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Real Estate Market Intelligence

Comprehensive Market Insights Across 20+ Global Property Markets.

Transform raw property data into strategic market intelligence with PropAPIS. Monitor pricing trends, track inventory levels, analyze supply and demand dynamics, and forecast market movements across Zillow, Rightmove, Idealista, PropertyGuru, Domain, and 15+ global platforms.

The Challenge​

Real estate professionals, investors, and businesses operate in an information vacuum: making strategic decisions with incomplete, delayed, or expensive market intelligence.

Delayed Market Reports​

  • Industry reports published quarterly or monthly
  • Data is 30-90 days old by publication
  • Miss real-time market shifts and opportunities
  • Result: Late to trends, reactive strategy

Limited Geographic Coverage​

  • Traditional data providers focus on major metros only
  • No visibility into emerging secondary markets
  • Cannot compare opportunities across regions
  • Result: Missing high-growth markets

Fragmented Data Sources​

  • US data from CoreLogic, Zillow, NAR
  • UK data from Rightmove, Land Registry
  • Europe scattered across local providers
  • No unified view of global opportunities
  • Result: Incomplete analysis, siloed insights

Expensive Market Data​

  • CoreLogic costs 10K to 50K per year per market
  • CoStar costs 50K to 100K per year for commercial
  • Local MLS access costs 500 to 2000 per month plus broker license
  • Result: Prohibitive costs for most businesses

Manual Analysis is Time-Consuming​

  • Analysts spend 40-60 hours per week collecting data
  • Excel spreadsheets quickly become outdated
  • Cannot scale analysis across multiple markets
  • Result: Limited strategic capacity

The PropAPIS Solution​

PropAPIS provides instant, programmatic access to property data from the world's largest real estate platforms, enabling sophisticated market intelligence at scale.

Real-Time Market Metrics​

Access current market data including:

  • Pricing Trends: Median prices, price per square foot, asking vs sold prices
  • Inventory Levels: Active listings count, new listings, sold properties
  • Market Velocity: Days on market, sale-to-list ratios, absorption rates
  • Demand Indicators: Views per listing, inquiry rates, bidding wars
  • Supply Dynamics: Months of inventory, listing-to-sale conversion

Historical Market Data​

Analyze trends over time:

  • 10+ Years of historical pricing and transaction data
  • Trend Analysis: Year-over-year, month-over-month, quarter-over-quarter growth rates
  • Seasonality: Identify seasonal patterns and cycles
  • Market Cycles: Understand long-term appreciation trends

Geographic Granularity​

Drill down to any level:

  • National Level: Country-wide market trends
  • Regional: State or province market dynamics
  • Metropolitan: City and metro area analysis
  • Neighborhood: ZIP code or postcode level insights
  • Micro-Markets: Street-level granularity where available

Property Segment Analysis​

Segment by multiple dimensions:

  • By Type: Single-family, condo, townhouse, multi-family
  • By Price Range: Entry-level, mid-market, luxury, ultra-luxury
  • By Bedrooms: Studio, 1br, 2br, 3br, 4br and up
  • By Status: Active, pending, sold, off-market

Competitive Intelligence​

Track competitors and market share:

  • Market Share: Track listing volumes by brokerage or agent
  • Pricing Strategies: Analyze how competitors price properties
  • Marketing Effectiveness: Time-to-sale by marketing approach
  • Geographic Focus: Where competitors are most active

How It Works​

Monitor market price movements in real-time:

from propapis import PropAPIS

api = PropAPIS(api_key='your_api_key')

# Get median prices for a market
market_data = api.platforms.zillow.get_market_trends(
    location='Austin, TX',
    property_type='Single Family'
)

print(f"Median Price: ${market_data.median_price:,}")
print(f"YoY Change: {market_data.yoy_change:.1f}%")
print(f"Active Listings: {market_data.active_count:,}")

Analyze Inventory Levels​

Track supply and demand dynamics:

# Monitor inventory trends
inventory = api.platforms.zillow.get_inventory_metrics(
    location='Austin, TX',
    time_period='last_90_days'
)

print(f"New Listings: {inventory.new_listings}")
print(f"Sold Properties: {inventory.sold_count}")
print(f"Months of Supply: {inventory.months_supply:.1f}")
print(f"Days on Market (avg): {inventory.avg_dom:.0f}")

Compare Multiple Markets​

Identify best opportunities across geographies:

# Compare markets side by side
markets = ['Austin, TX', 'Nashville, TN', 'Raleigh, NC']

for location in markets:
    data = api.platforms.zillow.get_market_trends(location=location)

    print(f"\n{location}")
    print(f"  Median: ${data.median_price:,}")
    print(f"  YoY Growth: {data.yoy_change:.1f}%")
    print(f"  Inventory: {data.months_supply:.1f} months")

Historical Trend Analysis​

Analyze long-term market patterns:

# Get 5-year price history
history = api.platforms.zillow.get_price_history(
    location='Austin, TX',
    start_date='2019-01-01',
    end_date='2024-01-01',
    interval='monthly'
)

for month in history:
    print(f"{month.date}: ${month.median_price:,}")

Quick Start​

from propapis import PropAPIS

api = PropAPIS(api_key='your_api_key')

# Get market trends for a location
market_data = api.platforms.zillow.get_market_trends(
    location='Miami, FL'
)

print(f"Median Price: ${market_data.median_price:,}")
print(f"Active Listings: {market_data.active_count:,}")
print(f"Days on Market: {market_data.avg_dom:.0f}")

For detailed code examples and advanced usage, see our API Documentation.

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