How is Big Data Reshaping the Commercial Real Estate Industry

3 min readAug 4, 2022

Big data is helping real estate organizations improve efficiency, cut costs, and make decisions, allowing them to become more adaptable to improve customer satisfaction and experiences. Unlike previous approaches, real estate businesses can now receive real-time data from big data. This data enables realtors, buyers, and investors to assess risks and uncover great opportunities. Based on the latest research by Markets and Markets, Big Data Market will be worth $273.4 billion by 2026.

Big data in the real estate sector helps customers get their desired homes, the type of bedroom they need, and the right neighborhood in any region without visiting the location for assessment. It also optimizes consumer search and provides recommendations of reputable real estate websites to potential sellers and buyers.

Few examples of how big data helps Commercial Real Estate Firms and professionals?

  • Using historical data, real estate companies can estimate project costs and construction schedule delays.
  • Mortgage underwriters can reduce risk by measuring borrowers’ credibility in better ways.
  • Property management companies can improve the effectiveness of building systems while lowering operational costs.
  • Acquisition possibilities that both institutional and individual investors can find the best suit an investor’s investing strategy.
Source: Anblicks

9 Ways Big Data is Transforming the Real Estate Industry

  1. Maintain accurate property evaluation: Real estate organizations can use big data to enable automated assessment methods that will replace the traditional real estate appraisal, which has a high error rate. A big data model employs the most recent economic, demographic, and geographic data to eliminate human errors during property evaluation. Although humans cannot be replaced, big data algorithms use more data points to make better conclusions while boosting accuracy.
  2. Target potential buyers: Thanks to big data solutions, real estate agents are no longer forced to make blind projections because they can now monitor and forecast customer behavior. They aid in identifying the requirements of potential buyers, making it simpler for the agents to identify and connect with their target audience. This strategy excels in luxury homes where customers aren’t looking in a specific location but rather for homes with high-end features. Using data analytics, real estate companies can provide potential homes tailored to these buyers’ tastes, preferences, and expectations.
  3. Data-driven risk mitigation and property insurance: Obtaining accurate and clean data sets is also important when developing predictive analyses of the financial risks of investing in specific buildings and projects. Furthermore, big data analytics can assist insurance companies in providing the right insurance to prospective buyers or homeowners and actuaries in making better assessments. Also, Real estate firms can use data more precisely to determine a property’s condition and age and obtain reliable data on its redesigns and renovations.
  4. Improvement in marketing strategies: Private and public data sources, business surveys, and social media provide insights that help determine the best market for a real estate project. Big Data analytics, for example, can provide real estate businesses with the data they require by sorting gender, age, preference, interests, and region. This will eventually improve specific firms’ marketing interactions. This information can assist real estate firms in identifying the needs of their ideal customers, such as homes or pet-friendly properties in excellent school districts. Whatever the ideal client’s requirements are, big data enables real estate firms to improve their marketing strategies to win real estate marketing revenue.

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