We extract residential listings, Global Luxury properties, agent directories, and MLS pricing signals from Coldwell Banker. 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 Property Listings objects from coldwellbanker.com. All fields typed and schema-versioned.
"listing_id": "CB-98214", "mls_number": "ML819234", "status": "Active", "price": 1250000, "address": "123 Maple St", "city": "Austin", "beds": 4, "baths": 3
| # | listing_id | mls_number | property_type | status | price | address |
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Complete list of extractable fields for Agent Profiles objects from coldwellbanker.com. All fields typed and schema-versioned.
"agent_id": "AGT-4451", "name": "Sarah Jenkins", "title": "Global Luxury Specialist", "office_name": "CB Realty Austin", "phone_number": "512-555-0198", "active_listings_count": 14, "sold_listings_count": 82
| # | agent_id | name | title | office_name | office_address | phone_number |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Office Directory objects from coldwellbanker.com. All fields typed and schema-versioned.
"office_id": "OFF-992", "office_name": "Coldwell Banker Realty", "city": "Beverly Hills", "state": "CA", "agent_count": 145, "managing_broker": "Michael Scott", "phone": "310-555-0144"
| # | office_id | office_name | brokerage_type | address | city | state |
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Complete list of extractable fields for Market & Pricing objects from coldwellbanker.com. All fields typed and schema-versioned.
"listing_id": "CB-98214", "current_price": 1250000, "original_price": 1300000, "price_reductions": 1, "cb_estimate": 1265000, "tax_assessed_value": 1150000, "price_per_sqft": 450
| # | listing_id | current_price | original_price | price_reductions | last_reduction_date | last_reduction_amount |
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Complete list of extractable fields for Open Houses objects from coldwellbanker.com. All fields typed and schema-versioned.
"listing_id": "CB-98214", "event_date": "2024-05-18", "start_time": "13:00", "end_time": "16:00", "hosting_agent": "Sarah Jenkins", "virtual_tour_available": true, "city": "Austin"
| # | listing_id | address | city | state | zip | price |
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Our real estate scraper handles every layer of the platform: property listings, agent directories, map interfaces, and historical pricing signals — with JavaScript rendering, session management, and anti bot circumvention built in.
Capture beds, baths, square footage, lot size, year built, and MLS descriptions across all active and pending properties.
Isolate high net worth properties listed under the Coldwell Banker Global Luxury banner with specific amenity details.
Extract agent names, contact details, license numbers, spoken languages, and historical transaction volume.
Monitor proprietary Coldwell Banker property valuations alongside actual listing prices to identify market gaps.
Bypass viewport limitations to extract all listings within a geographical bounding box, not just visible map pins.
Log initial list price, reduction events, timestamps, and current asking price to track seller motivation.
Aggregate upcoming open house dates, times, and hosting agents for targeted local market analysis.
Map the entire Coldwell Banker franchise network including office locations, managing brokers, and agent rosters.
Extract primary and gallery image URLs without downloading heavy assets, optimising pipeline speed.
Capture granular financial details including monthly HOA dues, annual property taxes, and tax assessed values.
Brief in. Clean data out.
Provide target zip codes, cities, or agent criteria. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and anti bot circumvention for coldwellbanker.com.
Schema validation, null rate checks, and geospatial outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Real estate platforms invest heavily in scraping detection. Here is how we stay resilient — and why teams choose managed infrastructure over DIY.
Real estate sites deploy strict WAF rules. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing to bypass PerimeterX and Cloudflare WAFs.
Coldwell Banker caps map results to a few hundred pins. We programmatically subdivide large bounding boxes into micro grids to ensure 100 percent listing extraction without truncation.
Listing details and CB Estimates load asynchronously. We run full Playwright browser sessions to hydrate dynamic widgets and capture data that headless HTTP clients miss entirely.
DOM structures change frequently. Our selector strategy uses multiple fallback chains per field so a layout update does not break your data pipeline overnight.
For large property catalogues, we maintain a hash index of last seen values per listing. Subsequent runs only push price drops or status changes, reducing downstream load.
PropTech companies aggregate listing data to train automated valuation models and identify emerging market trends.
Competing brokerages track high performing agents based on active listing volume and transaction history for targeted recruitment.
Investors monitor days on market and price reduction velocity to identify motivated sellers and distressed assets.
Lenders track new listings and open houses to target potential buyers with pre approval offers.
Home staging, photography, and moving companies monitor new listings to pitch services to selling agents.
Regional MLS portals and aggregator apps sync Coldwell Banker data to maintain comprehensive market coverage.
"Coldwell Banker holds a vast repository of premium real estate data, but extracting it requires navigating aggressive bot protection and dynamic map interfaces."
Most teams underestimate the investment required. Reliable real estate scraping requires residential proxies, full JavaScript rendering, micro grid map traversal, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on property analysis.
Everything supported by our coldwellbanker.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 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 coldwellbanker.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available property listings and agent directories is generally permissible under applicable law in the US. DataFlirt targets only public, non authenticated data. We do not extract personal user data or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We bypass strict WAF rules commonly deployed by real estate brokerages.
Yes. We accept input lists of zip codes, cities, counties, or custom geospatial bounding boxes to target specific real estate markets.
Real time streaming pipelines achieve sub 60 minute latency for new listings and price changes in defined markets. Full national catalogue refreshes complete within a 12 to 24 hour window depending on scale.
Yes. We capture the proprietary Coldwell Banker Estimate alongside the actual listing price, tax assessed value, and historical price reductions.
Our smallest packages start at a defined regional scope (typically 10,000 to 50,000 listings) with daily delivery. For national coverage, we price based on volume and delivery frequency.
Absolutely. We provide a sample run of up to 500 listings or 50 agent profiles as part of the pre engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a regional agent directory or a continuous price monitoring feed across national listings, we scope, build, and operate the pipeline. Tell us what you need.
