Web scraping requires reliable access to large amounts of public web data.

However, most websites implement protection mechanisms that block automated traffic when too many requests originate from the same IP address.

If hundreds or thousands of requests come from the 

, platforms quickly identify it as automated traffic and block access.

This is where proxies become essential and why many developers and data teams use 

 there is actually no specific proxy type designed exclusively for scraping. Instead, scrapers typically rely on:

Each option offers different trade-offs in terms of reliability, speed, and detection resistance.

 is commonly used in the web scraping community, but it does not refer to a specific type of proxy.

proxies used as intermediaries between a scraper and the target website

. These proxies route requests through different IP addresses rather than sending all traffic from a single source.

By distributing requests across multiple IPs, scrapers can:

In practice, the proxies used for scraping are typically 

residential, mobile, or datacenter proxies

, depending on the reliability, scale, and level of anonymity required for the data collection task.

Why Residential Proxies Work Best for Scraping

Because these IPs belong to real households, they appear like 

This makes residential proxies particularly effective for:

Key Scraping Techniques to Avoid Detection

Each request uses a different IP address.

This prevents platforms from detecting request patterns from a single source.

Sending too many requests too quickly triggers anti-bot systems.

Scrapers should rotate browser fingerprints to mimic real devices.

Many platforms return different data depending on location.

Proxies allow scrapers to access content from:

With proxy rotation enabled, thousands of requests can be distributed across a 

Common Use Cases for Scraping With Proxies

E-commerce companies monitor competitor prices across marketplaces.

Businesses collect product listings, reviews, and availability data.

Marketing teams verify ads appear correctly across locations.

Analysts track shipment data, logistics dashboards, and inventory updates.

Best Practices for Stable Scraping Infrastructure

To maintain long-term scraping reliability:

Combining good scraping architecture with reliable proxies dramatically increases data collection success.

Large-scale web scraping is difficult without proper infrastructure.

residential proxies, IP rotation, and intelligent request management

, developers and data teams can collect data efficiently while avoiding common anti-bot protections.

For organizations that rely on external web data, proxies are an essential component of modern scraping workflows.

Proxyrack

Company

How to Scrape Websites at Scale Without Getting Blocked (Using Residential Proxies)

How to Scrape Websites at Scale Without Getting Blocked

Global eCommerce Data Collection

A Comprehensive Guide

For online retailers, tailoring their offerings to suit the needs and trends of consumers is a critical practice. From elevating the customer experience and encouraging them to make online purchases to understanding users' habits and refining product offerings based on users' locations, the benefits of collecting global eCommerce data can be lucrative.

We've put this guide together to help you gain insights into how people shop online and get a competitive advantage on online businesses in the same space.

Here, you'll find everything you need to know about collecting eCommerce data, including key considerations before you start finding data, how to collect eCommerce data, and how 

 can make the whole process much more straightforward.

Global eCommerce data refers to information and statistics gathered from eCommerce businesses, i.e. online stores that buy and sell goods and services to online customers. 

eCommerce data covers a wide range of metrics and insights from the online retail sector, all of which businesses and online retailers can leverage to understand the trends, behaviors, and performance of the global eCommerce market.

What are the main elements of global eCommerce data?

A company’s sales revenue is the total monetary value of global goods and services sold through online platforms. Tracking sales revenue helps to assess the overall size and growth of the eCommerce market.

Tracking this metric will give you an insight into the number of online transactions, including purchases, payments, and other financial activities conducted through eCommerce platforms, like competitor websites.

Providing information on the market share held by eCommerce companies and platforms, this metric indicates which competitors have relative dominance or competitiveness in the global market.

Understanding key demographics, like the age, gender, and location of online shoppers, can help your business tailor its marketing strategies and product offerings. If you want to expand globally, tracking international eCommerce transactions and cross-border shopping trends is crucial.

