Property Identity
Build normalized property records connected to source identifiers and locations.
- Address and unit
- Coordinates and property type
- Parcel or source IDs
Home / Real Estate & Local
Property intelligence ledgerReal Estate Data Scraping for Property and Local Market Intelligence
Collect and normalize property listings, asking prices, rents, attributes, agents, listing events, developments, neighborhood signals, and eligible local-market data across public real estate sources.
✓Property-level resolution✓Listing-event history✓Cross-platform matching✓Local market context
AUSTIN PROPERTY VIEWABCDSelected property + nearby candidates
PROPERTY RECORD 00742LATEST OBSERVATION
NORMALIZED ADDRESS
Example Cedar Residence
Austin, TX · Single-family · Property and listing IDs retained
ACTIVEFOR SALEPROPERTY MATCHED
CURRENT ASKING PRICE$625,000Previous asking price retained
BEDS3
BATHS2
LIVING AREA1,840 sq ft
STATUSActive
DAYS OBSERVED26
LISTING SOURCEPortal A
Price reduction observedPrevious and current values retained
-$15,00001PropertyAddress and identity
02UnitBuilding and unit context
03ListingSource and listing period
04OfferSale price or rent
05EventStatus and price change
06MarketComparables and location
Comparable property intelligence
A listing is not the property, and the latest price is not the full history.
The same property may appear across portals, return with a new listing ID, change agent, or contain several independently listed units. Kvetoiq preserves those relationships.
01One property can have multiple listings, agents, sources, and listing periods.
02Buildings, parcels, units, and properties need separate identifiers.
03Delisting and relisting can distort days-on-market and inventory analysis.
04Sale, long-term rental, short-term rental, and commercial records require different schemas.
RAW LISTING123 Cedar Ave · $625K
→
PROPERTY IDENTITYAddress + geo + unit
LISTING CONTEXTSource + ID + agent + period
→
OBSERVED OFFERStatus + price + terms
HISTORICAL EVENTNew, changed, pending, removed
→
MARKET CONTEXTComparables + neighborhood
Real estate data coverage
Capture property, listing, agent, market, and local signals in a usable structure.
Fields are selected around the target decision, property segment, source feasibility, geography, refresh cadence, and responsible use.
Listings & Status
Track listing IDs, URLs, asking prices, rents, statuses, and listing periods.
- Active, pending, sold, rented
- Listing and observation dates
- Delisting and relisting
Property Attributes
Structure physical characteristics and advertised property features.
- Beds, baths, area
- Year built and lot size
- Amenities and parking
Listing Content
Retain descriptions, images, virtual tours, open houses, and source disclosures.
- Description and images
- Content changes
- Attribution and source context
Rental Market Data
Collect long-term rental listings, rates, availability, units, deposits, and lease context.
- Monthly asking rent
- Unit and building details
- Availability and terms
Agents & Brokers
Connect listing agents, brokerages, offices, and eligible professional information.
- Agent and brokerage
- Listing inventory
- Market and property focus
Developments
Monitor announced, planned, under-construction, and completed property developments.
- Developer and project
- Unit mix and amenities
- Stage and expected completion
Neighborhood & Local
Connect eligible neighborhood, transit, school, amenity, and local-business signals.
- Neighborhood and ZIP
- Nearby services and transit
- Market inventory context
Real estate entity modelDiscuss a Custom Property Schema →
Separate stable property identity from changing market observations.
A durable real estate dataset connects parcels, properties, buildings, units, listings, agents, sources, and events without flattening them into one row.
✓Stable property records with source-specific identifiers and matching evidence
✓Distinct listings and listing periods connected to the same resolved property
✓Timestamped observations for price, rent, status, content, agent, and availability changes
PARCEL / PROPERTY
BUILDINGName, type, address
UNITNumber, beds, area
LOCATIONGeo, ZIP, neighborhood
LISTINGID, source, period
AGENTProfessional relationship
OFFERSale, rent, terms
OBSERVATIONValue, source, time
EVENTNew, changed, removed
COMPARABLECriteria and relationship
Cross-platform property matchingExplore Product Matching →
Resolve duplicate listings without merging distinct units or listing periods.
Matching can combine normalized address, unit, coordinates, parcel or source IDs, property type, attributes, images, description similarity, agent context, and other agreed evidence.
01Classify exact property, building-level, unit-level, duplicate, relisted, and uncertain matches.
02Retain original source IDs and matching evidence for audit and review.
03Protect distinct units in multifamily buildings from incorrect deduplication.
