How do I connect Make to Scrapernode?

Use Make's webhook trigger to receive data from Scrapernode. Copy the webhook URL from Make and paste it into Scrapernode's webhook settings for the scraper. Each completed job sends results automatically.

What Xing profiles data fields are sent to Make?

All 17 output fields from the Xing Profiles scraper are included: account_id, familyName, gender, membership, country_code, experience, and more. The full payload is sent as structured JSON — no fields are filtered out.

Can I schedule recurring Xing scrapes to Make?

Yes. Use Make's scheduling features to trigger Scrapernode scrapes on a recurring basis via the REST API. You can also set up Make to process results as they arrive via webhooks.

How much does it cost to scrape Xing profiles into Make?

Each profiles record costs 1 credit. Credits start at $9 for 3,000 credits (Starter plan). The Make integration itself is included free — no additional charges for data delivery.

What happens if the Make delivery fails?

Your scraped data is always stored in Scrapernode regardless of the integration status. If delivery to Make fails, you can re-trigger the sync or download results manually as CSV or JSON from the job details page.

XingMake

How to Scrape Xing Profiles into Make

Extract profiles data from Xing and pipe into Make automatically

Step-by-step guide

Choose the Xing Profiles scraper

Navigate to the Xing Profiles scraper in Scrapernode. Select "Fresh Scrape" for real-time data or "Quick Lookup" for pre-collected records. Each record costs 1 credit.

Set up your Make connection

Create a new Make scenario with a Webhook trigger module. Copy the webhook URL into Scrapernode's webhook settings. Use Make's built-in JSON parser to map scraper fields to downstream modules like "Create Spreadsheet Row" or "Send Email".

Provide your Xing input URLs

Paste the Xing URLs you want to scrape — one per line, or upload a CSV. Scrapernode accepts direct profile links, search result URLs, and content pages.

Launch the scraping job

Click "Start Extraction" to begin. Scrapernode handles proxy rotation, rate limiting, and anti-bot detection automatically. Jobs typically complete in under 60 seconds per batch.

Receive data in Make

When the job completes, Scrapernode sends the full results to your Make workflow. Each record includes 17 fields like account_id, familyName, gender, membership. Route the data to any downstream app — CRMs, databases, email tools, and more.

Cost per record

1 credit

Output fields

17 fields

Destination

Make

Sample Output

Preview the data you'll receive — 5 sample records

Record 1 of 5

Account Id

sample_account_id

FamilyName

sample_familyName

Gender

sample_gender

Membership

sample_membership

Country Code

Experience

Array [2]

Object {3}

role:"VP of Engineering"

company:"Stripe"

years:"2021-present"

Object {3}

role:"Staff Engineer"

company:"Google"

years:"2017-2021"

Education

Array [1]

Object {2}

degree:"M.S. Computer Science"

school:"Stanford University"

Skills

PythonMachine LearningProduct StrategyAWS

Languages

Array [2]

Object {2}

title:"English"

subtitle:"Native"

Object {2}

title:"Mandarin"

subtitle:"Professional working"

City

San Francisco

Profile Url

sample_profile_url

Profile Image

sample_profile_image

Headline

VP of Engineering at Stripe | Ex-Google

About

Passionate about making technology accessible. 15 years building products that millions of people use daily.

Followers

28,401,080

Connections

1,000

Input Url

https://www.linkedin.com/in/sarahchen

Data Dictionary

17 fields returned per record

Unique identifier for the user's account (100.00% fill rate)

The user's family name or surname (100.00% fill rate)

The user's gender (100.00% fill rate)

Membership type (Basic, Premium, etc.) (100.00% fill rate)

Country code of the user (99.87% fill rate)

Work experience history (90.61% fill rate)

Sub-fields

currentBooleanWhether this is the current position

companyTextCompany name

titleTextJob title

start_dateTextStart date of the position

end_dateTextEnd date of the position

company_urlTextCompany Xing page URL

company_logoTextCompany logo URL

descriptionTextRole description

Educational background (71.34% fill rate)

Sub-fields

institutionTextEducational institution name

degreeTextDegree obtained

fieldTextField of study

start_yearNumberStart year

end_yearNumberEnd year

List of professional skills (62.45% fill rate)

Languages spoken (55.32% fill rate)

City of the user (89.44% fill rate)

URL of the Xing profile (100.00% fill rate)

Profile picture URL (78.21% fill rate)

Professional headline (82.14% fill rate)

About/bio section text (41.23% fill rate)

Number of followers (68.44% fill rate)

Number of connections (65.32% fill rate)

The URL that was entered when starting the scraping process (100.00% fill rate)

Frequently Asked Questions

Common questions about How to Scrape Xing Profiles into Make

Ready to connect Xing data to Make?

Start extracting xing profiles data and pipe into Make in minutes.

Go to Xing Profiles scraper Browse all integration guides

No code requiredAuto-delivery to Make17 data fields