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Real Estate Data Scraping & Intelligence API for India

Real-time Real Estate Data Scraping across 50+ Indian property platforms. Extract property listings, INR prices per sq ft, RERA numbers, rental yields, builder data, and market trends from MagicBricks, 99acres, Housing.com, NoBroker, Square Yards & more — structured JSON delivered to your pipeline.

10M+Listings Indexed
50+IN Platforms
99.7%Uptime SLA
<2sAvg Response
magicbricks_property.json
{
  "listing_id": "MB-20394810293",
  "platform": "magicbricks",
  "type": "Residential Apartment",
  "bhk": 3,
  "carpet_area_sqft": 1280,
  "super_builtup_sqft": 1650,
  "asking_price_inr": 14500000,
  "price_per_sqft_inr": 8788,
  "rera_number": "P52100041243",
  "builder": "Godrej Properties",
  "locality": "Baner, Pune",
  "city": "Pune",
  "possession_status": "Ready to Move",
  "days_on_market": 18,
  "scraped_at": "2025-06-04T06:14:22Z"
}
50+ Cities
India Coverage
80+ Fields
Per Property Record
15min
New Listing Alert
RERA
Registration Data
INR
Native Pricing + ₹/sqft

What Is Real Estate Data Scraping in India

Turn Indian Property Data into Real Estate Intelligence

India's real estate market is the world's third largest by value — and one of the most complex to analyse. Listings are fragmented across MagicBricks, 99acres, Housing.com, NoBroker, and hundreds of builder websites, each with different schemas. Prices are quoted in INR, per sq ft, and in crore/lakh, while the critical distinction between carpet area, built-up area, and super built-up area can make the same property look 30% more or less expensive depending on which measurement is used. Add RERA compliance requirements, circle rate variations by sub-registrar jurisdiction, stamp duty calculations, and possession status (Under Construction vs. Ready to Move) — and Indian real estate data demands infrastructure built specifically for it. Our platform normalises all of it into a consistent, queryable schema.

01

Discover

We crawl 50+ Indian real estate platforms continuously — detecting new listings, price changes, and possession status updates within 15 minutes of going live across 50+ Indian cities and their micro-localities.

02

Extract

80+ structured fields per property — INR asking price, price per sq ft (carpet, built-up, super built-up), RERA number, BHK configuration, builder, possession date, maintenance charges, stamp duty value, and locality-level market data.

03

Normalise

Data is deduplicated, area measurements standardised to carpet area, prices converted to ₹/sqft (carpet) across all platforms, and localities mapped to our unified Indian city and micro-market taxonomy for cross-platform analysis.

04

Deliver

Structured JSON via REST API, webhooks, or bulk exports to S3, BigQuery, or Snowflake — with locality-level granularity and timestamps on every record for time-series Indian property market analysis.

Supported Platforms

50+ Indian Real Estate Platforms Covered

From the Big 3 property portals and broker aggregators to builder micro-sites, government property registries, and NRI investment platforms — our real estate data scraping covers the full Indian property landscape.

🏠 MagicBricks
🔑 99acres
🏢 Housing.com
🤝 NoBroker
🟦 Square Yards
🔶 Anarock
🐯 PropTiger
🏡 CommonFloor
🇮🇳 IndiaProperty
🌐 Sulekha Property
🏗 DLF Official
🌿 Godrej Properties
🏛 Prestige Group
🔷 Sobha Developers
⭐ Brigade Group
🏘 Mahindra Lifespaces
📊 JLL India Residential
🏡 Quikr Homes
🏢 FlatsDekho.in
➕ +33 More
Data Fields

80+ Structured Fields per India Property Record

Our India real estate data schema includes fields unique to the Indian property market — carpet area vs. super built-up area, BHK configuration, RERA registration number, possession status, circle rate, stamp duty, maintenance charges, floor rise charges, and builder track record — alongside the complete standard property data set.