Cross-Platform Property ResolutionILLUSTRATIVE WORKFLOW
123 Cedar Ave, Unit 7Portal A · Listing 4821 · 1,120 sq ft
EXACT
123 Cedar Avenue #7Portal B · Listing R912 · 1,118 sq ft
123 Cedar AvePortal C · Building listing · 12 units
BUILD
Cedar ResidencesDevelopment page · Same coordinates
Matching thresholds and review rules are configured for the project. Illustrative classifications do not represent production accuracy claims.
Listing lifecycle and event tracking
Record what changed instead of overwriting the previous property state.
Each event can retain its source, listing ID, property ID, previous value, current value, agent context, and observation time.
01First ObservedProperty and listing context stored
02ActiveCurrent offer and availability
03Price ChangedPrevious and current value retained
04PendingListing status transition
05Sold or RentedOutcome when publicly observable
06Removed or RelistedNew period connected to property
Asking Price HistoryTIMESTAMPED EVENTS
May 02First observed$655,000
May 18Price changed$640,000
Jun 06Price changed$625,000
Jun 21Status changedPending
Jul 09Listing removedOff market
Historical asking prices
Keep listing periods, price events, and status changes connected to the correct property.
Historical records can support price-change alerts, market-duration analysis, relisting research, inventory monitoring, and investment screening.
01Distinguish observed asking prices from verified transaction prices.
02Retain source, listing period, agent, and timestamp for every event.
03Define days on market consistently for the intended analysis.
Comparable property framework
Build comparable sets from documented property and market criteria.
Kvetoiq can prepare comparable-property data inputs. Valuation methodology and final appraisal conclusions require separately validated rules and appropriate professional review.
| Candidate | Distance | Type | Beds | Area | Status | Observed price |
|---|---|---|---|---|---|---|
| Target property | 0.0 mi | Single-family | 3 | 1,840 | Active | $625,000 |
| Comparable A | 0.4 mi | Single-family | 3 | 1,790 | Pending | $610,000 |
| Comparable B | 0.7 mi | Single-family | 3 | 1,920 | Sold | Source value |
| Comparable C | 1.1 mi | Single-family | 4 | 2,050 | Active | $675,000 |
Documented selection inputs
Geographic distanceConfigured
Property and offer typeRequired
Beds, baths, areaWeighted
Age and amenitiesOptional
Status and recencyRequired
Review thresholdProject-defined
Values are illustrative and demonstrate a comparable-data structure, not an appraisal or valuation.
Property and market segments
Use a schema that fits the property market being observed.
Sale, rental, short-term rental, commercial, multifamily, and development records should not be forced into one generic listing model.
Residential SalesListings, asking prices, status, attributes, agents, history
Long-Term RentalsMonthly rent, deposits, lease terms, units, availability
MultifamilyBuildings, unit mix, rents, amenities, availability
CommercialProperty class, area, lease type, asking rent, occupancy
New DevelopmentsProjects, developers, stages, units, expected completion
Short-Term RentalsListings, nightly rates, availability, fees, reviews
Land & LotsParcel context, lot area, zoning-related source fields
Local BusinessEligible places, categories, locations, hours, ratings
Neighborhood and local intelligence
Connect properties to the local context that supports market research.
Eligible neighborhood and local data can include boundaries, ZIP codes, transit, schools, amenities, local businesses, inventory, asking-price bands, and rental-market observations.
01Preserve source, geography, observation time, and definition for every local metric.
02Avoid using protected characteristics or discriminatory proxies in housing decisions.
03Separate source-published facts from derived scores and analytical classifications.
Transit
Schools
Retail
Healthcare
Selected Property
Restaurants
Parks
Employment
Local Services
Real estate intelligence use cases
Turn property, listing, and local signals into practical market decisions.
Listing Price Monitoring
Track asking-price and rent changes across selected properties, markets, and sources.
Explore Price Monitoring →New Listing Detection
Identify newly observed listings that match defined property, location, and offer criteria.
Delisting & Relisting
Connect removed and returning listings to the correct property and listing period.
Rental Market Intelligence
Compare asking rents, availability, unit attributes, lease context, and market inventory.
Comparable Property Research
Prepare candidate sets using documented distance, property, attribute, status, and recency criteria.
Investment Screening
Structure listing, property, market, and change signals for separately defined investment rules.
Agent & Broker Intelligence
Analyze eligible listing inventory, property focus, market coverage, and brokerage relationships.
Development Monitoring
Track project announcements, stages, unit mix, availability, and expected completion.
