How to Scrape Data from Multiple URLs Without Coding

As a developer, you may have extracted data from various websites using tools such as BeautifulSoup or Selenium Webdriver. But what if you need to collect information from a website without writing any code?

In such cases, you can use various web scraping tools available in the market.

List of Top 4 web data extraction tools

Anysite Scraper:

Any Site Scraper is a high-quality data extraction tool for websites such as Instagram, Facebook, and Twitter. It can scrape multiple URLs at the same time and export them for use in other programs or via email. This program is ideal for data collection and database storage.

Cute Web Phone Number Extractor:

Cute Web Phone Number Extractor is a simple software that extracts phone numbers from any website. The tool, which was created with the assistance of web programming professionals, can retrieve any type of phone number and save it in formats such as Excel, CSV, or Text files. Its built-in UI makes it simple to customize extraction settings.

Cute Web Email Extractor:

Cute Web Email Extractors is a powerful email extraction tool that works with a variety of email formats and protocols, including POP3, IMAP, HTTP, and SSL. The tool has an easy-to-use interface and can extract multiple emails at once. It also supports batch processing and automatic content extraction from HTML pages. Options such as file name extension, size, and line or character limits can be used to customize the extraction settings.

Google Map Extractor:

Google Map Extractor is a simple data scraping tool that allows you to extract useful information from Google Maps without having to write any code. The tool, which has an interface similar to Google Chrome’s URL scraper, can extract structured data from hundreds of business directories every day. This tool is a quick and easy way to get company information from Google Maps.

How to Train Your AI Model With Web Data Using Web Scraping

A significant amount of information can be found in the form of data in today’s era, which can help in coming to conclusions and making informed decisions through research. Nonetheless, gathering all of this information on your own can be difficult, prompting the use of specialized tools. This is where web scraping services come in handy, allowing for the gathering of abundant information from various sources in order to improve website performance.

Leveraging Web Scraping to Enhance Market Analysis

The primary goal of data extraction is to gather information that isn’t readily available. This can be advantageous for market research because it enables customized data analysis and information extraction without relying on public access or self-service functions.

Training AI Model to Discover the Varied Types of Data Obtainable via Web Scraping

When you are training your AI Model to scrape the web for data extraction, you should make sure to emphasize training it to collect only the data that can provide valuable insights to facilitate business growth. Below are some of the information you can extract with web scraping:

Company information:

A critical data collection task is procuring company information from a competitor’s website. The primary goal of gathering such relevant data is to comprehend how the business generates revenue. By analyzing this data, you can evaluate their performance and find opportunities for increased profitability.

Product information:

Acquiring product data is critical because it is used to promote your products or services. By scrutinizing a product’s Amazon product page, one can learn important information about it, such as its name, features, qualities, price, etc.

User behavior data:

Another important type of data that can be obtained through data scraping is user behavior. It allows you to gain insight into your website’s users’ interests, thoughts, actions, and interactions.

Sales numbers:

These are the basic data forms that can be obtained through web scraping. You can use this information to evaluate your website’s performance, site volume of traffic, and traffic sources.

When using data scraping, take into account that particular legal requirements have to be fulfilled when configuring the crawler. For example, if you intend to extract financial information, you must ensure that the crawler complies with all laws and regulations.

Also Read: A Simple Guide to Scraping Static and Dynamic Websites with Python


Large-Scale Web Scraping: An Ultimate Guide

The expanse of the internet requires no new introductions, and the number of people that visit the internet each day can be counted in millions. These millions of people generate a massive amount of data every minute of the day, making it a time-consuming and resource-intensive task to retrieve all such data.

It is critical to organize this enormous trove of information in a meaningful way in order to derive meaning from it. This is where large-scale web scraping is becoming extremely useful. It is a process that involves gathering information from websites, particularly those with large amounts of data.

