We extract contractor directories, verified reviews, license credentials, and local project cost guides from Angi. 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 Contractor Profiles objects from angi.com. All fields typed and schema-versioned.
"contractor_id": "A-12345", "business_name": "Apex Roofing", "category": "Roofing", "phone_number": "+1-555-0198", "city": "Austin", "state": "TX", "overall_rating": 4.8, "angi_certified": true
| # | contractor_id | business_name | category | phone_number | website_url | street_address |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from angi.com. All fields typed and schema-versioned.
"review_id": "R-98765", "contractor_id": "A-12345", "rating": 5.0, "project_type": "Roof Replacement", "review_text": "Excellent work and cleanup.", "verified_purchase": true, "review_date": "2026-03-14"
| # | review_id | contractor_id | reviewer_name | review_date | rating | project_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Project Cost Guides objects from angi.com. All fields typed and schema-versioned.
"project_category": "Asphalt Shingle Roof", "zip_code": "78701", "average_cost": 8500.0, "low_end_cost": 5200.0, "high_end_cost": 12400.0, "last_updated": "2026-01-10T00:00:00Z"
| # | guide_id | project_category | zip_code | city | state | average_cost |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Credentials & Licenses objects from angi.com. All fields typed and schema-versioned.
"contractor_id": "A-12345", "credential_type": "State Roofing License", "license_number": "TX-R-88291", "status": "Active", "insurance_verified": true, "verification_date": "2026-04-01"
| # | contractor_id | credential_type | license_number | issuing_authority | issue_date | expiration_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from angi.com. All fields typed and schema-versioned.
"search_term": "plumber", "zip_code": "78701", "position": 1, "contractor_id": "P-99210", "sponsored_placement": true, "angi_certified_badge": true, "scraped_at": "2026-05-12T10:00:00Z"
| # | search_term | zip_code | position | contractor_id | business_name | rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Angi scraper handles location-based directory traversal, review pagination, and dynamic contact detail rendering with session management and anti-bot circumvention built in.
Capture business names, categories, contact details, and ratings across all home service verticals.
Extract complete review histories, including project types, costs, text bodies, and contractor responses.
Scrape local pricing guides for specific project types across 41,000 US zip codes.
Capture license numbers, issuing bodies, and background check statuses for compliance teams.
Extract exact zip codes and municipal boundaries where contractors operate.
Track organic versus sponsored positions for specific trades in target zip codes.
Execute JavaScript to reveal hidden phone numbers and email addresses protected by DOM manipulation.
Monitor badge status changes and certification criteria compliance over time.
Run daily, weekly, or monthly diffs to track new market entrants and review velocity.
Brief in. Clean data out.
Provide zip codes, trade categories, or specific contractor URLs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for angi.com.
Schema validation, null-rate checks, location accuracy validation, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Directory scraping requires systematic location spoofing and bot mitigation. Here is how we stay resilient.
Angi employs bot protection heuristics. Our crawlers use US residential ISP proxies with realistic browser fingerprints and full cookie session management to bypass Datadome and Cloudflare challenges.
Search results on Angi are strictly geo-fenced. We inject accurate zip code data into request headers and cookies to ensure the returned contractor list matches the targeted local market exactly.
Phone numbers and deep profile data are often obfuscated until user interaction. We run full Playwright browser sessions to trigger these events and capture data that headless HTTP clients miss entirely.
Directory layouts change frequently. Our selector strategy uses multiple fallback chains per field so a layout change does not break your data pipeline overnight.
For massive national directories, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Aggregate local construction costs to build accurate property valuation and renovation models.
Local contractors track competitor pricing, review velocity, and service area expansions.
Building material suppliers identify high-volume contractors for targeted outreach.
Verify contractor credentials, bond status, and license validity for underwriting.
Analyse regional market fragmentation and category leaders for roll-up acquisitions.
Train natural language models on home improvement review corpuses and project descriptions.
"Angi holds the most comprehensive local contractor directory and pricing index in the US market - but accessing it across 41,000 zip codes requires serious infrastructure."
Most teams underestimate the investment required: reliable Angi scraping requires residential proxies, location spoofing, CAPTCHA handling, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our angi.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 angi.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from directories is generally permissible under applicable law. DataFlirt targets only public, non-authenticated contractor profiles, reviews, and cost guides. We do not extract personal user data or circumvent authentication walls. Clients should review Angi's ToS and consult legal counsel for specific use cases.
We use US residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour to bypass Datadome and Cloudflare challenges.
Yes. We inject precise location data into our session cookies to extract accurate local search results and service area definitions for any US zip code.
Full directory refreshes for specified zip codes complete within 12-24 hours. We can configure daily diff runs to capture new reviews and profile updates quickly.
Yes. Our Playwright integration executes the necessary JavaScript to trigger contact detail rendering, capturing data that standard HTTP requests miss.
Our smallest packages start at a defined list of trade categories across up to 1,000 zip codes. For national coverage, we price based on volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off contractor directory dump or continuous review monitoring across 10,000 zip codes, we scope, build, and operate the pipeline. Tell us what you need.
