We extract residential listings, commercial properties, agent directories, and office intelligence from Century21. 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 century21.com. All fields typed and schema-versioned.
"listing_id": "C21-8849201", "mls_number": "ML8192039", "price": 850000.0, "address": "123 Maple Street", "beds": 4, "baths": 3.0, "sqft": 2450, "status": "Active"
| # | listing_id | mls_number | property_type | price | currency | address |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Agent Profiles objects from century21.com. All fields typed and schema-versioned.
"agent_id": "AGT-39201", "first_name": "Sarah", "last_name": "Jenkins", "phone_number": "+1-555-019-2834", "languages": "['English', 'Spanish']", "active_listings_count": 14, "office_id": "OFF-9920"
| # | agent_id | first_name | last_name | title | office_id | phone_number |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Office Directories objects from century21.com. All fields typed and schema-versioned.
"office_id": "OFF-9920", "office_name": "Century 21 Real Estate Center", "city": "Seattle", "state": "WA", "agent_count": 42, "phone": "+1-555-882-1192", "broker_name": "David Chen"
| # | office_id | office_name | broker_name | address | city | state |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Open Houses objects from century21.com. All fields typed and schema-versioned.
"listing_id": "C21-8849201", "address": "123 Maple Street", "open_house_date": "2026-06-14", "start_time": "13:00", "end_time": "16:00", "agent_id": "AGT-39201", "price": 850000.0
| # | listing_id | address | city | state | price | open_house_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Historical Pricing objects from century21.com. All fields typed and schema-versioned.
"listing_id": "C21-8849201", "current_price": 850000.0, "original_price": 890000.0, "price_drop_pct": 4.5, "days_on_market": 24, "list_date": "2026-05-21", "status_changes": 1
| # | listing_id | mls_number | current_price | original_price | price_drop_amount | price_drop_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Century21 scraper handles every layer of the platform: property listings, agent directories, geospatial map parsing, and price reduction tracking, with anti-bot circumvention built in.
Beds, baths, sqft, lot size, year built, and full property descriptions parsed into structured types.
Extract agent directories, contact numbers, spoken languages, and active listing counts per office.
Cross-reference Century21 listings with local MLS identifiers for downstream normalisation.
Track upcoming open house dates, times, and associated agent contact details.
Monitor original list price versus current price to calculate discount percentages and days on market.
Filter and extract specialised property categories including Century21 Commercial and Fine Homes & Estates.
Extract latitude and longitude data for precise mapping and spatial analysis.
Capture arrays of image URLs and virtual tour links associated with each property.
Target specific states, ZIP codes, or radii to isolate regional real estate markets.
Run daily or weekly pipelines to catch new listings, pending sales, and sold statuses.
Brief in. Clean data out.
Provide ZIP codes, cities, or agent directories. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and session management for century21.com.
Schema validation, null-rate checks, and geospatial coordinate verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Real estate aggregators invest heavily in scraping detection. Here is how we stay resilient.
Real estate sites monitor request velocity. We use residential ISP proxies with realistic browser fingerprints and randomised request timing to prevent IP bans.
Century21 relies on map-boundary API calls. We reverse-engineer the bounding box requests to paginate through high-density urban areas without missing listings.
DOM structures for listings vary by property type. Our selector strategy uses multiple fallback chains per field so a layout change does not break your pipeline.
For large state-wide catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and storage bloat.
Every run emits structured logs to our observability stack. We alert on null-rate spikes and coverage drops, responding before you notice.
Identify underpriced properties, track days on market, and calculate price per square foot across target ZIP codes.
Enrich existing real estate platforms with normalised listing data, agent profiles, and MLS identifiers.
Brokerages track top-performing Century21 agents based on active listing volume and geographic dominance.
Analyse inventory levels, average listing prices, and price reduction frequencies to predict local market shifts.
Extract office directories and broker contact information for B2B real estate service sales.
Feed recent listing data and property characteristics into automated valuation models.
"Century21 holds critical inventory and agent performance data, but extracting it requires navigating complex geospatial map APIs and strict rate limits."
Most teams underestimate the investment required: reliable real estate scraping requires residential proxies, map bounding-box pagination, 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 century21.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 map interactions.
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, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About century21.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available real estate listings is generally permissible under applicable law. DataFlirt targets only public, non-authenticated property and agent data. Clients should review Century21 Terms of Service and consult legal counsel for specific use cases.
We reverse-engineer the underlying API calls using bounding box coordinates to ensure we capture all listings in high-density areas without missing records due to map zoom limits.
Yes, we extract public office numbers, emails where visible, and associated broker details from the agent directory pages.
Pipelines can be configured to run daily or sub-daily to capture new listings, price changes, and sold statuses rapidly.
We extract the high-resolution image URLs. We do not host the image binaries by default, but can configure download pipelines if required.
Yes. Every pipeline run produces timestamped snapshots. We maintain a time-series record per listing to track original price versus current price.
Our smallest packages start at defined geographic regions, typically at the state or major metro level, with weekly or daily delivery cadences.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a specific zip code export or a continuous national property feed, we scope, build, and operate the pipeline. Tell us what you need.
