We extract vendor listings, pricing signals, Couples Choice Awards, review corpora, and FAQs from WeddingWire. 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 Vendor Storefronts objects from weddingwire.com. All fields typed and schema-versioned.
"vendor_id": "WW-VEN-98421", "name": "The Grand Estate", "category": "Wedding Venues", "location": "Austin, TX", "rating": 4.9, "review_count": 142, "price_tier": "$$$", "capacity": 300, "awards": "['Couples Choice 2024']"
| # | vendor_id | name | category | location | rating | review_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Packages objects from weddingwire.com. All fields typed and schema-versioned.
"vendor_id": "WW-VEN-98421", "base_price": 5500.0, "price_unit": "per event", "package_name": "Gold Weekend Package", "deposit_required": "50%", "minimum_guest_count": 100, "included_services": "['Tables', 'Chairs', 'Linens', 'Lighting']"
| # | vendor_id | base_price | price_unit | package_name | included_services | deposit_required |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Vendor Reviews objects from weddingwire.com. All fields typed and schema-versioned.
"review_id": "REV-8849201", "vendor_id": "WW-VEN-98421", "reviewer_name": "Sarah J.", "rating": 5.0, "review_date": "2025-10-12", "wedding_date": "2025-09-28", "helpful_votes": 14, "services_used": "['Ceremony', 'Reception']"
| # | review_id | vendor_id | reviewer_name | rating | review_date | wedding_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Venue Amenities objects from weddingwire.com. All fields typed and schema-versioned.
"vendor_id": "WW-VEN-98421", "venue_type": "Estate / Mansion", "indoor_capacity": 150, "outdoor_capacity": 300, "catering_options": "['In-house', 'Preferred list']", "alcohol_policy": "BYO allowed with licensed bartender", "parking_available": true, "curfew_time": "23:00"
| # | vendor_id | venue_type | indoor_capacity | outdoor_capacity | catering_options | alcohol_policy |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Rankings objects from weddingwire.com. All fields typed and schema-versioned.
"keyword": "wedding photographers", "location_slug": "austin-tx", "rank_position": 3, "vendor_id": "WW-PHO-11234", "vendor_name": "Lumina Photography", "sponsored_badge": false, "rating": 4.8, "scraped_at": "2026-02-14T08:12:00Z"
| # | keyword | location_slug | rank_position | vendor_id | vendor_name | sponsored_badge |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our WeddingWire scraper handles every layer of the platform: vendor storefronts, dynamic pricing packages, location-based rankings, and the review corpus. We manage the infrastructure, circumvent anti-bot systems, and deliver structured data.
Extract business names, contact details, categories, descriptions, capacity limits, and external website links for every vendor in a specified region.
Capture base prices, tier definitions, minimum guest counts, and included amenities from vendor pricing tabs.
Extract historical award data to identify top-performing vendors and track consistency over multiple wedding seasons.
Extract full review text, ratings, wedding dates, and vendor responses paginated across all review pages.
Extract structured boolean and categorical data regarding indoor/outdoor spaces, catering policies, and accessibility.
Track organic versus sponsored positions for specific vendor categories across targeted geographic markets.
Extract data from US, UK, Canada, and India storefronts using a unified, normalised schema.
Extract image counts, video links, and gallery metadata to gauge vendor activity and portfolio depth.
Run continuous pipelines that only emit diffs for new reviews, pricing updates, or newly listed vendors.
Brief in. Clean data out.
Provide geographic regions, vendor categories, or specific storefront URLs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for weddingwire.com.
Schema validation, null-rate checks, and data normalisation testing before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
WeddingWire employs strict rate limiting and dynamic rendering. Here is how we stay resilient and why teams choose managed infrastructure.
WeddingWire monitors request velocity and IP reputation. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing, trained on real user behaviour patterns.
Vendor storefronts and pricing widgets often rely on client-side rendering. We run full Playwright browser sessions to hydrate the DOM, capturing data that headless HTTP clients miss entirely.
DOM structures change without notice. Our selector strategy uses multiple fallback chains per field, including CSS selectors, XPath, and JSON-LD structured data extraction.
For large vendor catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, schema drift, and coverage drops, responding before you notice.
Event planning agencies and venue investors analyze regional vendor density, average pricing, and capacity constraints.
Wedding vendors and hospitality groups track competitor pricing tiers, package inclusions, and discount strategies.
B2B software companies targeting the wedding industry extract vendor contact details, website URLs, and operational scale.
Machine learning teams use the vast corpus of wedding reviews to train sentiment analysis models and recommendation engines.
Private equity firms evaluate venue popularity, review velocity, and award history to assess potential acquisitions.
Niche event directories syndicate basic vendor information and ratings to bootstrap their own marketplace supply.
"WeddingWire holds the definitive graph of wedding vendor pricing, availability, and reputation data, but it remains siloed until you build the pipeline."
Most teams underestimate the investment required: reliable WeddingWire scraping requires residential proxies, full JavaScript rendering, CAPTCHA handling, daily selector maintenance, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our weddingwire.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, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across US/UK/CA regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About weddingwire.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from WeddingWire is generally permissible under applicable law. DataFlirt targets only public, non-authenticated vendor storefronts, pricing, and reviews. We do not extract personal user data or private messages. Clients should review WeddingWire terms of service and consult legal counsel for specific use cases.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for rate limits in real time and trigger pool rotation automatically.
We support data extraction across all major WeddingWire locales, including the US, Canada, UK, and India, normalising the data into a unified schema regardless of the source region.
We can configure pipelines to run at daily, weekly, or monthly cadences. A full regional catalogue refresh typically completes within a 4-8 hour window depending on category size.
We extract exactly what the vendor publishes on their storefront. While many vendors provide explicit base prices and PDF attachments, some list 'Starting At' prices or require custom quotes. We capture the exact string and structure provided.
Our smallest packages start at a defined regional or category list (typically 5,000-20,000 vendors) with weekly delivery. We price based on volume and delivery frequency.
Yes. We paginate through all historical reviews for a vendor, capturing the complete text, rating, date, and any responses from the vendor.
Yes. We provide a sample run of up to 200 vendors in a specific category and region as part of the pre-engagement scoping process.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off extraction of US wedding venues or a continuous monitor of vendor pricing changes, we scope, build, and operate the pipeline. Tell us what you need.