5. Conversion rates and average order value (AOV)

This data shows the percentage of website visitors who complete a desired action, usually making a purchase, and can help you evaluate the effectiveness of your eCommerce website.

The AOV represents the average amount customers spend in a single online transaction. This data can help your business gauge its revenue potential and profitability.

6. Shipping information and payment methods

Using this data, you can find shipping times, costs, and delivery options and how they can impact customer satisfaction and influence buying decisions.

Gaining an insight into how people like to pay for their goods or services can help you make changes that improve the customer experience.

Understanding how many people use mobile devices for online shopping, including mobile app usage and mobile-friendly website design, can help you identify areas for development and track how customers use your website. 

Information on online security threats and fraud incidents will help your eCommerce company protect its customers and business.

Monitoring customer reviews and feedback on eCommerce platforms is valuable for maintaining and improving the quality of your products and services.

Analyzing data on competitors' strategies, pricing, and customer reviews can help your business stay competitive in the eCommerce market.

Collecting eCommerce sales data can help your business make informed decisions, optimize operations, and adapt to market trends and customer sentiment changes. eCommerce data also serves as a valuable resource for researchers and policymakers to understand the impact of eCommerce on a global scale.

Ultimately, insights from eCommerce activities enable data-led decision-making, which can support commercial growth far more effectively than assumption-based tactics.

If you think collecting eCommerce sales data will benefit your online business, you can’t just dive in head first and hope for the best. You’ve got to plan with precision. 

This way, you can ensure the data collected is relevant, accurate, and actionable. To see the best results from any eCommerce data collection efforts, we recommend taking the following steps to prepare before getting started.

Determine the specific goals and objectives of your data collection efforts. What do you want to achieve with the data you collect? Are you looking to optimize sales, understand customer behavior, improve website performance, or something else?

2. Select key performance indicators (KPIs)

Identify the key metrics and KPIs that align with your objectives. Common eCommerce KPIs include boosting sales revenue, conversion rate, average order value, and reducing customer acquisition costs.

Decide where you will collect data from. eCommerce data can be sourced from your website, mobile app, social media, email marketing, third-party platforms, and more. Ensure that you have access to the necessary data sources.

Select the tools and technology required for data collection. The eCommerce platform your company uses may have built-in analytics tools, but additional software or services may be needed for more in-depth analysis. Standard tools include Google Analytics, Adobe Analytics, and eCommerce-specific analytics platforms.

5. Ensure compliance with data protection laws

When you collect eCommerce sales data, you must adhere to strict privacy regulations. To do this, familiarize yourself with relevant data protection legislation and ensure your collection, storage, and deleting methods comply with the law.

You can set up automated reporting tools to regularly share key insights with stakeholders. Continuously reviewing and refining your data collection and analysis processes will provide a complete picture of customer activity and insights. You must also stay updated with industry trends and technologies to adapt to evolving customer behavior and market dynamics.

Collecting eCommerce data involves gathering information about online sales, customer behavior, and website performance. To make your data collection tasks a little easier, we've listed some typical methods and techniques to collect eCommerce data below:

You should utilize tools like Google Analytics or platforms your eCommerce software provides, e.g. Shopify Analytics. These tools offer pre-built features to track retail sales, conversion rates, and customer behavior.

Implement tracking pixels or JavaScript tags on your eCommerce website to track user interactions, page views, add-to-cart actions, and completed purchases. You can do this via Google Tag Manager.

Integrate your eCommerce platform with third-party tools and services specializing in data collection and analysis. To gather additional data, you can integrate CRM systems, email marketing platforms, and customer review services.

Use cookies to track user behavior and preferences. Cookies can store information about user sessions, cart contents, and past interactions, allowing you to personalize the shopping experience and analyze user journeys.

Collect qualitative data by using surveys and feedback forms on your website. Ask customers for their opinions and suggestions, which can provide insights into their preferences and pain points. 

Monitor social media platforms to collect data on customer sentiment, mentions of your brand, and product discussions. 