The Best Practices for Large Scale Web Scraping

Managing large-scale web scraping can be a difficult task because it involves large amounts of data that must be updated on a regular basis. The following are some of the best practices for large-scale web scraping to optimise the process:

  • Create Crawling Path:

To gather extensive data via web scraping, the initial step is to establish a crawling path, which involves methodically exploring a website and its content for data. This can be done using automation tools Scrapebox and ScraperWiki, or by manually inputting URLs into software to extract data.

  • Data Warehouse:

A data warehouse is essential for large-scale web scraping because it acts as a centralised hub for analysing and cleansing large amounts of data. It is a structured data collection that is organised and used for analytics and business reporting.

  • Proxy Service:

A proxy service, which can be used to scrape images, blogs, and other types of information collected via the internet, can make large-scale web scraping easier. It conceals your IP address by replicating your computer’s IP address on another server and sending requests to it.

  • Detecting Bots & Blocking:

Bots pose a significant challenge to web scraping as they mimic human behaviour and extract data from websites. To detect them, crawling libraries like Scrapy, ScrapySpider, and Selenium WebDriver are crucial to avoid being blocked by website owners who don’t want their sites crawled.

Large Scale Web Scraping is an important tool for businesses because it allows them to analyse website traffic and visitor behaviour. It can also be used to compare the performance of different website versions.

Also Read:

Top 10 Amazon Scraping Tools 2023

How To Extract Data From Food Delivery Apps For Business Profits

Top 10 Amazon Scraping Tools 2023

The practice of retrieving a webpage and extracting its data is referred to as web scraping. After acquiring the information, it is common to analyze, reformat, parse, or transfer it to a spreadsheet. There are various web scraping applications, but we will concentrate on a few for now, such as collecting price and product data from marketplaces. Retailers utilize this information to enhance their understanding of the market and competition.

With millions of products available on the Amazon Marketplace, it can be challenging to keep up with the latest trends and insights to improve your store’s performance. Fortunately, web scraping can be useful for extracting valuable data from Amazon’s website, including product information, pricing, customer reviews, and more.

Why should you use web scraping?

Web scraping can help you streamline your product research process and save time that would otherwise be spent manually searching through the website. This can help you stay ahead of the competition and improve your store’s efficiency and profitability. Web scraping can assist in increasing your business growth tenfold using web data, regardless of whether you’re a new or expanding enterprise.

Here is how web scraping can help you improve your business:

Technology makes it easy:

Everyone has access to the latest technology, and there is no reason for you to hold back on utilizing every resource you can get your hands on. Access to technology is paramount when it comes to web scraping since it allows virtually anyone to scrape large amounts of data efficiently. Numerous resources are available online to help you become proficient in web scraping, and you can leverage various service providers who can assist with data collection.


The potential uses of web scraping are boundless. By providing easy access to web data for everyone, web scraping sets a higher standard for innovation. It compels businesses to enhance their value proposition. Web scraping enables businesses to test and implement new ideas more swiftly, promoting faster innovation.

Marketing automation:

Web scraping can aid in marketing automation by automating lead generation, competitor analysis, market research, and content creation. Extracting data from websites helps businesses acquire the necessary information for effective marketing campaigns and decision-making.

Brand monitoring:

The market for brand monitoring is rapidly expanding. In today’s world, checking customer reviews before buying online has become fundamental, as consumers prefer recommendations and reassurance when making purchasing decisions.

Top 10 Amazon Scraping Tools for 2023


Octoparse is a web scraping tool that is free for life, enabling users to extract web data without any coding knowledge quickly. The tool stands out with its intuitive, graphic UI design and auto-detection function, eliminating the need to search for data manually. While the free plan has a 10,000-row limit, paid plans offer cloud service, scheduled automatic scraping, and IP rotation, making them useful for monitoring stock numbers, prices, and other information on a regular basis.

SS Technology:

SS Technology is a leading Amazon scraping service provider that utilizes modern technology to scape Amazon data and help businesses make informed decisions regarding their marketing. They use various tools, scripts, and software that are crucial in the process of web data extraction, particularly when dealing with enterprise-level data.


