ProWein Fair Match Scraper

Last updated: February 2025

Extract visitors and exhibitors from the ProWein Fair Match networking platform. Perfect for wine & spirits industry B2B lead generation, event networking, and exhibitor databases.

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🎯 Why use this scraper?

Extract 20,000+ ProWein participants in minutes with automatic login, pagination, and optional profile enrichment. No manual export, no copy-paste. Data ready for CRM, spreadsheets, or outreach campaigns.

✅ What you get

Complete participant data including:

• Identity: First name, last name, company
• Professional: User type (EXHIBITOR / VISITOR), job industry, position, department (libellés lisibles)
• Location: City, post code, country (when enrichment enabled)
• Profile: Profile images (when enrichment enabled)
• Product interests: Categories wanted & offered (when enrichment enabled)

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🚀 Key Features

📊 Complete Data Extraction

• ✅ Automatic login via Puppeteer (or skip with JWT)
• ✅ Cookie consent handling (Usercentrics shadow DOM)
• ✅ Pagination with parallel requests (5+ pages at once)
• ✅ Optional profile enrichment via userprofiles API

⚡ Performance Optimized

• ✅ Parallel pagination – 5 concurrent page requests (configurable)
• ✅ Parallel profile fetching – 8 concurrent profile requests (configurable)
• ✅ Progressive CSV export – output.csv updated as data flows in
• ✅ Headless mode – Fast, no GUI overhead

✨ Profile Enrichment

• ✅ City, post code, country
• ✅ Job industry, position, department (IDs → libellés lisibles)
• ✅ Product categories (wanted & offered)
• ✅ Profile image URL

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💼 Use Cases and Client Benefits

🏢 For Wine & Spirits Professionals

The Problem: Manually collecting ProWein Fair Match contacts is tedious. The platform doesn't offer bulk export with full profile data.

The Solution: One-click extraction of all participants with optional enrichment. CSV ready for Excel, Google Sheets, or CRM import.

Client Benefits:

• 📊 Complete database – All visitors and exhibitors in one run
• 💰 Time saved – Hours of manual work → minutes
• 🎯 Qualified leads – Filter by country, user type, product categories
• 📧 Outreach ready – Names, companies, job positions formatted for campaigns

ROI: Save 5–10 hours per fair × $50/hour = $250–500 saved

🤝 For Event Organizers

The Problem: Need attendee lists for post-event follow-up, analytics, or partner sharing.

The Solution: Export all Fair Match participants with enrichment. Segment by EXHIBITOR vs VISITOR, by country, by product interests.

Client Benefits:

• 📈 Analytics – Understand attendee demographics and interests
• 🔗 Networking – Match visitors to exhibitors by product categories
• 📋 Reporting – Ready-made participant database for stakeholders

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📈 Before vs. After

	Before (manual)	After (scraper)
Time	5–10 hours	10–30 minutes
Data completeness	Partial (what you can copy)	100% (all 22k+ participants)
Enrichment	Manual research	Automatic (city, categories)
Format	Scattered	Dataset + CSV

Time saved: ~95%
Speed: 100–500 participants/minute (basic) / 50–200/min (with enrichment)

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💰 Costs and Optimization

Estimated Cost (Apify)

Service	Typical run	Cost
Actor compute	15–60 min	$0.15–0.60
Dataset writes	22,000 items	~$0.22
Total		~$0.40–0.85

💡 Optimization Tips

• Quick test : maxPages: 2, fetchUserDetails: false → ~200 participants en ~2 min
• Extraction rapide : fetchUserDetails: false → ~25 min pour 22k participants
• Données enrichies : fetchUserDetails: true, maxUserDetails: 500 → 500 profils enrichis + reste basique
• Sans login : Fournir jwtToken + ticket pour éviter Puppeteer (économise ~1 min)