Property Identity
listing_id / platform / property_type
Platform-native listing ID and our normalised cross-platform property_id for deduplication. Property type follows India's standard classification: Residential Apartment, Independent House / Villa, Builder Floor, Plot / Land, Commercial Office, Commercial Shop, Warehouse / Industrial. Essential for segmenting the Indian property market correctly across platforms.
"type": "Residential Apartment"
Property Identity
bhk / bedrooms / bathrooms
BHK (Bedroom Hall Kitchen) configuration — the standard Indian residential unit descriptor (1 BHK, 2 BHK, 3 BHK, 4+ BHK, Studio) — plus separate bedroom and bathroom counts. BHK is how all Indian buyers search and compare; normalising this field across MagicBricks, 99acres, and NoBroker is the primary key for residential comp analysis in India.
"bhk": 3, "bathrooms": 3
Property Identity
locality / city / zone / pincode
Micro-locality (e.g. Baner, Whitefield, Andheri West), city (Pune, Bengaluru, Mumbai), city zone (North Bengaluru, South Delhi, Navi Mumbai), and PIN code. Indian real estate value is hyper-local — the same BHK configuration can vary 300% in price between adjacent localities in Bengaluru or Mumbai. Locality-level granularity is the core geographic unit for Indian property analysis.
"locality": "Baner", "city": "Pune"
Property Identity
builder / project_name / society_name
Builder/developer entity (DLF, Godrej Properties, Prestige, Lodha, etc.), the specific project name, and housing society name where applicable. Builder brand is a primary purchase driver in Indian new-launch residential — tracking builder-level listing volumes, pricing trends, and inventory absorption enables developer market share intelligence unavailable from headline market data.
"builder": "Godrej Properties", "project": "Godrej Emerald"
Property Identity
floor_number / total_floors / facing
Floor level of the unit, total floors in the building, and facing direction (East, North-East, North, Vastu-compliant flag). Floor and facing are significant value drivers in Indian apartment pricing — higher floors command floor-rise premiums and East-facing / Vastu-compliant units typically price 3–8% higher in tier-1 Indian cities due to cultural buyer preferences.
"floor": 12, "total_floors": 24, "facing": "East"
Property Identity
possession_status / possession_date / age_years
Possession status (Ready to Move, Under Construction, Pre-Launch) and expected possession date for under-construction projects. Ready-to-Move properties command a significant premium over Under Construction in most Indian markets post-RERA — typically 10–15% — making this field a key price normalisation input for cross-listing comparison.
"possession": "Ready to Move"
Pricing (INR)
asking_price_inr / price_in_crore / price_in_lakh
Asking price in INR absolute value, in crore (₹1Cr = ₹10,000,000), and in lakh (₹1L = ₹100,000) — all three representations in which Indian property prices are expressed. Indian buyers, builders, and media quote prices in crore/lakh depending on context; all three forms are included to power dashboards and reports without manual conversion.
"price_inr": 14500000, "price_cr": 1.45
Pricing (INR)
carpet_area_sqft / builtup_area_sqft / super_builtup_sqft
Carpet area (actual usable floor area), built-up area (carpet + walls), and super built-up area (built-up + proportional share of common areas). The distinction matters enormously in Indian real estate — a unit listed at 1,650 sq ft super built-up may have only 1,280 sq ft of actual carpet area. RERA mandates carpet area disclosure; our schema tracks all three and flags which was used for listing price calculation.
"carpet_sqft": 1280, "super_builtup": 1650
Pricing (INR)
price_per_sqft_carpet / price_per_sqft_buildup
Price per square foot calculated on carpet area and on built-up area separately. Price per sq ft on carpet area is the only truly comparable metric across Indian property listings — RERA requires it for new projects. This calculated field enables genuine apples-to-apples comparison across listings that use different area measurement conventions.
"psf_carpet": 11328, "psf_builtup": 8788
Pricing (INR)
price_history_inr[] / price_30d_change_pct
Time-series INR price data going back up to 24 months — essential for tracking Indian real estate appreciation cycles, pre-launch vs. near-possession price trajectories for under-construction projects, and locality-level micro-market trend analysis. Each record is timestamped with the platform, listing status, and current possession stage.
"price_30d_change_pct": +2.8
Pricing (INR)
days_on_market / list_date / last_updated