ScrapeStorm is a visual web scraping tool that uses AI to detect data, similar to Octoparse’s auto-detection. Its browser-like UI makes it easy to use, and its Pre Login function can scrape URLs that require login. A free quota of 100 rows and one concurrent run is available, but upgrading to the professional plan with 10,000 rows per day is recommended for more data.


ParseHub, a downloadable web scraper, is another free tool that enables users to build custom crawlers and export data into structured spreadsheets. Although it doesn’t support auto-detection or offer Amazon templates, experienced users can still utilize it for Amazon scrapping.

Instant Data Scraper:

The majority of the Amazon scraping tools that have been mentioned have additional and advanced functionalities apart from scraping. While they can be beneficial, they can also make the platform more complicated. For those who only require data extraction from a webpage, Instant Data Scraper is a simpler solution.

Data Miner:

Data Miner is a browser extension that can be used with Google Chrome and Microsoft Edge. It enables the extraction of data from web pages and exporting it to a CSV or Excel file. There are several custom recipes that can be used to scrape Amazon data with ease. With a user-friendly interface and basic functions, it is suitable for small businesses or casual users.


This tool can assist you in scraping data from Amazon, as well as a variety of operating systems, and its AI-based web scraping tool eliminates the need to specify the desired data. Developed by expert developers, these tools are reliable and efficient. is a developer tool that offers a point-and-click interface. Unlike other scrapers, it doesn’t have specific templates for Amazon or e-commerce scraping, so users must build their own crawler by selecting the information they need.

Scraper Parsers:

Scraper Parsers is a browser extension that can extract unstructured data and visualize it without requiring any coding. Once the data is extracted, it can be viewed on the site or downloaded in various formats such as XLSX, XLS, XML, and CSV. Moreover, the tool can create charts and display the extracted numbers in an easy-to-understand format.


Apify is a powerful Amazon scraper that surpasses the limitations of the official Amazon API. t allows you to obtain price offers for a specific Amazon standard ID, search for a specific keyword, and target a specific country. With Apify, you can easily obtain all the necessary data you need from Amazon.

By leveraging web scraping techniques, you can obtain detailed insights about your competitors, identify popular products, track pricing trends, and gather valuable customer feedback. These insights can help you make informed decisions about your inventory, pricing strategies, and marketing campaigns, giving you a competitive edge in the marketplace.


How To Extract Data From Food Delivery Apps For Business Profits

The food delivery app sector is among the most rapidly expanding industries, as stated by Statista. The online food delivery segment is expected to grow to approximately $129 billion by 2023 and is projected to increase further to around $192 billion by 2025.

Numerous apps are included in the category of food ordering apps, such as Zomato, Swiggy, and Uber Eats. These apps have gained popularity not only for delivering food but also for the significant amount of data they gather. With this data, you can offer your customers a customized experience and an extraordinary culinary journey.

Various Kinds of Data to Collect from Food Delivery App

Restaurants can team up with food delivery apps to expand their business further. If you are starting your own restaurant, you can use web scraping services to obtain several data types from your local food delivery app. The following are some examples of data that you can collect using web scraping services:


Location data plays a vital role in food ordering applications as it helps determine the optimal location for customers and ensure timely food delivery. GPS or other technologies such as Wi-Fi, Bluetooth, and even employee assistance can be utilized to gather location data.

Order History:

The order history comprehensively records all orders placed through the app. It can aid in identifying trends and patterns in customer behavior. By leveraging restaurant data scraping, this information can help restaurants better comprehend their customers’ preferences and ensure prompt delivery of their products.

Category Data:

The category data consists of the most frequently ordered food type by users. This categorization can be utilized to refine search results, making it easier to locate the appropriate restaurant or dish.

Benefits of Collecting Data from Food Delivery App

Collecting and analyzing data has become a crucial aspect for businesses in today’s world. Utilizing data from various sources, including online food-ordering apps, can benefit businesses in several ways. It can help improve the overall customer experience by identifying pain points and offering tailored solutions. As a restaurant owner, you can leverage the data to enhance your marketing efforts by gaining insight into customer preferences and behavior. Understanding customer behavior can also help businesses optimize their products and improve accessibility.