Commercial Market Research
Collect commercial listings, property class, lease context, asking rent, area, and availability.
Neighborhood Intelligence
Connect properties to eligible local amenities, services, transit, schools, and market observations.
PropTech Application Data
Build normalized property, listing, agent, event, comparable, and local records for applications.
Portfolio Market Monitoring
Observe external asking prices, rents, inventory, and neighborhood changes around selected assets.
Team-to-data mapping
Give each property team the market context behind its decisions.
Investment & Acquisitions
Listings, price history, attributes, comparables, local signalsProperty screening and market research
PropTech Product
Properties, listings, events, agents, images, locationsSearch, alerting, analytics, and application features
Brokerage
Listings, agents, offices, status, market inventoryMarket coverage and competitive intelligence
Property Management
Rental rates, units, availability, amenities, local contextExternal rental-market benchmarking
Development
Projects, permits where eligible, stages, unit mix, supplyPipeline and market assessment
Commercial Real Estate
Listings, lease types, area, property class, asking rentAvailability and competitive research
Research & Consulting
Inventory, prices, rents, listings, market and local signalsMarket studies and trend analysis
Data & Analytics
Normalized entities, observations, events, QA, lineageModels, dashboards, warehouses, and reporting
Historical property timeline
Retain how listings, asking prices, agents, content, and status changed over time.
Timestamped observations create a property-market history instead of preserving only the latest listing state.
01
First observedProperty and listing stored02
Price changedPrevious and current retained03
Content changedAttributes or media updated04
Agent changedListing relationship revised05
Status changedPending, sold, or rented06
Listing removedLast observed state retained07
Property relistedNew listing period connectedReal estate and local source coverage
Assess the public sources that shape each property market.
Every source is evaluated for requested fields, property segment, geography, licensing or source conditions, refresh behavior, responsible collection, and technical feasibility.
ZillowRealtor.comRedfinHomes.comTruliaApartments.comRent.comHotPadsApartment ListLoopNetCrexiCommercialCafeProperty WebsitesBrokerage WebsitesDeveloper WebsitesAuction WebsitesPublic Records SourcesGoogle MapsYelpAirbnbVrboRightmoveZooplaOther eligible sources
Real estate data workflow01 02 03 04 05 06
Validate properties, listing scenarios, matching rules, events, and fields before scaling.
Define Decisions
Confirm markets, property segments, sources, fields, and intended use.
Validate Sources
Test representative searches, listings, properties, units, and changes.
Design Model
Map properties, units, listings, agents, observations, and events.
Build & Resolve
Collect, normalize, match, deduplicate, timestamp, and preserve lineage.
Review Sample
Confirm fields, matching, event logic, quality rules, and output.
Launch & Maintain
Monitor collection, refresh records, and manage source changes.
Real estate data quality
Validate identity, listing context, historical events, geography, and freshness.
Address Normalization
Standardize address components while retaining original source values.
Geospatial Checks
Validate coordinates, boundaries, ZIP codes, counties, and location relationships.
Property Resolution
Classify property, building, unit, duplicate, relisting, and uncertain matches.
Event Validation
Check previous and current values, listing periods, statuses, and timestamps.
Unit Protection
Prevent distinct units and offers in the same building from being merged.
Duplicate Controls
Identify cross-source duplicates while preserving source and listing lineage.
Freshness Controls
Timestamp observations and align refresh cadence with field volatility.
Source Monitoring
Detect structural changes, unexpected gaps, extraction anomalies, and schema drift.
Data delivery
Receive structured property data where your team already works.
Delivery can be aligned with your schema, refresh cadence, event model, validation rules, and downstream environment.
CSVExcelJSONJSONLParquetAPIWebhookDelta FeedS3AzureGoogle CloudSnowflakeBigQueryDatabaseCustom Integration
Related Kvetoiq services
Build the property data workflow around the market, source, cadence, and decision.
Enterprise Web Crawling
Support broad property-market discovery and maintained listing collections.
Explore Enterprise Crawling →Live Crawler
Support scheduled observations, listing changes, alerts, and delta feeds.
Explore Live Crawler →AI-Powered Scraping
Assist property extraction, classification, matching, and content analysis.
Explore AI-Powered Scraping →Web Scraping API
Connect structured property data to applications and internal workflows.
Explore Web Scraping API →Responsible real estate data collection
Scope property data around legitimate use and fair-housing safeguards.