Number of days since first listed and the original listing date. Days on market is the most important liquidity signal in Indian real estate — a 3 BHK at 90+ DOM in a 25-DOM locality market signals overpricing or a motivated seller. This field, unavailable from static property portals, requires live data scraping to compute accurately across the Indian market.
"dom": 18, "list_date": "2025-05-17"
Pricing (INR)
last_transacted_price_inr / last_transaction_date
Most recent registered transaction price from state government sub-registrar records (where publicly available via IGRS / MahaRERA / RERA portals). The spread between registered transaction price and current asking price reveals actual market direction and seller expectation gaps — a critical input for AVM (Automated Valuation Model) development for India.
"last_tx_inr": 11200000, "tx_date": "2022-11-08"
Property Features
amenities[] / amenity_count
Full list of society amenities extracted from listing pages — Clubhouse, Swimming Pool, Gymnasium, Children's Play Area, Jogging Track, 24/7 Security, Power Backup, Lift, Visitor Parking, CCTV. Amenity count and quality are significant price premium drivers in Indian residential — gated communities with full amenities command 15–25% premiums over non-gated stock in the same locality.
"amenities": ["Clubhouse", "Pool", "Gym"]
Property Features
furnishing_status / kitchen_type
Furnishing status (Unfurnished, Semi-Furnished, Fully Furnished) and kitchen type (Open, Closed, Modular). Furnishing status is a major price variable in Indian rental and resale markets — fully furnished apartments in Bengaluru and Mumbai tech corridors command rental premiums of 20–35% over unfurnished equivalents and complicate direct price comparisons without this field.
"furnishing": "Semi-Furnished"
Property Features
parking_covered / parking_open / car_parks
Whether covered and open parking is included, and the number of car parking spaces. Parking is a separately priced line item in many Indian cities — particularly Mumbai and Bengaluru where covered car parks are sold for ₹5–25 lakh separately. Listing prices often exclude parking; this field enables total cost calculation.
"covered_parking": 2
Market Intelligence
locality_median_psf / locality_price_trend_pct
Current median price per sq ft (carpet area) for the property's locality and 90-day price trend percentage. Locality-level market data contextualises every individual listing — enabling instant comparison of a property's asking rate against its micro-market median. Essential for identifying underpriced listings and overpriced outliers in any Indian city.
"locality_median_psf": 9200, "trend_90d": +3.4
Market Intelligence
active_inventory_locality / months_of_supply
Active listing count and months of supply for the property's locality and BHK type. Months of supply below 4.0 in an Indian city indicates a seller's market; above 8.0 signals buyer leverage. This real-time market indicator is unavailable from any static Indian property data source and requires continuous live scraping to compute.
"inventory": 312, "months_supply": 5.2
Market Intelligence
avg_dom_locality / absorption_rate_pct
Average days on market for recently sold comparable properties in the locality and monthly absorption rate. These two metrics define micro-market velocity in Indian real estate — high absorption in Whitefield or Gurgaon signals demand outpacing supply, a direct input for pricing strategy for new launches and resale listings.
"avg_dom": 32, "absorption_rate": 14.8
Market Intelligence
connectivity_score / metro_distance_km / it_hub_distance_km
Infrastructure connectivity score, distance to the nearest metro station in km, and distance to the nearest major IT park or SEZ. In Indian cities — particularly Bengaluru, Hyderabad, and Pune — proximity to IT hubs is the dominant value driver for residential property, often accounting for 30–50% of price variation between otherwise comparable localities.
"metro_km": 1.2, "it_hub_km": 3.8
Rental Intelligence
rent_estimate_monthly_inr / rental_yield_pct
Market rent estimate in INR/month derived from comparable active rental listings on MagicBricks, 99acres, and NoBroker for the same BHK, locality, and furnishing status. Gross rental yield calculated as annual rent divided by asking price — the primary investment return metric for Indian residential real estate investors who are increasingly yield-focused post-RERA.
"rent_est_inr": 38000, "gross_yield_pct": 3.1
Rental Intelligence
security_deposit_months / lock_in_period
Standard security deposit in months of rent and typical lock-in period in months. Indian rental market norms vary significantly by city — Mumbai typically demands 2–3 months security deposit while Bengaluru demands 6–10 months, representing a large upfront capital requirement invisible in headline rent figures but critical for tenant cost-of-entry analysis.
