work with. Read the provider’s Terms of Service, search for some reviews and mentions to be sure there were no involvements with illegal use cases, unethical scraping, or intellectual property rights infringement. However, sticking to a law is necessary, whether using a pre-built scraper or developing your tool. 

Instead of a final word 

He, who lives by the crystal ball, will eat shattered glass. Price prediction is not something to take lightly – only accurate, up-to-date information makes a difference and helps you build your business. Thus, you should consider every aspect, so your scraping projects succeed. DataImpulse is ready to have your back and provide you with legally derived IPs that will protect you from IP rate limits and bans and grant you access to data. Contact us at [email protected] or click the “Try now” button to start.