We extract business names, addresses, phone numbers, categories, operating hours, and reviews from Yellowpages. 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 yellowpages.com. All fields typed and schema-versioned.
"yp_id": "45918231", "business_name": "Apex Plumbing Services", "street_address": "123 Main St", "city": "Austin", "state": "TX", "zip_code": "78701", "phone_number": "(512) 555-0198", "primary_category": "Plumbers", "rating": 4.5, "review_count": 42
| # | yp_id | business_name | street_address | city | state | zip_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Operating Hours objects from yellowpages.com. All fields typed and schema-versioned.
"yp_id": "45918231", "monday_hours": "08:00 AM - 05:00 PM", "tuesday_hours": "08:00 AM - 05:00 PM", "friday_hours": "08:00 AM - 05:00 PM", "saturday_hours": "Closed", "sunday_hours": "Closed", "is_24_hours": false
| # | yp_id | monday_hours | tuesday_hours | wednesday_hours | thursday_hours | friday_hours |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from yellowpages.com. All fields typed and schema-versioned.
"review_id": "rev_8912347", "yp_id": "45918231", "author_name": "John D.", "star_rating": 5, "review_date": "2026-03-12", "review_body": "Fixed our leak in under an hour. Highly recommended.", "source": "yellowpages"
| # | review_id | yp_id | author_name | review_date | star_rating | review_title |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for SERP & Rankings objects from yellowpages.com. All fields typed and schema-versioned.
"search_term": "plumber", "search_location": "Austin, TX", "rank_position": 3, "yp_id": "45918231", "is_sponsored": false, "distance_miles": 2.4, "scraped_at": "2026-05-12T10:15:00Z"
| # | search_term | search_location | rank_position | yp_id | business_name | is_sponsored |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Services & Metadata objects from yellowpages.com. All fields typed and schema-versioned.
"yp_id": "45918231", "payment_methods": "['Visa', 'MasterCard', 'Amex', 'Cash']", "neighborhoods": "['Downtown', 'East Austin']", "social_links": "['facebook.com/apexplumbing']", "languages_spoken": "['English', 'Spanish']", "bbb_rating": "A+"
| # | yp_id | general_info | payment_methods | neighborhoods | aka_names | social_links |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Yellowpages scraper handles location spoofing, pagination, and data normalisation to deliver clean local business records without the typical directory scraping headaches.
Extract accurate Name, Address, and Phone number records for millions of local businesses across all US zip codes.
Capture primary and secondary categories to map businesses accurately into your internal industry classifications.
Extract star ratings, review counts, and full text reviews to gauge local business reputation and sentiment.
Monitor organic vs sponsored rank positions for specific service keywords across targeted local markets.
Extract and standardise complex operating hours, including weekend availability and 24-hour service flags.
Identify businesses paying for premium placement to build targeted lists of high-intent B2B prospects.
Traverse thousands of search result pages reliably without missing records or getting trapped in infinite loops.
Crawl directory results by specific city, state, or zip code parameters to build hyper-local datasets.
Run one-off bulk exports or configure continuous pipelines at weekly or monthly cadences to track new business listings.
Brief in. Clean data out.
Provide target categories, keywords, or zip codes. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and location headers for yellowpages.com.
Schema validation, null-rate checks, and address formatting normalisation before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage.
Directory scraping looks easy until you try to scale it. Here is how we maintain high yield and clean data.
Yellowpages employs rate limiting and IP blocking for high-volume requests. Our crawlers route traffic through US-based residential ISP proxies to distribute load and maintain uninterrupted access.
Directory data is notoriously messy. We parse raw HTML text into clean, structured fields, splitting full addresses into street, city, state, and zip components, and stripping special characters from phone numbers.
Deep search results often contain duplicate listings or loop infinitely. Our spiders maintain stateful crawl frontiers and deduplicate records by unique YP identifiers to ensure precise coverage.
For ongoing monitoring, we maintain a hash index of last-seen values per business. Subsequent runs only push diffs, saving you compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes or layout changes and repair selectors before you notice missing data.
Sales teams build targeted outreach lists of local businesses filtered by category, location, and years in business.
Agencies track client rankings against competitors for specific local service keywords across multiple zip codes.
Enterprise strategy teams analyse business density and category saturation to inform expansion and franchise planning.
Service businesses monitor competitor pricing signals, promotional offers, and review sentiment in local markets.
CRM administrators append accurate phone numbers, addresses, and operating hours to incomplete existing database records.
Call centres ingest fresh, verified phone number lists mapped to specific verticals for outbound campaigns.
"Yellowpages remains the most structured directory of local business NAP data on the internet, but capturing it across thousands of zip codes requires serious infrastructure."
Most teams underestimate the investment required: reliable Yellowpages scraping requires rotating residential proxies, aggressive pagination handling, rate limit circumvention, and constant schema normalisation. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our yellowpages.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 any required JavaScript rendering and interaction flows.
We maintain pools of residential ISP proxies. Rotation happens per-request to bypass directory rate limits and IP bans.
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 yellowpages.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available business information from directories is generally permissible under applicable law. DataFlirt targets only public, non-authenticated NAP data and reviews. We do not extract personal data or circumvent authentication walls. Clients should review Yellowpages ToS and consult legal counsel for specific use cases.
We use US-based residential ISP proxies and request timing modelled on human behaviour. Our infrastructure automatically rotates IPs when rate limits are detected to maintain pipeline throughput.
We can extract data across all US zip codes and cities supported by the yellowpages.com platform.
We can run pipelines on weekly or monthly cadences to capture new business listings, updated phone numbers, and fresh reviews.
Yes, if the business has published an email address on their public Yellowpages profile, we extract it. However, directory email coverage varies by category.
Our minimum engagements typically start at a defined list of target categories and zip codes. Contact us with your volume requirements for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of plumbers in Texas or a continuous feed of local businesses across the US, we scope, build, and operate the pipeline. Tell us what you need.