"deposit_months": 6, "lock_in_months": 11
Rental Intelligence
maintenance_charges_inr / maintenance_type
Monthly maintenance or society charges in INR and the charge type (per sq ft, flat rate, or variable). Maintenance charges in premium Indian gated communities run ₹5,000–₹25,000/month and are a significant ongoing ownership cost invisible in listing prices. Including this field enables true total-cost-of-ownership comparison across Indian residential properties.
"maintenance_inr": 8500, "type": "per_sqft"
Agent & Builder Data
agent_name / agent_phone / agency_name
Listing agent's name, contact phone, and agency/brokerage name where disclosed. For NoBroker listings, owner contact details are included directly. Agent data enables broker market share analysis, lead generation for PropTech platforms, and monitoring of which agencies dominate listing inventory in specific Indian localities.
"agency": "RE/MAX India, Pune West"
Agent & Builder Data
listing_type / owner_listing_flag
Whether the listing is from a broker/agent or directly from the property owner (a field unique to NoBroker which explicitly marks owner listings) and the listing type (New Launch, Under Construction, Resale, Auction). Owner listings typically price 3–7% below equivalent broker listings — this flag is critical for accurate price comparison and brokerage commission impact analysis.
"owner_listing": true, "type": "Resale"
India-Specific
rera_number / rera_state / rera_expiry
RERA (Real Estate Regulatory Authority) registration number, the state RERA authority under which it is registered, and the registration expiry date. Mandatory for all new residential projects in India post-2017 — the presence or absence of RERA registration is a primary trust and legal compliance signal for buyers, and a critical dataset for PropTech platforms building buyer protection tools.
"rera": "P52100041243", "state": "MahaRERA"
India-Specific
circle_rate_psf_inr / stamp_duty_pct / registration_charges_pct
Government-mandated circle rate (Ready Reckoner rate) per sq ft for the sub-registrar jurisdiction, applicable stamp duty percentage, and property registration charges. These three fields define the total transaction cost for an Indian property purchase — stamp duty alone adds 5–7% to total acquisition cost. Essential for mortgage origination, investment return modelling, and legal compliance analysis.
"circle_rate_psf": 7200, "stamp_duty_pct": 6.0
India-Specific
vastu_compliant / gated_community / society_name
Vastu compliance flag (a significant purchase filter for a large share of Indian homebuyers), gated community status, and housing society name. Vastu-compliant, East-facing properties in gated communities command measurable price premiums in tier-1 and tier-2 Indian markets — this field enables valuation models to account for India-specific buyer preference signals absent from any Western property data schema.
"vastu": true, "gated": true
Legal & Ownership
ownership_type / title_status / encumbrance_status
Ownership type (Freehold, Leasehold, Society, POA), title verification status, and encumbrance details indicating whether the property has any legal claims, loans, or disputes. Clear-title properties are easier to finance and typically sell faster in the Indian market. These fields support due diligence, risk assessment, and fraud detection.
"ownership_type": "Freehold", "title_status": "Clear", "encumbrance_status": "No Encumbrance"
India-Specific
occupancy_certificate / completion_certificate
Occupancy Certificate (OC) status, Completion Certificate (CC) status, and project approval verification. These are among the most important legal compliance fields in Indian real estate post-RERA. Properties lacking OC or CC may face mortgage eligibility issues, utility connection restrictions, and resale complications. Tracking approval status across municipal authorities enables buyers, lenders, and PropTech platforms to identify regulatory risks before transaction completion.
"oc_status": "Issued", "cc_status": "Issued"
Infrastructure & Location
school_distance_km / hospital_distance_km / airport_distance_km
Distance to the nearest major school, hospital, and airport, plus an aggregated livability score derived from surrounding infrastructure. Access to education, healthcare, and transport infrastructure is one of the strongest drivers of residential demand and long-term appreciation in Indian cities. These location intelligence fields support buyer decision-making, investment screening, and valuation models by quantifying real-world accessibility beyond simple locality names.
"school_km": 0.8, "hospital_km": 1.6, "airport_km": 12.4
Sample Dataset

