We extract venue listings, pricing packages, capacity matrices, and reviews from weddingvenues.com. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Venue Profiles objects from weddingvenues.com. All fields typed and schema-versioned.
"venue_id": "WV-84921", "name": "The Glasshouse Estate", "type": "Estate", "capacity_min": 50, "capacity_max": 350, "price_range": "$$$", "rating": 4.8, "review_count": 142
| # | venue_id | name | type | style | capacity_min | capacity_max |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Packages objects from weddingvenues.com. All fields typed and schema-versioned.
"venue_id": "WV-84921", "package_name": "Premium Summer Package", "price_per_head": 185.0, "minimum_spend": 15000.0, "deposit_required": 5000.0, "tax_rate": 8.5, "service_charge": 20.0
| # | venue_id | package_name | price_per_head | minimum_spend | deposit_required | inclusions |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Amenities & Facilities objects from weddingvenues.com. All fields typed and schema-versioned.
"venue_id": "WV-84921", "indoor_capacity": 200, "outdoor_capacity": 350, "dance_floor": true, "parking_spaces": 120, "wheelchair_accessible": true, "catering_type": "In-house mandatory", "alcohol_policy": "BYO allowed with corkage"
| # | venue_id | indoor_capacity | outdoor_capacity | dance_floor | parking_spaces | wheelchair_accessible |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from weddingvenues.com. All fields typed and schema-versioned.
"review_id": "REV-993821", "venue_id": "WV-84921", "author_name": "Sarah Jenkins", "rating_overall": 5, "rating_service": 5, "rating_value": 4, "date_posted": "2023-08-14", "event_date": "2023-07-22"
| # | review_id | venue_id | author_name | rating_overall | rating_service | rating_value |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from weddingvenues.com. All fields typed and schema-versioned.
"keyword": "barn wedding", "location": "Austin, TX", "position": 3, "venue_id": "WV-44219", "name": "Rustic Oaks Farm", "price_tier": "$$", "rating": 4.6, "review_count": 89, "promoted_badge": false
| # | keyword | location | position | venue_id | name | price_tier |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our scraper handles every layer of the platform: venue listings, dynamic pricing matrices, capacity rules, and the review corpus - with JavaScript rendering and anti-bot circumvention built in.
Name, description, capacity limits, property styles, and location metadata extracted at the individual venue level.
Capture per-head costs, minimum spend requirements, seasonal variations, and specific package inclusions.
Extract structured lists of facilities, indoor versus outdoor limits, parking availability, and accessibility features.
Full review text, category ratings, event dates, and management responses paginated across all review pages.
Exact address details, region categorisation, and map coordinates for spatial analysis and routing.
Track organic versus promoted position for any location and venue style combination.
Monitor calendar blocks, booking lead times, and seasonal closure dates where surfaced.
Extract image URLs, gallery counts, and virtual tour links associated with each venue.
Run continuous pipelines at weekly or monthly cadences to capture new venues and pricing adjustments.
Brief in. Clean data out.
Provide target regions, venue styles, or specific URLs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for weddingvenues.com.
Schema validation, null-rate checks, and data normalisation before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Aggregators invest heavily in scraping detection. Here is how we stay resilient - and why teams choose managed infrastructure over DIY.
Venue platforms block datacentre IPs rapidly. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management.
Pricing matrices and availability calendars are heavily JavaScript-rendered. We run full Playwright browser sessions to capture data headless clients miss.
DOM structures change frequently. Our selector strategy uses multiple fallback chains per field so a layout update does not break your pipeline.
Venue pricing and capacity text varies wildly. We parse and normalise ranges, currencies, and amenity lists into strict data types.
Every run emits structured logs. We alert on null-rate spikes and coverage drops, responding before you notice.
Venue operators track local competitor pricing, package inclusions, and promotional offers to optimise their own rates.
Hospitality groups analyse venue density, average ratings, and capacity limits to identify underserved regions for new acquisitions.
Caterers, photographers, and event planners extract new venue listings to build targeted B2B outreach campaigns.
Industry analysts track changes in venue styles, popular amenities, and pricing shifts to publish market reports.
Niche wedding directories supplement their own databases with normalised profile and amenity data.
Service agencies aggregate review text to identify common complaints and train hospitality staff on critical success factors.
"Weddingvenues.com holds the definitive catalogue of event spaces and pricing matrices, but querying it requires dedicated extraction infrastructure."
Venue aggregators deploy strict rate limits and dynamic DOM structures. DataFlirt handles the proxy rotation, JavaScript execution, and schema maintenance so your engineers focus on data modelling rather than pipeline repairs.
Everything supported by our weddingvenues.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and retry logic. Playwright handles JavaScript rendering and interaction flows.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management.
Data delivered to where your team already works — no new tooling required.
About weddingvenues.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible. DataFlirt targets only public, non-authenticated venue profiles, pricing, and reviews. We do not circumvent authentication walls or extract private user data.
We use residential ISP proxies, realistic browser fingerprints, and request timing modelled on human behaviour to avoid triggering rate limits.
Full catalogue refreshes typically complete within a 24-hour window depending on target region size. Incremental updates can run daily.
Yes. We extract package names, per-head costs, minimum spends, and detailed inclusions lists where the venue provides them publicly.
Yes. We separate indoor and outdoor capacities, seated versus standing limits, and output them as strict integer fields.
Our packages start at a defined region list with monthly delivery. Contact us with your specific data requirements for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off region export or continuous price monitoring across 10,000 venues - we scope, build, and operate the pipeline. Tell us what you need.
