We extract global business listings, contact information, category classifications, and operating hours from Cybo. 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 Business Profiles objects from cybo.com. All fields typed and schema-versioned.
"business_id": "CYB-98231", "name": "Apex Industrial Supplies", "primary_category": "Manufacturing", "claimed_status": false, "year_established": 1998, "employee_count": "50-200"
| # | business_id | name | cybo_url | description | primary_category | sub_categories |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Contact Information objects from cybo.com. All fields typed and schema-versioned.
"business_id": "CYB-98231", "phone_primary": "+1-555-019-8472", "email": "contact@apexindustrial.example.com", "website": "https://apexindustrial.example.com", "fax": "+1-555-019-8473", "whatsapp_number": "None"
| # | business_id | phone_primary | phone_secondary | website | fax | |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Location Data objects from cybo.com. All fields typed and schema-versioned.
"business_id": "CYB-98231", "street_address": "1942 Westlake Ave", "city": "Seattle", "state_province": "WA", "postal_code": "98101", "country": "United States", "latitude": 47.6134, "longitude": -122.3381
| # | business_id | street_address | city | state_province | postal_code | country |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Operating Hours objects from cybo.com. All fields typed and schema-versioned.
"business_id": "CYB-98231", "monday": "09:00-17:00", "tuesday": "09:00-17:00", "friday": "09:00-16:00", "saturday": "Closed", "sunday": "Closed", "timezone": "America/Los_Angeles"
| # | business_id | monday | tuesday | wednesday | thursday | friday |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from cybo.com. All fields typed and schema-versioned.
"business_id": "CYB-98231", "average_rating": 4.2, "review_count": 14, "cybo_score": 85, "reviewer_name": "John D.", "rating_value": 5, "review_date": "2023-11-12"
| # | business_id | average_rating | review_count | cybo_score | review_id | reviewer_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Cybo scraper handles directory pagination, category taxonomy parsing, and contact normalisation. We deliver clean business datasets ready for your CRM or analytics tools.
Extract business profiles across 240 countries and territories indexed by Cybo.
Clean extraction of phone numbers, email addresses, and website URLs from raw HTML text nodes.
Capture primary and secondary industry classifications mapped to Cybo's internal taxonomy.
Extract latitude, longitude, and formatted street addresses for mapping and logistics use cases.
Parse unstructured opening hours into clean, queryable daily schedules with timezone normalisation.
Track proprietary Cybo scores and rating metrics for local business reputation analysis.
Extract and normalise data across the 50+ languages supported on regional Cybo domains.
Capture user reviews, star ratings, and publication dates for sentiment analysis pipelines.
Monitor specific directories or categories for new business listings and updated contact details.
Brief in. Clean data out.
Provide target countries, cities, or industry categories. We design the schema to match your requirements.
We configure Scrapy crawlers, proxy rotation, and pagination logic to traverse Cybo's directory structure.
Schema validation, null-rate checks on contact fields, and location accuracy verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Directory scraping requires heavy pagination and strict IP rotation to avoid rate limits. Here is how we maintain throughput.
Cybo categories span thousands of paginated results. We use distributed crawl frontiers to traverse deep category trees without missing listings.
Directory sites aggressively throttle IP addresses making sequential requests. We route traffic through large proxy pools to distribute the load.
Phone numbers and addresses often appear in inconsistent formats. Our pipeline applies regex-based normalisation to standardise outputs.
We use custom HTTP clients that mimic standard browser TLS fingerprints and header orders to bypass basic application firewalls.
For large regional directories, we maintain hash indexes to only extract newly added businesses or updated contact details.
Sales teams use extracted contact details and category classifications to build targeted outbound outreach lists.
Marketing agencies audit Cybo listings to ensure NAP (Name, Address, Phone) consistency for local search optimisation.
Consultancies analyse business density across regions and categories to identify market saturation and expansion opportunities.
CRM administrators append missing phone numbers, websites, and operating hours to existing incomplete business records.
Retailers track competitor locations and reputation scores across specific geographic territories.
Logistics companies use latitude and longitude coordinates to map business clusters and optimise delivery routes.
"Cybo aggregates millions of global business records, but extracting structured contact data requires navigating complex category trees and aggressive rate limits."
Building a reliable directory scraper means handling millions of paginated URLs, normalising inconsistent address formats, and managing proxy rotation at scale. DataFlirt absorbs this infrastructure overhead so your data team can focus on enrichment and analysis.
Everything supported by our cybo.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 and Redis handle distributed URL queues, ensuring high-throughput extraction across millions of directory pages.
We maintain extensive proxy pools to distribute requests globally, preventing IP bans and rate limiting during deep crawls.
Airflow schedules recurring extraction jobs, manages retries, and triggers downstream delivery to your data warehouse.
Data delivered to where your team already works — no new tooling required.
About cybo.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available directory information is generally permissible. DataFlirt targets only public business profiles and contact data, avoiding private user information.
Our schema allows for nullable fields. If a business has not provided an email or website, the field returns as null rather than breaking the pipeline.
Yes. We can configure the crawl frontier to target specific geographic regions, countries, or individual city directories.
Extraction speed depends on the category size and platform rate limits. A typical city-level category completes in minutes, while global categories may take several hours.
Yes. We apply standardisation to phone number strings where possible, though the raw extracted string is also provided for reference.
Yes. We provide a sample dataset of up to 1,000 business records during the scoping phase to ensure the schema meets your requirements.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a targeted list of local businesses or a global directory dump - we scope, build, and operate the pipeline. Tell us what you need.