Kvetoiq evaluates public accessibility, source conditions, requested fields, personal-data necessity, contact-field purpose, retention, licensing context, intended use, and request controls. Protected characteristics and discriminatory proxies should not be used for housing decisions. Project-specific legal questions require qualified counsel.
Read the Privacy Policy →✓Public-source and source-condition assessment
✓Purpose, necessity, and data-minimization review
✓Fair-housing and discriminatory-use safeguards
✓Personal-data and retention considerations
✓Source lineage, timestamps, and claim separation
Real estate data FAQ
What property teams ask before starting.
What is real estate data scraping?
It is the managed collection and structuring of eligible public property, listing, agent, development, neighborhood, and local-market information from real estate websites and related sources.
What real estate data can Kvetoiq collect?
Potential fields include addresses, coordinates, property types, beds, baths, area, lot size, year built, amenities, listing IDs, asking prices, rents, statuses, dates, agents, brokerages, descriptions, images, developments, and eligible local context.
Can property listings be monitored over time?
Yes. Timestamped observations can retain price, rent, status, availability, agent, description, image, attribute, and listing-presence changes.
Can new listings and price reductions be detected?
Yes. Defined searches or property sets can be monitored for newly observed listings, asking-price changes, rent changes, status transitions, and removals.
Can the same property be matched across platforms?
Matching can combine normalized address, unit, coordinates, parcel or source IDs, property type, attributes, images, descriptions, agent context, and other agreed evidence.
How are duplicate listings handled?
Records can be classified as exact property matches, building matches, unit matches, cross-source duplicates, relistings, or uncertain candidates while preserving source lineage.
Can delisted and relisted properties be identified?
Yes. A new listing period can be connected to the resolved property when matching evidence and project rules support the relationship.
Can sale and rental listings be separated?
Yes. Sale, long-term rental, short-term rental, commercial, and development records can use distinct schemas and offer types.
Can historical asking prices be retained?
Yes. Asking-price or rent observations can retain previous value, current value, source, listing ID, property ID, event type, and observation time.
Can days on market be calculated?
It can be derived under a documented rule using first-observed, listing-date, removal, relisting, and status events. The definition should match the intended analysis.
Can agent and broker information be collected?
Eligible professional information may include listing agent, brokerage, office, listing inventory, market coverage, and property focus. Requested contact fields require purpose and necessity review.
Can apartment and multifamily unit data be collected?
Potential fields include building, unit, floor plan, beds, baths, area, asking rent, fees, availability, amenities, lease context, and observation date.
Can commercial real estate data be collected?
Eligible fields may include property class, building and lot area, lease type, asking rent, sale price, occupancy-related source fields, amenities, broker, and availability.
Can new developments be monitored?
Potential fields include project name, developer, location, stage, property type, unit mix, amenities, availability, announced dates, and expected completion.
Can short-term rental data be collected?
Eligible public data can include property type, location, capacity, bedrooms, amenities, nightly rate, fees, minimum stay, availability, host context, ratings, and reviews.
Can neighborhood and local business data be collected?
Eligible fields may include neighborhood, ZIP, schools, transit, amenities, local businesses, categories, locations, hours, ratings, and market observations. Scope depends on source and intended use.
Can comparable-property datasets be created?
Yes. Candidate sets can be prepared using documented criteria such as distance, offer type, property type, beds, baths, area, age, status, and recency. Final valuation requires a separately validated methodology.
Can real estate data be delivered through an API?
Yes. Delivery options may include API, webhook, CSV, Excel, JSON, JSONL, Parquet, delta feeds, cloud storage, databases, warehouses, and custom integrations.
How frequently can property data be refreshed?
Cadence depends on source behavior, market scope, property volume, requested fields, change frequency, validation requirements, intended use, and responsible request controls.
How is real estate data validated?
Validation may cover addresses, coordinates, units, property matching, duplicates, listing periods, prices, statuses, agents, timestamps, expected fields, anomalies, and source changes.
Can we review a sample before production?
In many cases, representative properties, listings, markets, and event scenarios can confirm the schema, matching rules, historical logic, quality checks, and delivery format.
How does Kvetoiq approach responsible real estate data collection?
Kvetoiq scopes public sources, necessary fields, source conditions, personal-data considerations, retention, fair-housing safeguards, intended use, and delivery requirements. Qualified counsel should review project-specific legal questions.
Start with representative properties
See what a reliable property intelligence dataset could unlock.
Share your target markets, property types, platforms, fields, event rules, matching goals, refresh requirements, and delivery destination. Kvetoiq will help shape a practical collection and validation plan.