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Reshaping Real Estate: 5 Ways to Apply Data Science to Real Estate

— February 14, 2022

Identifying the leads and segregating them is another way of harnessing data science to reshape the real estate industry.

Data Science has chalked out a transformational path for all types of businesses by delivering valuable insights. Similarly, in real estate, data science has unlocked different perspectives and potentials from lead generation to reporting and operational activities by incorporating machine learning and evidence-based approaches. In 2018, KPMG conducted a survey, which reported that the real estate industry would be impacted by artificial intelligence and data analysis in upcoming years, 49% of the survey applicants believed it. The real estate industry will be reshaped through constant improvements in technology regulated by data science. However, the question is how the real estate industry will be transformed through updated technology and what will be the application of data science? The article is going to answer this query.

Importance of Data Science for Market Research

The significance of Data Science for market research is indescribable as it provides statistical insight by evaluating raw information in bulk quantity to help businesses in decision making. With those robust statistical insights, market research interprets the outcomes generated from data science to address the particular needs and requirements. Data Science enables the real estate industry to articulate the price indices to better reach the untapped market and satisfy the needs of unique customers, which will result in increased customer satisfaction and loyalty.

Conduct Market Survey and Collect Authentic Real Estate Data

The National Association of Realtors reported that 56% of individuals searched and obtained their houses virtually. The outbreak of COVID-19 surely has affected the in-person home showings. Further, the adoption of technology by Generation Y also has significantly changed the viewing procedure.  Now, contemporarily collected data is being used to display the view of real estate property. This kind of real estate data is reshaping the industry and making it more competitive by bringing new entrants. To anticipate the ever-changing customer needs, and to stay competitive, the realtors need to access the authentic real estate data by collaborating with a reliable platform.

Radix is a cloud-based online platform that helps users with market research and data analytics with its built-in tools to interpret a large quantity of unstructured and indistinctive data. Realtors or real estate business owners can access data to make data-driven decisions and compete with their competitors. They can also access real estate data for different submarkets by collaborating with Radix.

Five Ways to Apply Data Science to Real Estate

Real estate investing street sign on Wall Street; image by Investment Zen via Flickr, CC BY 2.0, no changes.
Image by Investment Zen via Flickr, CC BY 2.0, no changes.

KPMG conducted a survey in 2019, which shows 80% of real estate firms do not apply data science in their decision making procedures. In addition, only 5% of firms have data analytics experts to drive the data transformational efforts while other firms have skill gaps.  The following five ways will help real estate companies for the effective application of data science.

  • Formulating Data Science Method for Price Indices

Data science tactics solve multiple problems of property price indices by working on a large set of data and going beyond human capacity to generate accurate market performance indicators for properties. From locality, demographics, property sectors, and characteristics to generating indices for sub-division of the market, tons of transactions are smoothly gathered and documented through data science. Data indexation defines historical trends, which help real estate firms to regulate pricing and estimate future returns.

  • Implementing Cluster Analysis to Differentiate Performance of Properties’ Sections

The property performance varies from location to location and different macroeconomics factors can influence their performances. Similarly, economic activities, neighborhoods, luxury condominiums, and other sub-sectors are a few elements that make cities different.  To cover each area, locality, or property, cluster analysis is conducted as it analyzes which section of the property will perform better or similar.

  • Streamlining the Procedure of Home Trading

The application of data science has simplified the home trading process to a great extent. The realtors can analyse different factors with help of data science before deciding on property prices such as area covered, nearby zones, commercial centres, commutation, and transportation. Examining buyers’ behaviour, expectations, budget, lifestyle, and facilities preferences will help real estate firms to offer properties according to customers’ needs.

  • Nurturing Leads and Setting Them Apart

Identifying the leads and segregating them is another way of harnessing data science to reshape the real estate industry. Managing and following up thousands of leads is surely a frantic task but applications based on data science have made it possible to set those leads apart that are more likely to trade properties.

  • Improved and Authentic Projections

Projections are needed to track where the real estate industry is heading in upcoming years. For better forecasting, data science use different models and set of data to project better financial returns and investment. Seasonal trends, patterns, and variations can be estimated more accurately now through data science.


Data science will surely leave some striking effects on the real estate industry as currently, the industry is at the start of implementing data science. Several ways can be found to apply data science as mentioned above to discard tons of noisy data transactions and to construct a concise collection of data concerning to make investment and business decision making easy. 

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