We extract business listings, contact information, category taxonomies, and user reviews from Getit. 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 getit.in. All fields typed and schema-versioned.
"business_id": "GT-849201", "name": "Sharma Electronics", "primary_category": "Consumer Electronics", "is_verified": true, "year_established": 1998, "website_url": "http://sharmaelectronics.co.in", "email_address": "contact@sharmaelectronics.co.in"
| # | business_id | name | primary_category | sub_categories | is_verified | description |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Contact & Location objects from getit.in. All fields typed and schema-versioned.
"business_id": "GT-849201", "primary_phone": "+919876543210", "city": "Bengaluru", "state": "Karnataka", "pincode": "560001", "latitude": 12.971598, "longitude": 77.594562, "landmark": "Opposite MG Road Metro"
| # | business_id | primary_phone | secondary_phones | address_line_1 | address_line_2 | city |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Operating Hours objects from getit.in. All fields typed and schema-versioned.
"business_id": "GT-849201", "monday_hours": "10:00 AM - 08:00 PM", "tuesday_hours": "10:00 AM - 08:00 PM", "wednesday_hours": "10:00 AM - 08:00 PM", "sunday_hours": "Closed", "is_24_hours": false, "holiday_status": "Closed on National Holidays"
| # | business_id | monday_hours | tuesday_hours | wednesday_hours | thursday_hours | friday_hours |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from getit.in. All fields typed and schema-versioned.
"review_id": "REV-99234", "business_id": "GT-849201", "reviewer_name": "Rahul Verma", "star_rating": 4.5, "review_text": "Great selection of appliances and good service.", "date_posted": "2025-08-14", "helpful_votes": 12
| # | review_id | business_id | reviewer_name | star_rating | review_text | date_posted |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from getit.in. All fields typed and schema-versioned.
"keyword": "plumbers", "location_filter": "Indiranagar, Bengaluru", "rank_position": 3, "business_id": "GT-112093", "is_sponsored": false, "rating_summary": 4.2, "review_count": 87, "scraped_at": "2026-02-11T14:30:00Z"
| # | keyword | location_filter | rank_position | business_id | name | rating_summary |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Getit scraper navigates geographic search grids, bypasses pagination limits, and executes JavaScript to reveal obfuscated contact details, delivering structured directory data at scale.
Capture business name, description, categories, establishment year, and verified badges across millions of directory listings.
Execute JavaScript to render hidden or masked phone numbers and email addresses, ensuring complete lead generation datasets.
Extract exact latitude and longitude coordinates, structured addresses, and landmarks for spatial analysis.
Paginate through user reviews to capture ratings, text, helpful votes, and owner responses for sentiment analysis.
Normalise complex operating hours into structured daily schedules, including 24-hour flags and holiday closures.
Monitor keyword search results across specific cities and neighbourhoods to track organic rank versus sponsored placements.
Crawl Getit's hierarchical category tree to discover niche businesses without relying on broad keyword searches.
Track changes in business profiles, new reviews, and updated contact details with hash-based diffing to reduce processing overhead.
Scale extraction across Tier 1, Tier 2, and Tier 3 Indian cities using localized search parameters and geo-targeted proxies.
Brief in. Clean data out.
Provide target categories, cities, or specific search keywords. We design the extraction schema together.
We configure Scrapy crawlers, residential proxy rotation, and JavaScript rendering to bypass Getit's anti-scraping measures.
Schema validation, null-rate checks on phone numbers, 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 involves overcoming aggressive pagination limits and contact obfuscation. Here is how we maintain data completeness.
Directory sites often mask phone numbers behind 'Click to reveal' buttons or render them via JavaScript to prevent basic scraping. We run full Playwright browser sessions to trigger these interactions and capture the raw contact data.
Getit truncates search results after a certain number of pages, hiding thousands of businesses. We bypass this by breaking down broad city searches into granular, overlapping micro-neighbourhood grids, ensuring total category capture.
Business directories contain inactive listings. We capture signals like recent review dates, verified badges, and profile update timestamps to help you filter out closed or abandoned businesses from your final dataset.
High-volume crawling from data centre IPs triggers CAPTCHAs and blocks. We distribute requests across a pool of Indian residential ISP proxies, mimicking local user traffic to maintain high throughput.
Listing templates vary heavily based on business type, claimed status, and advertising tier. Our parsing logic uses multiple fallback selectors to ensure robust extraction regardless of the specific page layout.
Sales teams extract structured contact lists of local SMEs, filtered by category, city, and establishment year to build targeted outreach campaigns.
Marketing agencies track their clients' search rankings across specific neighbourhoods and monitor competitor visibility in sponsored slots.
Retail and logistics companies analyze business density across geographic grids to plan new store locations or delivery zones.
Brands monitor customer reviews and star ratings across franchise locations to identify service issues and track sentiment trends.
Aggregators track the growth of specific business categories and analyze competitor service areas and operating hours.
CRM administrators match existing partial records against Getit's directory to append missing phone numbers, addresses, and geographic coordinates.
"Getit holds a massive repository of Indian SME contact data, but extracting it requires navigating aggressive pagination limits and obfuscated contact fields."
Most teams underestimate the difficulty of directory scraping: reliable Getit extraction requires geo-targeted proxies, JavaScript execution for phone number rendering, and spatial grid search algorithms to bypass 100-page limit truncations. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our getit.in 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 handles JavaScript execution for contact rendering. Combined via scrapy-playwright middleware.
We maintain pools of Indian residential ISP proxies. Rotation happens per-request to prevent rate limiting and ensure localized search results.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About getit.in scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available business directory information is generally permissible under applicable law. DataFlirt extracts only public, non-authenticated business profiles, contact details, and reviews. We do not bypass authentication walls to access private user data. Clients should review Getit's Terms of Service and consult legal counsel for their specific use cases.
Directory sites often cap search results at 50 or 100 pages, hiding thousands of listings in dense areas. We solve this using spatial grid search algorithms, breaking down broad city searches into small, overlapping geographic bounding boxes to ensure 100% capture of the target category.
Yes. Getit often requires a click interaction to reveal the full phone number or renders it via JavaScript. Our pipelines use Playwright to execute these scripts and simulate clicks, capturing the unmasked contact data.
We can extract data across all Indian cities and towns listed on Getit. You can define the scope by specific Tier 1 cities, states, or nationwide extraction.
We can configure pipelines to run one-off historical dumps or schedule weekly/monthly incremental updates to capture new business listings, updated phone numbers, and fresh reviews.
Our minimum engagement typically starts at a defined category or city list (e.g., 50,000 listings). We price based on the total volume of records and the frequency of extraction. Contact us for a precise quote.
Yes. We provide a sample run of up to 1,000 business listings for your target category and city during the scoping phase, allowing you to validate schema completeness and contact accuracy.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a complete national directory dump or continuous monitoring of specific local categories, we build and operate the pipeline. Tell us your requirements.
