Magicbricks, India's leading real estate platform, has launched an instant property valuation tool, PropWorth, powered by advanced machine learning algorithms, which helps buyers and sellers assess the estimated value of any property, leveraging price inputs provided by owners, comprehensive local data collected by agents, and Magicbricks' extensive property listings. Price valuation is not done based on reckoner rates.
Built on 15 years of data and over 30 million property listings, PropWorth covers 50,000 projects across 5,500 localities in 30 cities, including Mumbai, Pune and Nagpur, and offers comprehensive valuations of various property types, including apartments, houses and villas.
According to Magicbricks, over the past three years, demand for housing has surged 23.8% and property prices in major cities have risen nearly 42.6%. In this context, PropWorth is a groundbreaking tool, helping homeowners assess their property value with an astounding 98% accuracy rate.
Highlighting the significance of the launch, Sudhir Pai, CEO, Magicbricks said, “In today's dynamic real estate market, accurate property valuations are more important than ever. PropWorth uses data-driven estimates to eliminate guesswork and ensure fast and accurate property valuations. This clarity empowers buyers and sellers to make informed decisions with confidence.”
Powered by sophisticated and advanced machine learning systems, PropWorth is a tool that efficiently analyzes vast amounts of data, identifies key factors, and generates reliable property value estimates.
Users can provide comprehensive property details like project name, locality name, property type (apartment or house/villa), number of bedrooms, land area, number of floors, parking space, etc. Moreover, specific details like property orientation (as per Vaastu), view from the property (road, garden, pool), extra rooms, amenities (clubhouse, swimming pool, elevator, park, gym) can be shared to further enhance the accuracy of property valuation.
“This is an amazing tool that is on the horizon. It will empower retail home buyers with the power of technology for decision-making. However, to get closer to a more accurate output, data collection points need to include SRO data. In the initial phase, we expect a variation of 6-9% in actual transaction values due to a number of factors including difference in listing prices, broker community estimates, and payment ratios which are still prevalent in many micro markets. This is the much-awaited beginning of empowering retail home buyers,” said Nitin Singhal, Co-founder, PropFina.
Published Date: Wednesday, July 10, 2024 8:41 PM IST
