ScrapeIT.io

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Overview

< $25/hr

Avg Hourly Rate

10 - 49

Employees

2021

Year Founded

ABOUT SCRAPEIT.IO

Web Scraping Services. Tailored Data Delivery.

We specialize in web scraping services, providing ready-to-use datasets in various formats, whether you need real-time, hourly, daily, weekly, or on-demand data. We can manage projects of any size, from single requests to the daily extraction of numerous records from complex and secure platforms. Our expertise includes data scraping from major sites like Amazon, eBay, Walmart, Allegro, eMAG, Alibaba, Zillow, Realtor, Indeed, and over 1,000 other websites across multiple sectors. We serve a wide array of industries, including E-Commerce, Real Estate, Travel, Marketing, Automotive, Finance, Job Market, and Healthcare. Our team handles CAPTCHA solving, anti-bot measures, scalable browser clusters that mimic real user activity, and AI-driven data transformation customized to each client's specific needs, including language translation. We oversee the entire delivery process and adhere to deadlines. Reach out to us for prompt access to the data you require.

Languages Spoken

EnglishPolish

HIGHLIGHTS

< $25/hr

Avg Hourly Rate

10 - 49

Employees

2021

Year Founded

Services

Focus

Industries

Clients

Services Provided

100% BI & Big Data Consulting & SI

About the Team

OUR STORY

ScrapeIt Sp. z o.o., based in Bialystok, Poland, specializes in delivering expertly managed web scraping services tailored to the travel and hospitality industry. Recognizing the dynamic nature of travel tech—with rapidly changing fares, fluctuating room inventories, and evolving competitor offerings—ScrapeIt centralizes the complexity of data extraction from major platforms like Booking.com, Expedia, Airbnb, and more. By handling challenges such as JavaScript-heavy sites and anti-bot measures, ScrapeIt enables teams across OTAs, airlines, hotels, and market research to access timely, structured data for pricing, inventory, and sentiment analysis. Their managed approach ensures continuous data delivery without requiring clients to maintain scraping infrastructure, empowering businesses to stay competitive and make informed decisions in an ever-changing market.

Portfolio

Ralph Lauren Brand Monitoring on Amazon Worldwide

NDA

The customer's goal was to implement ongoing monitoring of Clothing, Footwear, and Accessories from the 'Ralph Lauren' brand available on Amazon subdomains: AE, DE, ES, FR, IT, NL, PL, and UK. The scraping websites included amazon.ae, amazon.de, amazon.es, amazon.fr, amazon.it, amazon.nl, amazon.pl, and amazon.co.uk. They sought a dataset with specific requirements: the positioning of products in Amazon search results (including the page number and slot number), a comprehensive list of ASINs categorized by colors and sizes for all products, product descriptions, images, and ratings, availability and inventory details, and a complete list of sellers for each ASIN along with their registration information. Furthermore, it was necessary to exclude products from third-party brands that were not associated with 'Ralph Lauren' from the search results. The data underwent normalization, formatting, and cleaning, resulting in a total dataset of 41,000 rows. The creation and testing of the scraper took 4 days, while the data crawling was completed in 1 day.

E-Commerce Data Scraping: Allegro

NDA

A client specializing in price optimization on Allegro.pl reached out to us. Their approach involves assessing the lowest price of a product on the marketplace against their suppliers' pricing to see if they can offer the product at an even lower price while still earning a profit. Our scraping target is allegro.pl. Each day, the client sends us a list of approximately 150,000 EANs for us to search on the site. Our job is to identify the lowest price for each of these products daily and provide the client with reports. They utilize these reports to calculate profit margins and decide on potential deals. This project is technically challenging due to Allegro's robust anti-bot measures, including a Slider Captcha which cannot be solved automatically. Managing 150,000 requests daily without downtime presents significant anti-bot difficulties. The development and testing phase took 12 working days, and the daily dataset consists of around 150,000 entries.

Zillow Real Estate Data Scraping

NDA

The customer's goal was to consistently track listings for various types of real estate properties available for sale and rent in Massachusetts. Websites to be scraped include zillow.com. One notable aspect of Zillow's property pages is that for buildings with multiple units, the scraper must navigate through all the unit cards. Zillow utilizes a "Press&Hold" Captcha to identify automated crawlers. While this Captcha may seem easy to solve at first glance, it effectively blocks access when it suspects automated traffic. The proper approach to circumventing the Press&Hold Captcha involves using an advanced browser masking technique to prevent it from triggering. The dataset comprises around 22,000 rows daily. The development and testing of the scraper took 5 days, while the actual data scraping took just 1 day.

10 more projects

Projects & Clients

Project Size & Rate

Average Hourly Rate

< $25/hr

Pricing Snapshot

Min Project Size

N/A

Avg Hourly Rate

< $25/hr

Cost Rating

N/A

What Clients Have Said

"ScrapeIT.io delivers quality projects within budget and timeline expectations based on verified client feedback."

Based on verified reviews and internal benchmark data

PROJECT BUDGETS

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BI & Big Data Consulting & SI

Locations

Headquarters

10/208 Legionowa str.

Bialystok, Podlaskie, Poland 15-099

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