Analyze data from email marketing campaigns, including open rates, click-through rates, and conversion rates. Email service providers often offer detailed analytics reports.

Collect data on your product catalog, including SKU details, product descriptions, prices, and inventory levels. This information is essential for managing your eCommerce store.

Incorporate data from your customer support interactions to analyze information relating to customer inquiries and complaints.

When collecting eCommerce data, it's essential to prioritize data security, privacy compliance, and ethical data handling practices to protect customer information and adhere to relevant regulations. Regularly review and update your data collection methods to adapt to changing customer behaviors and market dynamics.

Eight ways to use proxies for global eCommerce data collection

Proxy servers can be valuable tools for collecting global eCommerce data and enhancing analysis processes. Here are nine ways proxy servers can help you: 

Proxy servers allow you to route your requests through servers located in different geographic regions. This feature is handy for collecting eCommerce data from various territories. By using proxies in specific countries or regions, you can mimic your target audience's location and test your eCommerce website's performance in different global markets.

Proxies enable IP rotation, so you can switch between IP addresses as you collect data. This reduces the chances of your IP being blocked or websites rate limiting you, which may restrict access to scrapers or bots. By rotating IPs, you can collect data more efficiently and avoid being detected as a scraper.

Proxy servers are commonly used for web scraping and crawling tasks. They enable you to gather product information, prices, reviews, and other eCommerce-related data from multiple websites and sources. Proxies make it easier to distribute scraping requests across different IPs, reducing the risk of being banned or blocked by websites.

Proxies provide a level of anonymity when collecting data. This can be beneficial when gathering competitive intelligence or monitoring competitors' pricing strategies, as you can do so without revealing your identity or IP address.

If your eCommerce data collection involves checking the availability of products, prices, or content on your website from various locations, proxy servers can help you simulate a user's experience in different regions. This is useful for ensuring your website offers global customers a consistent and relevant experience.

Proxies can distribute traffic across multiple servers or data centers, helping to balance the load and ensure consistent performance when collecting data from high-traffic eCommerce websites. This can improve the efficiency and reliability of data collection processes.

Some proxy servers offer security features, such as filtering malicious traffic or encrypting data transmissions. This can help protect your data collection activities from threats and ensure the data's security.

Proxy servers can simulate user traffic and interactions with your eCommerce website from different locations. This is useful for performance testing, load testing, and assessing website responsiveness in various global markets.

It's important to note that when you use proxy servers for data collection, you should respect the terms of service and policies of the websites you access. Some websites may restrict web scraping or data collection activities, so gathering data responsibly and ethically is essential.

Proxyrack makes collecting global eCommerce sales data easy

 from Proxyrack, you can kick-start your global eCommerce data collection and leverage the data to set your online store apart from your competitors.

As well as being super reliable, our proxies offer full anonymity when browsing, so you can track commerce sales from competitors with complete peace of mind.

Start collecting global eCommerce data with Proxyrack

How can you collect eCommerce data from different countries?

Using a proxy from Proxyrack, you can change your browsing location to the specific country from which you want to collect global eCommerce data. Analysis of this data can help you to refine your offering and improve sales in the location of your choice.

Global eCommerce Data Collection: A Comprehensive Guide

How To Collect Global eCommerce Data

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Making money online is big business. Like, 

 that ecommerce will generate an eye-watering $6.542 trillion USD in 2023, and 51% of businesses now interact more with their customers online than offline. 

These numbers only tell half the story, though. 

A huge number of digital start-ups fail, if not within the first year, within the first 3, 5 or 10 years. One of the main reasons for this trend is a lack of data on market conditions, industry competitors and customer insights. 

If you’re one of the many people looking for growth opportunities online, you need to stay ahead of the competition and on top of your game.

Web scraping is one of the best ways to do just this. Whether you have your sights set on a career change or want a boost for a side hustle, web scraping services can improve your financial situation.

