We extract flex office listings, hot desk pricing, amenity lists, and operator intelligence from Coworkingmag. 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 Workspace Listings objects from coworkingmag.com. All fields typed and schema-versioned.
"workspace_id": "cw-9482", "name": "WeWork Galaxy", "operator_name": "WeWork", "city": "Bengaluru", "country": "India", "rating": 4.6, "capacity": 1200
| # | workspace_id | name | operator_name | city | country | address |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing Data objects from coworkingmag.com. All fields typed and schema-versioned.
"workspace_id": "cw-9482", "currency": "INR", "hot_desk_daily": 800, "hot_desk_monthly": 12000, "dedicated_desk_monthly": 15000, "private_office_monthly": 45000, "day_pass_available": true
| # | workspace_id | currency | hot_desk_daily | hot_desk_monthly | dedicated_desk_monthly | private_office_monthly |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Amenities & Facilities objects from coworkingmag.com. All fields typed and schema-versioned.
"workspace_id": "cw-9482", "high_speed_wifi": true, "coffee_tea": true, "meeting_rooms": true, "parking": false, "24_7_access": true, "pet_friendly": false
| # | workspace_id | high_speed_wifi | coffee_tea | meeting_rooms | printing | parking |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Operator Profiles objects from coworkingmag.com. All fields typed and schema-versioned.
"operator_id": "op-102", "operator_name": "WeWork", "total_locations": 700, "countries_present": 39, "cities_present": 119, "founded_year": 2010, "headquarters": "New York"
| # | operator_id | operator_name | total_locations | countries_present | cities_present | founded_year |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from coworkingmag.com. All fields typed and schema-versioned.
"review_id": "rv-84721", "workspace_id": "cw-9482", "reviewer_name": "Arjun K.", "rating_overall": 5, "rating_wifi": 5, "rating_community": 4, "review_date": "2023-11-14"
| # | review_id | workspace_id | reviewer_name | rating_overall | rating_wifi | rating_community |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Coworkingmag aggregates thousands of flexible office spaces. We handle the pagination, location filtering, and schema standardisation to deliver clean commercial real estate data.
Extract names, full addresses, operator branding, and geospatial coordinates for every listing.
Capture daily, monthly, and annual rates for hot desks, dedicated desks, and private offices.
Normalise unstructured amenity lists into boolean flags for easy database filtering.
Collect user ratings, textual reviews, and category specific scores for each workspace.
Link individual spaces to parent operators to map market share and footprint.
Extract high resolution gallery images and floor plan links directly from the listing.
Capture latitude and longitude coordinates from embedded maps for spatial analysis.
Extract public phone numbers, emails, and booking URLs where available.
Run weekly or monthly diffs to track pricing changes and new space openings over time.
Brief in. Clean data out.
Provide target cities, countries, or operator names. We design the extraction schema together.
We configure Scrapy crawlers and proxy rotation for coworkingmag.com.
Schema validation, null rate checks, and price outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or warehouse on agreed cadence.
Directory sites present unique extraction challenges. Here is how we ensure high data quality.
Directory sites often limit pagination depth. We use geographic sub category traversal to ensure 100 percent listing coverage across all cities and regions.
Operators list amenities inconsistently. We map custom text strings to a standardised boolean schema, turning unstructured descriptions into queryable columns.
Prices are listed in local currencies. We extract the raw value and currency code separately for downstream normalisation and exchange rate calculations.
Map widgets load coordinates asynchronously. We parse the embedded JSON payloads to extract exact latitude and longitude data without rendering the full map.
We maintain a hash index of workspace profiles. Subsequent runs only push diffs, reducing storage bloat and downstream processing load.
Commercial real estate firms analyse flex office density across different cities.
Workspace operators track competitor pricing and amenity offerings in their target markets.
B2B service providers target coworking operators for software and hardware sales.
Aggregators enrich their own databases with global workspace listings and operator profiles.
Urban planners study the distribution of remote work infrastructure globally.
Private equity firms evaluate operator footprint and expansion velocity for potential acquisitions.
"Coworkingmag holds the most comprehensive map of global flex space. Querying it requires a pipeline built for directory traversal."
Extracting data from directory sites requires navigating complex taxonomy trees and normalising highly unstructured user submitted data. DataFlirt handles the crawling, extraction, and standardisation so your data science team receives clean, queryable tables.
Everything supported by our coworkingmag.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.
Handles crawl depth, deduplication, and retry logic across complex directory trees and geographic categories.
Residential IPs prevent rate limiting during deep pagination crawls across thousands of listings.
AWS Lambda and ECS scale horizontally to process thousands of listings concurrently.
Data delivered to where your team already works — no new tooling required.
About coworkingmag.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available directory information is generally permissible. DataFlirt extracts only public workspace data, pricing, and reviews. We do not extract personal user data or bypass authentication walls.
We use regex mapping and predefined dictionaries to convert custom amenity descriptions into a standard set of boolean flags, ensuring consistent schema across all records.
Yes. We can configure the pipeline to target specific geographic regions, countries, or individual cities based on your requirements.
We typically run these pipelines on a weekly or monthly cadence to track pricing changes over time. Real time extraction is also available for specific target lists.
Yes. We parse the embedded map JSON payloads to extract precise latitude and longitude coordinates for spatial mapping.
We deliver data in JSON, CSV, or Parquet formats directly to your AWS S3 bucket, data warehouse, or via Webhook.
Yes. We provide a sample run of up to 100 listings to validate the schema and data quality before full deployment.
20-minute scoping call. Pilot dataset within the week. Production within two. Need a one off dump of global flex spaces or a continuous pricing feed? We scope, build, and operate the pipeline.