Real India Property Data — 10 Listing Samples

Every record below was extracted by our Indian real estate data scraping pipeline. INR pricing, price per sq ft, RERA numbers, BHK, and locality data included exactly as delivered via the API.

# Listing ID Platform Type / BHK Builder / Project Locality City Possession Scraped At
01 MB-20394810293 MagicBricks 3 BHK Apt Godrej Properties / Godrej Emerald Baner Pune Ready 2025-06-04 06:14
02 99A-48291039 99acres 2 BHK Apt Prestige Group / Prestige Sunrise Park Whitefield Bengaluru Ready 2025-06-04 06:15
03 HSG-19283741 Housing.com 4 BHK Villa DLF / DLF Crest Sector 54, Golf Course Rd Gurgaon Ready 2025-06-04 06:16
04 NB-8291047382 NoBroker 1 BHK Apt Owner Listing Andheri West Mumbai Ready 2025-06-04 06:17
05 SY-3920184729 Square Yards 3 BHK Apt Lodha / Lodha Palava City Dombivali Mumbai MMR UC 2026 2025-06-04 06:18
06 MB-48291038472 MagicBricks 2 BHK Apt Sobha / Sobha Dream Acres Panathur Bengaluru Ready 2025-06-04 06:19
07 99A-29384710 99acres Plot 200 sqyd Individual Owner Kompally Hyderabad Ready 2025-06-04 06:20
08 HSG-48291038 Housing.com 3 BHK Apt Brigade Group / Brigade Cornerstone Utopia Whitefield Bengaluru UC 2026 2025-06-04 06:21
09 AN-10293847 Anarock 4 BHK Apt Mahindra Lifespaces / Mahindra Citadel Pimpri Pune UC 2027 2025-06-04 06:22
10 NB-58291039 NoBroker 2 BHK Apt Owner Listing Koramangala Bengaluru Ready 2025-06-04 06:23
Real-Time Use Cases

Who Uses India Real Estate Data Intelligence

From PropTech platforms and real estate investors to private equity funds and urban planning researchers — real-time Indian real estate data insights power the most consequential decisions across India's ₹50 Lakh Cr property market.

Real Estate Developers & Builders

Competitive Launch Pricing & Inventory Intelligence

India's new launch market is intensely competitive — a developer launching a 3 BHK project in Whitefield needs to know exactly what Sobha, Brigade, and Prestige are selling at per sq ft (carpet area) today, not last quarter. Our real estate data scraping tracks active inventory, price per sqft trends, absorption rates, and days-on-market for every competitor project across 50+ Indian cities in real time. When a competing developer drops price or a nearby project sells out, your sales team knows within 24 hours — not at the next market review meeting.

launch pricinginventory intelcompetitor analysis
PropTech Platforms & AVM

Automated Valuation Models for Indian Property

Building an AVM (Automated Valuation Model) for Indian real estate requires property-level data that accounts for India-specific variables — BHK configuration, carpet vs. super built-up area, possession status premium, floor-rise pricing, Vastu compliance premiums, and IT-hub proximity effects. Our real estate data intelligence delivers the structured, normalised training dataset at scale that Indian AVM models require — with 24 months of historical price-per-sqft data per locality and BHK type across 50+ cities for model training and backtesting.

AVM modelsprice predictionML training data
Real Estate Investment & Funds

Indian Residential Investment Screening & Yield Analysis

Family offices, HNI investors, and real estate funds deploying capital in Indian residential markets need to screen thousands of listings for yield potential — gross rental yield, net yield after maintenance and property tax, and price-to-rent ratios across micro-localities. Our real estate data intelligence API delivers pre-calculated yield fields, rental comp data, and maintenance charge estimates for every scraped listing — enabling quantitative investment screening across the full Indian market rather than relying on broker-provided comparables.

rental yieldinvestment screeningcap rate India
Banks & Housing Finance Companies

Mortgage Collateral Valuation & LTV Risk Intelligence

Housing Finance Companies (HFCs) and banks need accurate, current property valuations to set LTV ratios and monitor collateral values for their mortgage portfolio. Our real-time Indian real estate data — locality median prices, price trend percentages, days-on-market, and circle rate comparisons — provides the market intelligence layer that internal valuation teams use to benchmark physical valuations, detect overvalued collateral, and monitor portfolio LTV risk as Indian property markets move.