In this blog post, we'll tell you all you need to know about web scraping. What it is, how it works and, most importantly, how you can make money from it.

 is the automated process of extracting data from websites. It involves using code to fetch web page content, examine it, and extract specific information for various purposes.

These purposes can include things like analysis, research, or data collection. It's essential to follow ethical guidelines and respect website policies when performing web scraping.

Companies can use any information you gather through scraping, meaning you can make money doing it and selling to them.

Web scrapers work by automating the process of fetching web page content, examining it, and extracting data. Here, you can see a step-by-step overview of how web scrapers typically work:

The web scraper initiates by sending HTTP requests to a targeted website's server. These requests will simulate the actions a web browser would take to access a web page.

The server responds to the requests by sending back the HTML content of the web page. This content contains the text, images, links, and other elements that make up the webpage.

The web scraper uses HTML parsing libraries to parse (examine) the received HTML content. This step involves breaking down the HTML into a structured format that can then be easily navigated and sorted.

From here, the scraper identifies and extracts specific data elements from the parsed HTML. This can involve searching for specific HTML tags (for example: <div>, <p>, <table>) or using 

Extracted web data can require cleaning and formatting to make it usable. This includes processes like removing unnecessary whitespace, converting data types, and handling any irregularities in the source data.

The scraped data can be stored in various formats, such as databases, spreadsheets, or JSON files, for further analysis. Sometimes, it can also be used directly in applications.

In cases where the data spans multiple pages, the web scraper may need to navigate through paginated content by following links to subsequent pages and then repeating the scraping process.

It’s important to note that web scrapers can vary in complexity, from simple scripts that extract a single piece of information from a web page to more complex systems that can crawl and scrape large amounts of data from multiple sources.

If done correctly and effectively, web scraping can be a valuable skill for generating income, but it's important to approach it ethically and in line with the law. Here are a few different ways to potentially earn money with web scraping:

 By offering web scraping services, scrapers can benefit financially by selling data to businesses that need it extracted from websites. The data can then be used for things like market research, competitive analysis, or gathering product information.

Enhance existing datasets by scraping additional relevant information from pages. Many companies are willing to pay for improved data quality.

Create a website or platform that aggregates content from various sources through web scraping. From here, you can monetize through advertising, subscription models, or affiliate marketing.

Extract data to generate leads for businesses looking for new customers. Data scraping can provide them with a list of contacts matching their criteria.

Build a price comparison website or tool that scrapes prices from various e-commerce sites. You'll see this commonly if you're looking for things like insurance providers. While these sites are live, you can earn money through affiliate programs or advertising.

Conduct market research by scraping data on product prices, customer reviews, or trends. Offer these insights to businesses or sell market reports. Businesses know that relevant data can be a hugely valuable asset when it comes to marketing plans going forward.

Create a job board that scrapes job listings from various websites, similar to 

 or Totaljobs. From here, you can monetize through job postings, premium features, or advertisements.

Scrapers can build a platform that aggregates real estate listings through web scraping. Once live, they can earn commissions or advertising revenue from property listings.

Use scraped data to create original content. For example, generate news articles or reports based on scraped data and monetize through advertising or subscriptions. These ideas could also be pitched and sold to publications if you are less interested in the creative side.

Once you understand the industry a little more, you can offer data analysis and consulting services to clients who have collected data through web scraping but need assistance in getting the most out of it.

Responsible web scraping involves adhering to ethical guidelines, respecting website terms of service, and being mindful of legal and ethical considerations. Here are some top tips to consider before you offer web scraping services:

To adhere to ethical scraping practices and stay out of any hot water in a legal sense, web scrapers should check the target website's robots.txt file to determine which parts of the site are off-limits to crawling and scraping.

Some websites may detect and block web scrapers. To avoid detection, web scrapers often include a user-agent header in their HTTP requests to make them appear as if they are regular web browser requests.

