We extract vendor directories, venue specifications, pricing tiers, and review corpora from The Knot. 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 Venues objects from theknot.com. All fields typed and schema-versioned.
"venue_id": "V-982734", "name": "The Grand Estate", "location_city": "Austin", "location_state": "TX", "capacity_max": 250, "price_tier": "$$$", "rating": 4.9, "review_count": 142, "best_of_weddings_winner": true
| # | venue_id | name | location_city | location_state | capacity_max | price_tier |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Vendors objects from theknot.com. All fields typed and schema-versioned.
"vendor_id": "P-44512", "name": "Lumina Photography", "category": "Photographers", "location": "Denver, CO", "rating": 5.0, "review_count": 87, "starting_price": 2500.0, "response_time": "Within 24 hours"
| # | vendor_id | name | category | location | rating | review_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews objects from theknot.com. All fields typed and schema-versioned.
"review_id": "R-9928173", "vendor_id": "V-982734", "author_name": "Sarah J.", "review_date": "2026-03-14", "wedding_date": "2025-10-12", "rating": 5, "review_text": "Absolutely stunning venue with incredible staff.", "helpful_votes": 12
| # | review_id | vendor_id | author_name | review_date | wedding_date | rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Services objects from theknot.com. All fields typed and schema-versioned.
"vendor_id": "P-44512", "service_type": "Full Day Coverage", "base_price": 3500.0, "deposit_required": "50%", "travel_policy": "Included within 50 miles", "cancellation_policy": "Non-refundable deposit", "custom_options": "['Second shooter', 'Drone footage']"
| # | vendor_id | service_type | base_price | package_details | deposit_required | travel_policy |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from theknot.com. All fields typed and schema-versioned.
"keyword": "florist", "location": "Seattle, WA", "position": 3, "vendor_id": "F-11234", "name": "Evergreen Blooms", "sponsored": false, "best_of_weddings_badge": true, "scraped_at": "2026-05-12T10:15:00Z"
| # | keyword | location | position | vendor_id | name | rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our pipeline extracts structured data across The Knot vendor directories, capturing deep profiles, pricing matrices, and historical reviews while managing location-based routing and heavy JavaScript rendering.
Extract max capacities, setting types, included amenities, and tier-based pricing for thousands of event spaces.
Capture contact details, response times, starting prices, and service categories across photographers, planners, and caterers.
Extract full review text, wedding dates, star ratings, and vendor responses across paginated review histories.
Monitor Best of Weddings and Hall of Fame badge assignments to identify top-performing vendors in specific locales.
Simulate searches across thousands of zip codes and metropolitan areas to map true vendor density and market saturation.
Extract base rates, deposit requirements, and package inclusions hidden within vendor FAQ and pricing sections.
Capture image URLs, video links, and gallery structures to analyse vendor presentation and style categories.
Track organic versus sponsored position for vendor categories by city to analyse local advertising spend.
Run continuous pipelines that only emit records when a vendor updates pricing, adds reviews, or changes availability.
Brief in. Clean data out.
Provide target cities, vendor categories, or specific profile URLs. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and location spoofing for theknot.com.
Schema validation, null-rate checks, and sample review datasets are verified before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
The Knot relies on heavy client-side rendering and location-based request routing. Here is how we extract reliable data at scale.
Vendor profiles on The Knot load pricing, FAQs, and reviews dynamically via JavaScript. We run full Playwright browser sessions to hydrate these components, capturing data that standard HTTP clients miss.
The Knot alters search results based on user IP and session location data. We inject specific geolocation coordinates into the browser context and use region-matched residential proxies to extract accurate local directories.
Category searches often cap at a specific number of pages. We segment searches by granular zip codes and sub-categories to force the platform to expose the entire underlying vendor database without truncation.
Aggressive scraping triggers rate limits and CAPTCHAs. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing to maintain high throughput.
Directory layouts change frequently. Our selector strategy uses multiple fallback chains per field, including structured data extraction, to ensure pipeline stability when DOM structures shift.
Venues and hospitality groups monitor local competitor pricing, capacity limits, and amenity offerings to optimise their own packages.
Software vendors and wholesale suppliers extract contact details to pitch CRM, inventory, or booking solutions to wedding professionals.
Real estate and hospitality investors analyse vendor density and review velocity to identify underserved metropolitan areas for new venue development.
Agencies mine historical reviews to understand what couples value most in specific vendor categories, guiding marketing strategies.
Marketing firms track sponsored placements across zip codes to estimate local advertising spend and market saturation.
Event planners aggregate base prices and package tiers across regions to build accurate budget estimation models for clients.
"The wedding industry is highly fragmented. The Knot centralises this market, providing the definitive dataset for local service pricing and vendor reputation."
Extracting this data requires handling complex location-based routing, heavy client-side rendering, and aggressive bot mitigation. DataFlirt manages the proxy rotation, JavaScript execution, and schema maintenance so your team can focus entirely on market analysis and lead generation.
Everything supported by our theknot.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 deduplication. Playwright handles JavaScript rendering and location spoofing. Combined via custom middleware.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required to maintain stable geolocation contexts.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About theknot.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available vendor directories and reviews is generally permissible. DataFlirt targets only public, non-authenticated directory data. We do not extract personal data from private wedding websites or circumvent authentication walls. Clients should review platform terms of service and consult legal counsel.
We use a combination of precise search queries, browser geolocation injection via Playwright, and region-matched residential proxies to ensure we extract the exact directory presented to users in specific metropolitan areas.
Yes. When a broad search hits a pagination limit, our orchestration engine automatically segments the query into smaller geographic units, such as specific zip codes, to extract the full underlying dataset without truncation.
Full directory refreshes for specific metropolitan areas typically complete within 24 hours. Change-detection pipelines can run daily or weekly to capture new reviews, pricing updates, and award changes.
We extract all metadata, descriptions, and high-resolution image URLs from public vendor portfolios. We do not download the actual image files, but provide the direct URLs for your systems to process.
Our smallest packages start at defined city or category lists with weekly delivery. For national coverage or custom schema requirements, we price based on volume and delivery frequency.
Yes. We provide a sample run of up to 500 vendor profiles across your target categories as part of the scoping process, allowing you to validate schema fit and data quality before committing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off vendor directory dump or continuous tracking of local pricing and reviews, we scope, build, and operate the pipeline. Tell us what you need.
