How to Use Real Estate Web Scraping to Gain Valuable Insights
Real estate web scraping: a powerful tool for data collection and analysis. Learn how to choose the right data collection method and benefit from real estate web scraping
XING is where professional hiring happens in the German-speaking world. From executive searches in Berlin to NGO recruitment in Zurich — this is the platform top employers use to reach local talent. With our XING scraper, you can extract valuable job listings and candidate data from a network trusted by over 21 million users in DACH. If you're targeting Germany, Austria, or Switzerland — this is your primary source.
At ScrapeIt, we act as your plug-and-play XING data scraper — no software to install, no parsing headaches. We extract live job postings, company profiles, and professional data directly from the XING ecosystem, filtered by region, industry, or language.
You’ll receive structured, clean data in your preferred format — ready to support your hiring platform, research project, or business expansion in DACH markets. We handle the extraction, so you get instant access to insight without dealing with the platform’s limitations.
With our XING scraper, we collect key data from both sides of the platform — job listings and professional profiles. From job ads, we extract job titles, company names, job locations, employment types (full-time, part-time, remote), job status (active, draft, closed), visibility metrics like impressions and number of applicants, and salary information — when disclosed by the employer.
We also extract candidate-facing data, including user names (where public), job titles, current employer, career level, location, skills, and profile activity. Many profiles contain structured details such as work history, education, languages, and industry focus — all useful for recruitment, lead generation, or research.
Our XING scraper also captures performance metrics from job ad dashboards — such as duration of publication, engagement stats, and working time models.
For company pages, we can extract structured sections like “About us,” “News,” “Open positions,” “Company culture,” and “Contact details.”
On the candidate side, we can retrieve profile summaries, photos, timestamps of recent activity, and optional star ratings or tags used internally by recruiters.
This extra layer of data helps platforms, HR teams, and analytics tools monitor activity and performance inside Germany’s leading career network.
XING is the leading professional networking platform in the DACH region — Germany, Austria, and Switzerland — with over 21 million users. Launched in 2003 and part of the New Work SE group, it serves as a local alternative to LinkedIn with deeper market penetration in German-speaking countries.
The platform connects professionals, recruiters, and companies through job listings, events, industry groups, and direct messaging. XING also offers employer branding tools, performance metrics, and recruiting services tailored for the DACH market. Its interface is available in multiple languages, but the content is primarily German.
XING operates under the main domain xing.com, with no regional subdomains — making it a unified entry point for all users across markets.
Get a QuoteDevelopers
Customers
Pages extracted
Hours saved for our clients
Customized scraping setup for XING — faster and cheaper than building a solution from scratch.
Data limits (rows): up to 10%
Iterations: up to 3
Custom requirements: Yes
Data lifetime: up-to-date
Data quality checks: Yes
Delivery deadline: 1-2 working days
Output formats: CSV, JSON, XLSX
Delivery options: e-mail
To understand the German-speaking job market, you need data from the source people actually use. When you scrape XING, you get access to up-to-date job ads, company activity, and candidate profiles — all structured around real local behavior.
Whether you're tracking hiring trends, mapping company networks, building a recruitment platform, or enriching your database with verified B2B leads — scraping XING gives you insights that global platforms often miss. It’s not just another job board — it’s the backbone of professional activity in DACH.
Learn how to use web scraping to solve data problems for your organization
Real estate web scraping: a powerful tool for data collection and analysis. Learn how to choose the right data collection method and benefit from real estate web scraping
Amazon provides valuable information gathered in one place: products, reviews, ratings, exclusive offers, news, etc. So scraping data from Amazon will help solve the problems of the time-consuming process of extracting data from e-commerce.
The use of sentiment analysis tools in business benefits not only companies but also their customers by allowing them to improve products and services, identify the strengths and weaknesses of competitors' products, and create targeted advertising.
ScrapeIt helps you collect web data without code, scraping tools, or guesswork. We deliver the exact information you need — cleaned, structured, and formatted for your use case. Whether you need a one-time pull or recurring data exports, we handle the entire process.
No need to build your own parser or manage API limits — we extract data directly from live platforms like XING and deliver it in a way that fits your workflow.
Yes, we can tailor the extractor to collect only the data type you need — job ads, profiles, or both.
We can deliver the data in CSV, Excel, JSON, or another convenient format that fits your workflow.
Yes, we can collect public profile data such as job titles, current employers, skills, and professional background.
We support both one-time exports and scheduled updates — daily, weekly, or custom intervals.
Scraping data from XING is increasingly common among HR tech platforms, B2B data providers, and recruiters targeting the DACH region. The platform’s regional focus and professional user base make it a valuable source for structured job and profile data.
1. Make a request
You tell us which website(s) to scrape, what data to capture, how often to repeat etc.
2. Analysis
An expert analyzes the specs and proposes a lowest cost solution that fits your budget.
3. Work in progress
We configure, deploy and maintain jobs in our cloud to extract data with highest quality. Then we sample the data and send it to you for review.
4. You check the sample
If you are satisfied with the quality of the dataset sample, we finish the data collection and send you the final result.
Scrapeit Sp. z o.o.
10/208 Legionowa str., 15-099, Bialystok, Poland
NIP: 5423457175
REGON: 523384582