How To Extract Data From Food Delivery Apps For Your Business?

There are numerous ways to collect data, but one of the most popular methods is through online food ordering app scraping service. SS Technology is a top-notch web scraping service provider. Their services enable you to effortlessly scrape data from popular apps such as DoorDash, Uber Eats, Grubhub, Zomato, Postmates, and Deliveroo, among others. They have a team of highly skilled developers to ensure that every minute detail of your business is accurately and professionally captured.

Also Read: Decide the Right Price for Your Hotel Using Web Scraping

An Easy TripAdvisor Scraper to Get Hotel Data and Reviews

Tripadvisor is the go-to website for finding the best hotels, restaurants, tourist attractions, adventure games, and everything else you need for an enjoyable trip. It has become a customary practice for anyone planning to travel to a new city or country to search Tripadvisor for the top sites and activities to do.

Millions of people use the internet to plan their dream vacations every year. As the platform is immensely popular, an increasing number of hotels, restaurants, and other tourist businesses are vying to get listed on it and maintain a good rating, as positive reviews on the website can be extremely advantageous.

Types of data that can be scraped from Tripadvisor

Tripadvisor is an online platform that allows users to book flights, hotels, and activities. It also enables customers to provide feedback on hotels, restaurants, tours, and other businesses, resulting in a wealth of review and pricing information. In the competitive tourism industry, Tripadvisor helps visitors find resorts, rentals, or excursions, making it a valuable tool for travel agencies and anyone operating in hospitality. Web scraping can be utilized to extract customer reviews, usernames, popular venue details, and more, in addition to ticket and room prices.

Steps to scrape Tripadvisor data without coding

SS Technology is a scraping tool that requires no coding skills and can gather hotel data from Tripadvisor. Its auto-detecting function allows anyone to create a crawler quickly, and it comes with pre-built templates for most websites, including Tripadvisor scraper, making the process faster and easier.

To scrape data from Tripadvisor using SS technology, simply copy the URL and paste it into the search box. Use the auto-detecting feature to scrape data, create a workflow, and preview the data fields. Modify as needed with the help of the Tip panel, then run the scraper and export the data in various formats.


By using data from Tripadvisor, travel agencies can gain insights into their clients’ preferences and analyze their competitors. The Tripadvisor API allows hospitality sites to incorporate Tripadvisor reviews into their own platforms.

Also Read: A Simple Guide to Scraping Static and Dynamic Websites with Python

How Web Scraping Reddit Can Benefit You

Businesses and individuals can find a wealth of information on social media platforms. However, some platforms are more user-friendly than others. For researchers, Reddit is a highly accessible and valuable site. Therefore, scraping Reddit data can be an efficient method to collect diverse data without the challenges found on other social media platforms.

Why Should You Start Web Scraping Reddit?

Reddit is unique among social media sites because it offers the option to create subreddits, which are community pages focusing on specific topics. Threads, or individual posts, can be created within these subreddits and may include various media forms such as images, videos, and GIFs. Other users can respond to these threads, creating a conversation.

The ease of use and anonymity fosters a sense of community among individuals with similar interests and preferences, resulting in a multitude of thriving subreddits devoted to topics ranging from weight loss to video games to politics to favorite brands.

What Can You Do With Reddit Data?

Given the high activity level on Reddit, web scraping data from the site can be beneficial for both personal and business purposes. Some popular applications of Reddit data scraping include:

Tracking opinions:

Companies often monitor public opinions regarding their brands to develop effective marketing strategies. Scraping Reddit data is a reliable method to keep track of these opinions and obtain precise outcomes.

Gathering feedback:

Organizations can use Reddit web scraping to gather feedback efficiently. The process of scraping is simple: extract comments and threads related to the organization or its products. Web scraping Reddit for feedback can provide novel insights that may not have been discovered through traditional customer surveys.