mortgage valuationLTV monitoringcollateral risk
Legal & RERA Compliance

RERA Registration Monitoring & Buyer Protection

Our real estate data scraping captures RERA registration numbers from Indian property listings and cross-references them against state RERA portal data — detecting listings that claim RERA registration but cannot be verified, projects with expired registrations still being actively marketed, and builders who have faced RERA penalties. For home buyer platforms, legal tech firms, and consumer protection organisations, this RERA compliance monitoring layer is invaluable — and impossible to build without structured listing data at scale.

RERA compliancebuyer protectionlegal tech
Market Research & Consulting

Indian City Real Estate Market Indices & Reports

Our real-time Indian real estate data insights cover 10M+ listings across 50+ cities — making it the most comprehensive private-sector source for Indian property market tracking. Research teams at JLL, Anarock, Knight Frank India, and HDFC Securities use granular listing data to build proprietary price indices, track quarterly supply and absorption by city and BHK segment, monitor the growing premium of RERA-registered over unregistered stock, and publish market intelligence reports that consistently lead official government real estate statistics.

market indicesquarterly reportsprice benchmarking
NRI Investment Platforms

NRI Property Investment Intelligence & Alerts

Over 18 million NRIs are eligible to invest in Indian real estate — and the INR depreciation cycle of the past decade has made Indian property increasingly attractive in dollar and dirham terms. NRI investment platforms need real-time listing data with RERA verification, builder track record, rental yield estimates, and locality growth data — all in English with INR pricing clearly presented. Our real estate data intelligence API provides the structured data layer these platforms need to serve NRI buyers making purchase decisions from Dubai, Singapore, London, and Toronto.

NRI investmentINR pricingbuilder tracking
Retail Home Buyers & Aggregators

New Listing Alerts & Price Drop Detection

New listings matching a buyer's criteria in high-demand Indian micro-markets like Whitefield, Baner, or Koramangala can receive 5–10 serious inquiries in their first 24 hours. Our real estate data scraping detects new listings across MagicBricks, 99acres, Housing.com, and NoBroker within 15 minutes of going live — enabling PropTech platforms to fire buyer alerts faster than any competitor whose data cycle runs daily. Price reduction webhooks can also alert buyers when a property drops to within their budget, capturing price-sensitive demand at the moment of motivation.

new listing alertsprice drop detectionbuyer platform
Urban Planning & Policy Research

Indian Housing Affordability & Supply Research

Academic researchers, urban planners, and government policy teams studying Indian housing affordability need current property price data at the micro-locality level across Tier 1 and Tier 2 cities — data that official records lag by 12–18 months. Our real estate data scraping provides a live picture of asking prices, inventory levels, and price-to-income ratios across 50 Indian cities, enabling housing affordability indices, supply gap analyses, and spatial pricing studies that inform infrastructure planning, affordable housing policy, and PMAY targeting decisions.

housing affordabilityurban researchpolicy analysis
Integrations & Delivery

Plug into Your Stack in Minutes

Our India real estate data intelligence API connects directly to the tools and warehouses your team uses — with INR-native output, structured JSON, and no Indian infrastructure required on your side.

❄️ SnowflakeData Warehouse
📊 BigQueryData Warehouse
🧱 DatabricksLakehouse
🪣 AWS S3Object Storage
🔌 REST APIDirect Access
🔁 WebhooksNew Listing Alerts
📈 Tableau / Power BIAnalytics
🐍 Python SDKClient Library
🟨 Node.js SDKClient Library
📄 CSV / JSON ExportBulk Download
⚡ Kafka / KinesisStream Delivery
🐘 PostgreSQLDatabase
📊 Power BI Business Intelligence
📈 Looker Data Visualization
📑 Google Sheets Spreadsheet Integration

