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How Dometr Works

Dometr uses machine learning algorithms to analyze real estate listings and provide accurate valuations.

Data Collection

Dometr continuously collects data from major Serbian real estate portals, including:

  • Property listings (apartments, houses, land)
  • Property characteristics (size, rooms, floor, condition)
  • Location data and coordinates
  • Price history and market trends
  • Infrastructure around properties (schools, shops, transport)

Machine Learning Models

Dometr uses several ML models:

  1. Price Prediction Model: Estimates fair market price based on property features, location, and comparable sales
  2. Rental Price Model: Predicts rental income based on property characteristics and market rates
  3. Yield Calculator: Calculates investment return (annual rental income / purchase price × 100)
  4. Luxury Level Classifier: Identifies luxury properties based on photos, location, and features

Data Imputation

For properties with missing data, Dometr uses statistical methods to estimate:

  • Missing property characteristics
  • Incomplete location information
  • Unspecified infrastructure features

Valuation Process

When you search for a property, Dometr:

  1. Finds similar properties in the area (within 2km radius)
  2. Compares prices within ±20% range
  3. Applies ML models to calculate fair market price
  4. Calculates rental yield if applicable
  5. Identifies if the property is overpriced or underpriced

Accuracy

Dometr's accuracy depends on:

  • Amount of market data available
  • Quality of property listings
  • Market conditions and trends

The service provides transparent calculations and shows comparisons with similar properties so you can make informed decisions.