Responsible, experienced web scrapers will implement rate limiting to avoid overloading the target website's server with too many requests in a short period. This helps prevent disruptions and ensures fair usage across the board.

Bot blocking, geo-restrictions, and IP bans can often stop web scrapers from accessing the sites they need. Using a proxy can protect you from this to ensure the process runs as smoothly as possible. 

Web scraping could potentially make you a lot of money. As we've covered in our blog, there are so many ways that you could put web scraping to use, so it makes sense to invest some of your free time to learn a new skill.

How much money can you make from web scraping?

The amount of money someone can make from web scraping varies massively, given the fact that you can go about it in so many different ways. If web scraping has caught your attention, you can always look at building your career in the world of big data as a full-time web scraping engineer.

A web scraping engineer at the peak of his career can be expected to earn around $131,500 annually. If you started scraping as a freelance junior, you could earn around $50-$250 an hour.

Web scraping is completely legal if you scrape data that is available to the public. That being said, some kinds of data are protected by international regulations, so scrapers need to be careful around intellectual property and personal or confidential data.

How to Earn Money with Web Scraping

How to earn money with web scraping

Are you tired of scrolling through hundreds of job postings on Indeed just to collect the data you need? Then you're in luck. There are plenty of web scraping tools for Indeed that allow you to automatically extract data and organize it into readable and easy-to-use formats.

If you're new to data scraping or just want to know how using proxies can help, then this article has got you covered. In it, we'll explore the benefits of scraping Indeed data, and the type of data you can collect. We'll also give you a comprehensive step-by-step guide on how to do it. Plus, we'll explain why using proxies from Proxyrack can make your scraping project faster, easier, and more efficient than ever!

Scraping data from Indeed can give you some much-needed information and 

. Of course, this can benefit several types of people, from job seekers to HR representatives, managers, and business owners.

Indeed has an extensive database of jobs that contain valuable information. And instead of manually gathering all of this data, an Indeed jobs scraper tool can help you 

 based on cities, states, or even zip codes. This level of customization will help you to find potential job opportunities that are tailored to suit your preferences.

Similarly, scraping job details from Indeed can give HR managers and recruiters beneficial insights into job openings, salaries, and the profiles of job seekers. This data can help these professionals to make more informed decisions during the hiring process. Plus, having this data at their fingertips can help them to 

Still, one of the most important benefits of scraping Indeed data is that you can 

access fresh data without needing to manually crawl through the site

 or write complex code. This means that you won't need any coding knowledge to streamline your data collection process.

You can use a web scraping tool to gather data from Indeed, but the exact data that you can extract will depend on the job listings themselves. For example, some job postings may not list a salary bracket or reviews on the company.

However, the Indeed scraper tool will try to pull as much information as possible from the available job listing data, including:

Why Is Scraping Indeed Data Better Than Extracting Manually?

Although you can manually extract job data from Indeed, it can be labor-intensive and time-consuming. On the other hand, 

web scraping is faster and more efficient

. With an Indeed scraper, you can automatically collect data from multiple job postings on Indeed, which will save you a lot of time and energy compared to visiting individual pages and copying the information.

But this isn't the only reason that scraping Indeed data is better than manual extraction. 

How To Scrape Indeed Data: A Step-By-Step Guide

There are several different Indeed scraper tools that are hosted by a cloud service or that can be used as a web app. With so many different scrapers available, it can be a little tricky to find one that suits your preferences.

When you use an Indeed scraper, you'll need to consider your coding knowledge, data collection skills, and ease of use for each application. Then, when you have found an Indeed scraper that works for you and your specific needs, you can go ahead and collect all the data you want to use.

Regardless of which Indeed job scraper you use, the basic steps remain the same. We've listed a simplified example of what these steps may look like, but it's important to remember that they may vary depending on the platform you use.

Here are some of the most common steps when using an Indeed scraper:

The first step in collecting data from Indeed is identifying the web page or website that you'll be using for data collection. In this case, the website will be the main page of Indeed.