FAQs

Indian Real Estate Data Scraping

Frequently Asked Questions

What real estate data can you scrape in India?
We scrape property listings, INR asking prices (in absolute INR, crore, and lakh), price per sq ft on carpet area and super built-up area, BHK configuration, RERA registration numbers, builder and project names, possession status, floor level, facing direction, amenities, furnishing status, maintenance charges, stamp duty values, circle rates, days on market, agent contact data, locality-level market trends, rental estimates, and gross rental yield — across 50+ Indian real estate platforms including MagicBricks, 99acres, Housing.com, NoBroker, Square Yards, Anarock, PropTiger, and major builder websites. The full schema covers 80+ data fields per property record.
How often is Indian real estate data updated?
New listings and price changes on MagicBricks, 99acres, and Housing.com are detected within 15 minutes of going live on Growth and Enterprise plans. Listing status changes (Active to Sold, Under Construction possession date updates) are captured within one refresh cycle. Locality market trend metrics are aggregated and updated daily. Historical transaction price data from sub-registrar records is refreshed weekly. Starter plans receive daily snapshots. Enterprise plans support near real-time monitoring with webhook alerts on new listings, price reductions, and possession status changes.
How do you handle carpet area vs. super built-up area pricing?
Both carpet area and super built-up area are tracked as separate fields, and price per sq ft is calculated on both independently. RERA mandates that all new project listings disclose carpet area — and since 2017 this has been the legally mandated comparison metric for registered projects. Our normalisation pipeline standardises all pricing to price-per-sqft on carpet area as the primary comparison field while retaining super built-up area data for platforms that still lead with it. A loading factor (ratio of super built-up to carpet) is also included per listing for further analysis.
Do you scrape RERA registration numbers and verify them?
Yes. RERA registration number is a standard field in our schema, captured from listing pages across all Indian portals that display it. For Enterprise plans, we offer cross-referencing against state RERA portal data (MahaRERA, K-RERA, RERA Haryana, TSRERA, and others) to flag unverifiable numbers, expired registrations, and builder entities with active RERA complaints or penalties. This verification layer is particularly valuable for PropTech buyer protection platforms and legal compliance tools operating in the Indian market.
Can I get alerts when new Indian property listings match my criteria?
Yes. New listing and price change webhooks are fully configurable on Growth and Enterprise plans. You can set criteria combining any combination of city, locality, BHK configuration, price range (INR), price per sq ft range, possession status, RERA-registered flag, builder name, property type, furnishing status, and days-on-market threshold. When a property matching your criteria goes live on any of our 50+ covered Indian platforms, the webhook fires within 15 minutes with the full property record in JSON format — including INR pricing, area details, and RERA number.
Do you scrape rental listings as well as for-sale properties?
Yes. Rental listings are a first-class data type in our Indian real estate platform. We scrape active rentals from MagicBricks Rent, 99acres Rentals, Housing.com Rent, and NoBroker (which dominates the Indian owner-direct rental market) for all major Indian cities. Rental records include monthly rent, security deposit in months, lock-in period, furnishing status, maintenance charges, and availability date. Rental comp data is also included as a nested array within for-sale property records to support gross yield and net yield calculation for investment analysis.
Can I track historical Indian real estate price trends?
Yes. Growth and Enterprise plans include price history going back up to 24 months per property across all tracked Indian platforms. Each price record is timestamped with the platform, listing status, and possession stage at that time — enabling Under Construction price trajectory analysis (pre-launch to near-possession appreciation), locality-level appreciation tracking, and identification of listings with significant price reductions that signal motivated sellers. This time-series data is what differentiates our Indian real estate data intelligence from periodic portal snapshots.
Is Indian real estate data delivered in INR?
Yes. All pricing fields are returned natively in INR — asking_price_inr, price_in_crore, price_in_lakh, price_per_sqft_carpet_inr, price_per_sqft_builtup_inr, rent_estimate_inr, maintenance_charges_inr, stamp_duty_value_inr, and circle_rate_psf_inr. USD equivalent at prevailing RBI reference rate is available as an optional computed field on request. INR billing is available on all subscription plans for India-based clients, including GST-compliant invoicing.
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At WebFusionData, we specialize in cutting-edge web scraping solutions to help you unlock valuable insights and drive business growth. Whether you need custom data extraction, real-time monitoring, or large-scale web scraping, our team is here to assist you.

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