Studying competitors:

Reddit provides an opportunity for businesses to identify their competitors’ strengths and weaknesses by analyzing public opinion, giving them an advantage in their own marketing strategies.

In Short!

Reddit contains abundant information on specialized topics, making it a valuable source for researchers. Scraping data from Reddit allows researchers to gain insights into public opinion, trends, and tips related to various subjects. Researchers can access all available information on a topic without the obstacles of privacy settings or IP bans, ensuring that no valuable conversations are missed.

Also Read: The Ultimate Guide to Review Scraping in 2023

Web Scraping Airline Data – A Boon for the Tourism Industry

In the ever-changing travel industry, customer needs and preferences constantly evolve, making it essential for market players to stay abreast of industry trends, customer choices, and their own historical performance in order to improve over time. Therefore, it’s no surprise that companies operating in this sector require copious amounts of data from various sources, as well as a robust pipeline to analyze and leverage that data for insights and recommendations.

Competition in the Travel and Tourism Industry

Over the past few years, the aviation industry has witnessed a surge in the number of market players, intensifying competition and compelling airlines to maintain competitive prices while delivering a seamless customer experience. Given that travel, whether domestic or international, can be a stressful affair for most people, a positive experience from the moment of ticket browsing can significantly influence an individual’s airline preference.

How can Web Scraping Airline Data help?

Retaining customers in the aviation sector is a complex process due to numerous variables that are in a constant state of flux. In such a scenario, web scraping airline data can prove immensely advantageous. It facilitates a better understanding of aviation market conditions, enables personalized offers, and allows monitoring of price fluctuations for comparable flights offered by other airlines.

Here is how web scraping can help:

  • Price Variations:

By evaluating the market conditions and pricing strategies of other airlines, carriers can use this data to refine their pricing model effectively. Access to information like price fluctuations is crucial for airlines to remain competitive, enabling them to analyze fluctuating flight prices.

  • Anticipate Business:

By providing a historical overview of high-traffic and low-traffic periods, including hotel reservations, seasonal flight bookings, and successful itineraries, companies can adapt their business model and better accommodate these variations.

  • Enhanced Marketing:

Airlines can leverage web scraping to understand their customers and enhance their offerings, tailor marketing strategies, and cultivate a loyal customer base.

  • Benchmarking:

Airlines can also benefit from web scraping by regularly benchmarking themselves against their competitors. In a saturated industry, maintaining high standards and ensuring customer satisfaction requires ongoing effort, and that’s how web scraping can help.

Companies in the travel and tourism sectors can reap significant rewards by incorporating web scraping services into their operations.

Also Read: How Can Data Scraping Help the Travel Industry Get More Business?

A Simple Guide to Scraping Static and Dynamic Websites with Python

You may need to retrieve a vast amount of information from a website swiftly for various reasons. It might be for your business or for your clients who need such information from websites to market their services and products. In such cases, web scraping can be incredibly useful, as it streamlines the task and guarantees the data’s quality. Currently, web scraping bots can scrape static and dynamic websites and present the data in an organized format.

Nevertheless, one may wonder how these bots can extract data from a static website and what techniques are involved in dynamic website scraping using Python. Additionally, it’s worth exploring the advantages of scraping different types of websites.

Benefits of Static and Dynamic Websites

Static Websites

Here are some of the well-known benefits of a static website:

Faster Creation:

Static websites do not require links to organized databases and can be created and published more swiftly due to their more straightforward nature.

Faster Load Time:

Static websites prioritize load time to enhance browsing efficiency, resulting in a website that utilizes fewer server resources and loads quickly.

Dynamic Websites

The benefits of having a dynamic website are:

Easy to update:

Dynamic websites are capable of updating multiple pages’ content without altering their appearance when a single page’s content changes.


Due to their interactive nature, dynamic pages provide efficient and high-quality services to end-users, resulting in an overall superior user experience.

