We extract business listings, executive contacts, NAICS categorisation, and consumer demographics from InfoUSA. 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 Listings objects from infousa.com. All fields typed and schema-versioned.
"company_name": "Apex Manufacturing Solutions", "city": "Chicago", "state": "IL", "zip_code": "60601", "phone_number": "312-555-0198", "naics_code": "332710", "employee_count_range": "50-99", "revenue_estimate": "10M-50M"
| # | company_name | address_line_1 | city | state | zip_code | phone_number |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Executive Contacts objects from infousa.com. All fields typed and schema-versioned.
"first_name": "Sarah", "last_name": "Jenkins", "job_title": "Vice President of Operations", "department": "Operations", "management_level": "VP", "company_name": "Apex Manufacturing Solutions", "phone_direct": "312-555-0199"
| # | first_name | last_name | job_title | department | management_level | company_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Consumer Demographics objects from infousa.com. All fields typed and schema-versioned.
"zip_code": "90210", "household_income_range": "150K+", "home_value_estimate": "1M+", "marital_status": "Married", "age_range": "45-54", "homeowner_status": "Owner", "length_of_residence": "10+ years"
| # | zip_code | household_income_range | home_value_estimate | marital_status | age_range | presence_of_children |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Industry Categorisation objects from infousa.com. All fields typed and schema-versioned.
"company_id": "IU-9823471", "naics_code": "541511", "naics_description": "Custom Computer Programming Services", "sic_code": "7371", "primary_industry": "Technology", "franchise_status": false, "public_company_flag": false
| # | company_id | naics_code | naics_description | sic_code | sic_description | primary_industry |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Location & GIS Data objects from infousa.com. All fields typed and schema-versioned.
"company_id": "IU-9823471", "latitude": 41.881832, "longitude": -87.623177, "county": "Cook", "building_type": "Commercial Office", "square_footage": "10,000-24,999", "location_type": "Headquarters"
| # | company_id | latitude | longitude | county | cbsa_code | neighborhood |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our InfoUSA scraper navigates complex search interfaces, deep pagination, and aggressive rate limits to deliver structured B2B and B2C data directly to your warehouse.
Extract company name, address, phone numbers, website URLs, and year established across millions of directory listings.
Capture key decision-makers, job titles, management levels, and direct dial numbers associated with business profiles.
Retrieve precise industry classifications, primary codes, and secondary operational categories for granular market segmentation.
Scrape aggregated consumer data including household income ranges, home values, marital status, and lifestyle interests.
Extract latitude, longitude, county codes, and CBSA data for precise geographic heatmapping and territory planning.
Capture estimated revenue brackets, employee count ranges, and public versus private company flags.
Identify headquarters, branch locations, and franchise affiliations to map out corporate hierarchies.
Monitor directory additions, defunct business removals, and executive turnover with hash-based diffing.
Bypass search result limits by programmatically iterating through geographic and industry sub-categories.
Brief in. Clean data out.
Provide target geographies, NAICS codes, or consumer demographic parameters. We design the extraction schema.
We configure Scrapy crawlers, residential proxy rotation, and session management to navigate InfoUSA search interfaces.
Schema validation, null-rate checks, and data normalisation routines run before full pipeline activation.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Directory sites deploy aggressive rate limiting and complex session states. Here is how we maintain reliable extraction.
InfoUSA limits search results to a fixed number of pages. We bypass this by automatically splitting large queries into smaller geographic or alphabetical grids, ensuring 100% coverage of the target dataset without hitting display ceilings.
Directory sites aggressively block datacentre IPs. We route all requests through US-based residential proxy networks, rotating IPs per request or maintaining sticky sessions where required to mimic normal user browsing behaviour.
Search queries often rely on complex, short-lived session cookies. Our Playwright integration handles cookie generation, token refresh cycles, and session persistence to keep extraction flows uninterrupted.
Directory data can be messy. We apply post-processing layers to normalise address formats, standardise job titles, and clean revenue ranges before the data hits your warehouse.
When automated traffic triggers CAPTCHA walls, our pipeline routes challenges to integrated solver APIs, resolving them in milliseconds without manual intervention.
Sales teams feed enriched business directories and executive contacts directly into their CRM for outbound campaigns.
Strategy teams aggregate NAICS codes, revenue estimates, and employee counts to calculate total addressable market size.
Revenue operations use geographic density and firmographic data to draw balanced sales territories.
Marketers extract precise consumer demographics and validated addresses to execute highly targeted direct mail operations.
Retailers track competitor locations and franchise expansions using structured GIS and directory data.
Investors analyse industry fragmentation, regional market concentration, and company longevity to evaluate acquisition targets.
"InfoUSA holds one of the most comprehensive business and consumer directories in North America, but extracting it at scale requires navigating aggressive rate limits and complex search interfaces."
Building a reliable InfoUSA extraction pipeline requires managing session state, bypassing CAPTCHAs, and handling thousands of paginated search results without triggering IP bans. DataFlirt handles the infrastructure complexity so your data engineers can focus on integrating the records into your CRM or data warehouse.
Everything supported by our infousa.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 manages search form interactions, session cookies, and dynamic content rendering.
We maintain large pools of US residential proxies. Rotation happens per request with sticky sessions to maintain search state without triggering blocks.
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 infousa.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly accessible directory information is generally permissible under applicable law, reinforced by the hiQ v. LinkedIn ruling. DataFlirt extracts only public, non-authenticated business and demographic data. We do not bypass payment gateways to access gated premium lists. Clients must ensure their use of the data complies with local marketing regulations such as CAN-SPAM or CCPA.
We distribute requests across thousands of US residential IPs, mimicking human browsing patterns with randomised request delays. We also manage session cookies dynamically to prevent token expiration blocks.
Yes. We extract visible executive names, job titles, and associated direct dial numbers as they appear on the public business profile pages.
We extract aggregated demographic data tied to zip codes and public records, including household income ranges and home value estimates. We do not extract gated personal contact information.
Our pipelines extract the live data exactly as it appears on InfoUSA at the time of the crawl. We can configure weekly or monthly runs to capture updates and new directory additions.
Yes. We provide a sample run of up to 1,000 business records based on your specific NAICS codes or geographic targets to validate schema fit before contract signature.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a targeted list of 10,000 manufacturers or a continuous sync of US consumer demographics, we build and operate the pipeline. Tell us your criteria.