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📋 Complete Data Fields

Field	Description	Source
userId	Unique ProWein user ID	Search API
registrationDate	Date/heure inscription (ISO, extrait du userId YYYYMMDDHH-MM-SS)	Derived
userType	EXHIBITOR or VISITOR	Search API
userTypeLabel	Trade visitor / Exhibitor	Derived
firstName	First name	Search API
lastName	Last name	Search API
company	Company name	Search API
profileThumbnailUrl	Small profile image	Search API
city	City	Enrichment
postCode	Postal code	Enrichment
countryId	ISO country code (FR, DE, ES…)	Enrichment
profileImageUrl	Full profile image	Enrichment
jobIndustry	Professional background (e.g. Import / export)	Mapping
jobPosition	Job position (e.g. Entrepreneur, co-owner, freelancer)	Mapping
jobDepartment	Area of responsibility (e.g. Management)	Mapping
categoryLabelsWanted	Product categories sought (readable)	Enrichment + catalogue
categoryLabelsOffered	Product categories offered (readable)	Enrichment + catalogue

Job labels (Professional background, Position, Department)

L’API ne renvoie que des IDs (ex. 1001_02, 1002_04). Le fichier src/job-labels.js contient le mapping vers les libellés. Pour récupérer un ID : appliquer un filtre dans Fair Match, ouvrir DevTools > Network, et regarder le JSON de la requête POST.

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📖 Input Configuration

Minimal (quick test)

{
  "email": "your@prowein.com",
  "password": "your-password",
  "maxPages": 2
}

Full extraction with enrichment

{
  "email": "your@prowein.com",
  "password": "your-password",
  "maxPages": 0,
  "fetchUserDetails": true,
  "maxUserDetails": 0,
  "userTypeFilter": ["EXHIBITOR"],
  "countryFilter": ["FR", "DE"]
}

Parameter Reference

Parameter	Type	Default	Description
email	string	–	ProWein account email
password	string	–	ProWein account password
jwtToken	string	–	Skip login: provide x-jwt-auth token
ticket	string	–	SSO ticket if auto-extraction fails
userTypeFilter	array	[]	EXHIBITOR, VISITOR, or both
countryFilter	array	[]	ISO codes (FR, DE, ES…)
jobPositionFilter	array	[]	IDs (1002_04, 1002_02…) – from Fair Match filters
jobIndustryFilter	array	[]	IDs (1001_20…)
jobDepartmentFilter	array	[]	IDs (1003_04…)
categoryFilter	array	[]	Product IDs (dim.pnb.prod=prowein2026.02)
maxPages	int	0	0 = toutes les pages, 2 ≈ 200 users (test rapide)
pageSize	int	100	Results per API page (50–100)
fetchUserDetails	bool	false	Enable profile enrichment
maxUserDetails	int	0	0 = all, or limit (e.g. 500)
pageConcurrency	int	5	Parallel page requests
profileConcurrency	int	8	Parallel profile requests

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📤 Output

• Dataset: One item per participant (JSON records)
• Key-Value Store: output.csv – Semicolon-separated CSV, updated progressively during the run

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🚀 Installation and Usage

Local

cd prowein-fair-match-scraper
npm install
# Edit input.json with your credentials
npm start

Apify Platform

1. Push: apify push
2. Configure input (email + password, or jwtToken + ticket)
3. Run
4. Download dataset or output.csv from Key-Value Store

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⚠️ Notes

• JWT & Ticket: Tokens expire. For long runs, use email+password and let the scraper obtain them.

Login troubleshooting

If you get "Could not extract JWT" or "Not logged in":

1. Verify credentials manually: Log in at prowein.com/en/Browse_Fair_Match in a normal browser. Ensure you see the participant list, not the login form.

2. Use JWT directly: Open DevTools (F12) → Network → reload Fair Match. Find a request to networking-api.messe-duesseldorf.de → copy the x-jwt-auth header value. Put it in jwtToken input (no need for email/password).

3. Omit ticket: Remove ticket from input to force a fresh flow. Old tickets expire quickly.

4. Headless debug: Set headless: false to watch the browser and see where it fails.

• Ticket extraction: If auto-extraction fails, log in manually, copy the ticket= value from the URL, and add it to input.
• Rate limits: If you get 429 errors, reduce pageConcurrency and profileConcurrency.
• ProWein 2026: ~22,390 participants across ~448 pages. Full extraction: ~25 min (basic) or ~2h (with full enrichment).

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📞 Support

Issues: GitHub Issues or contact the maintainer.

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