Once you have the URL of the website with the data you want, you'll need to access the website using your Indeed scraper tool. When you're collecting data from Indeed, the data you want to look at will be job postings.

You can access the website through a web browser if you're using tools like Indeed Scraper and Octoparse. However, for tools like Python with Beautiful Soup, you'll need to use Python's requests library.

No matter which tool you're using, the next step is to identify the specific elements on the webpage that contain the data you want to scrape. This can include elements like job openings, job titles, company names, locations, salaries, and more.

Now, you can use the tool-specific functions to extract any relevant data you find based on the elements you've chosen. In Indeed Scraper and Octoparse, you can do this through auto-detection, XPath selection, or by using templates. In Python with Beautiful Soup, you'll use HTML parsing and navigation methods to extract the data instead.

Once you extract data, it will need to be formatted as well so that you are able to understand and use it. Ideally, it will need to be formatted into a more structured format like JSON, CSV, Excel, or HTML. Most of the scraping tools across the web are able to support the extraction of data into various formats, so this step should be easy to achieve no matter which tool you use.

After you have set up the various parameters and workflows of your scrape, it's time to run the data scraping process. If you're using Python with Beautiful Soup, you can do this by executing the script. On Indeed Scraper and Octoparse, you'll click the 'Start' or 'Run' buttons respectively.

Pagination is a web design technique that is used to split large pages of data into multiple pages. This makes it easier for you to navigate through the content. In web scraping, pagination is important for extracting data from multiple pages of search results.

So, if you want to scrape multiple pages of job postings, you can set up pagination with tools like Python with Beautiful Soup and Octoparse so that you can navigate through different pages.

Why Choose Proxyrack For Indeed Scraping?

When you're web scraping data from sites like Indeed, using proxies can be helpful for several reasons. Proxyrack offers both high-quality

By using proxies from Proxyrack, you can boost the efficiency and reliability of your web scraping activities on Indeed. Our range of proxy options and our rotating proxies can help to give you the anonymity and IP diversity you need for successful scraping.

Yes! The data that you scrape on Indeed is available to the public, which means that it is legal to scrape. This is because it's completely legal to scrape data on any website that allows it, including Indeed.

It may be important to note, though, that some of the material that you scrape may be copyrighted. This is usually common with images like company logos, etc., that may appear on the job postings.

How many proxies are needed to scrape data from Indeed?

The number of proxies you'll need will depend on certain factors like the scale of your scraping project. Like other sites, Indeed has restrictions in place to avoid excessive scraping and ensure fair use of its resources for everyone. As a general rule of thumb, having around 10 proxies can be a good starting point when you're scraping Indeed or similar sites.

Can I trial a scraping proxy before I buy?

At Proxyrack, we take pride in the quality and reliability of our proxies. This is why we want you to experience their effectiveness first-hand with our 3-day trial for just $5 per product!

During your trial, you can test and evaluate our proxies to make sure that they suit your scraping needs. We're confident that once you try our proxies, you'll see the value that they can bring to your web scraping project management.

How To Scrape Job Data From Indeed

How to Scrape Data from Indeed

Automated testing is the process of using software to execute tests on other software in order to verify the authenticity of the proposed software. It's an integral part of the software development chain. With the fast-paced nature of development, numerous frameworks have sprung forth to facilitate automated testing. Two prominent contenders in the queue are Playwright and Selenium. 

This post provides a comprehensive comparison of Playwright and Selenium. It highlights their key differences and lists the advantages of each for automated testing. 

Brief Overview of Playwright and Selenium

 is an open-source JavaScript framework. Microsoft developed Playwright with automation testing as its default goal. It allows developers to automate web browsers for testing purposes. 

Playwright provides automated interactions with web browsers such as Chrome, Firefox, Safari, and Internet Explorer. Playwright was designed to be reliable, fast, and capable of handling complex web applications when the need arises. 