Web Scraping Using Python

Web scraping with Python is an exciting technique that allows us to extract vital data from websites with ease and efficiency. By utilizing the structured nature of HTML, and Python programming, and its powerful libraries such as BeautifulSoup and Scrapy, developers can gain valuable insights and even automate tasks like data mining and analysis. What makes this process truly captivating is its versatility, enabling you to acquire information from e-commerce listings, market trends, social media interactions, or any other online source your imagination could conceive. Furthermore, Python’s user-friendly syntax and extensive online resources facilitate learning and growth for novices and experts alike. No doubt, mastering the art of scraping web pages with python will unlock a world of boundless opportunities and new possibilities.

Ways to Scrape Static Websites With Python

Before scraping the data from a static website, figure out what data you need to extract. Create a new folder on the desktop with the extension (.py) using the terminal command, and launch Visual Studio Code with the command $ code. Then, open the single empty file in the “” folder and import the entire library. Use HTTP requests and BeautifulSoup to parse and search for the necessary data. Save the data to empty arrays and extract the required data using loops. Next, create a CSV file data frame with the header as the key and value pairs, and use the DataFrame method to convert data into a data frame. Finally, export the data frame to a CSV file using .to_csv(“name.csv”).

Ways to Scrape Dynamic Website with Python

Scraping dynamic web pages requires the use of a headless web browser and a combination of BeautifulSoup and Selenium libraries. To extract the resulting page links, use a while loop to navigate through the search result pages and store each page URL in the list page_lst_link.

Next, extract the product links from the resultant pages by navigating to each page link, parsing the HTML with BeautifulSoup, and storing the product links in the list product_links. You will need to create a data frame to store the extracted data, scrape the relevant information, and store the requests from the URL in page_content using the Selenium web driver. Create a CSV file after extracting the required information to complete the dynamic website scraping process.

Also Read: How do I scrape data from Google Maps?

How can advanced price monitoring software be a game changer for you?

The online world is quite dynamic and things change at a rapid pace when it comes to the eCommerce universe, things are even more dynamic. Cut-throat competition keeps you on your toes at all times. Finding out the right price for your products when pricing is the key differentiator that influences purchasing decisions the most isn’t that easy at all.

So, how do you deal with this herculean problem?

How would you entice a customer who is just a few clicks away from getting the best product that fits his bill at the desired price? An ultra-modern online price monitoring software is the panacea for all of these problems that might add to your woes. As an eCommerce business, the right competitor price monitoring software can truly be a game-changer for you.

How? Let’s dive right in and find out.

  • Define your main competitors

Having the best price monitoring software will solve almost all pricing optimization problems. Keeping track of price changes manually is simply not possible and this is where eCommerce price optimization for the marketplace turns out to be the secret sauce that makes selling your products at optimal prices a breeze.

The first step is defining your main competitors, but how do you define who your main competitors are?

Your main competitors will be the ones who are selling the same or similar products and are most likely to pull the customers away from your brand. It also makes sense to define your key products and more often than not these products are price-sensitive and the best-selling products.

  • Identify product variations

Identify product variations and try grabbing product details as much as you can. The best online price monitoring software will help you find the right direction, but at the end of the day, you would need to have a good strategy at hand. You can perform product matching using ultra-modern software customized to your needs.

Being a leading price comparison software company based in India, SS Technology offers bespoke competitor price monitoring software that would make the entire complex price optimization process a breeze for you. As a pioneer in the domain, we have seen eCommerce enterprises scaling newer heights of success by leveraging price monitoring.

  • Track competitor product URLs

Just defining your main competitors and key products isn’t enough as you must also know the product URLs on each of your competitors’ websites. This will help you strategize price optimization and make price changes, especially when they run out of stock on certain products.

Also Read: 3 Reasons to Use Price Monitoring Software for Price Policy Violations

The Bottom Line:

A robust competitor price monitoring software can fully automate the price monitoring process and owing to its accuracy, you’d see results in a very short time span. If you are looking for the best competitor price tracking tool, You can easily plan price monitoring and make the necessary adjustments in a jiffy. SS Technology will be more than glad to help you out. Drop us a line or call us and one of our price monitoring software experts will connect with you in 24 to 48 hours.


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