Published July 9, 2023

Online Home Value Estimates...where do they come from?

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Written by Nader Abed

Online Home Value Estimates...where  do they come from? header image.
I'm frequently asked about the accuracy of home value estimations offered by various online sources. In short, they can be fairly accurate or inaccurate. Many times, inaccurate estimates can be way off-base, whether too low or too high. This isn't surprising since there are many factors to take into consideration when generating an estimated home market value. Logarithms may calculate values based on home sales in the neighborhood, but you'll need a knowledgeable human to add in any upgrades made to a particular home. Perhaps new hardwood flooring replaced the old carpet throughout the home? Logorathims can't catch that on their own.   

Zillow and other similar real estate websites use a variety of methods to come up with estimated prices for homes. These estimates are commonly referred to as "Zestimates" on Zillow. While the exact algorithms and data sources used by each website may differ, I can provide you with a general overview of how these estimates are generated.


Publicly available data:
Real estate websites gather publicly available data from various sources, such as tax records, local government databases, and MLS (Multiple Listing Service) listings. This data includes information about recent sales, property characteristics, and historical trends.

Comparable sales:

One of the primary factors in estimating a home's value is analyzing the prices of comparable properties (comps) in the area. These comps are homes with similar characteristics, such as size, location, age, and features, that have recently sold. By comparing a subject property to these comps, an estimate can be derived.

Machine learning algorithms:
Real estate websites employ advanced machine learning algorithms to analyze the collected data and generate estimates. These algorithms consider various factors, including property size, number of bedrooms and bathrooms, location, historical sales data, and market trends. The algorithms learn from patterns in the data to predict a home's value based on its unique features.

User-submitted data:
Some real estate websites allow homeowners to provide additional information about their properties, such as renovations, upgrades, or other factors that may influence the value. This user-submitted data can be incorporated into the estimation process.

Local market conditions:
Real estate websites also take into account local market conditions and trends, such as supply and demand dynamics, changes in the economy, and other factors that can impact property values. This information helps adjust the estimates based on the current state of the market.

It's important to note that while these estimates can provide a general idea of a home's value, they are not precise appraisals. Zestimates and similar estimates should be considered as starting points for understanding a property's potential worth. For accurate valuations, it's recommended to consult professional appraisers or Realtors who can perform in-depth assessments based on specific market conditions and property details.

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