5 Ways to Apply Data Science to Commercial Real Estate in India

The commercial real estate sector in India is on its way to slowly bounce back and recovering in a post-pandemic world. The start of 2022 has unlocked many potentials and scopes of the commercial real estate industry in this country. Increasing demand for appropriate workspaces, commercial properties, and creative concepts in this industry will aid in powerful development. 

With the commercial real estate sector almost returning to its pre-Covid levels, data has become an extremely vital ‘raw material’ of the industry today. Data science has evolved into a separate study thanks to its importance in contributing to the growth of the real estate market. 

Real estate data analytics companies make use of advanced-level analytics and machine learning models to assess information that helps in making better decisions. With its assistance, you can understand consumer behavior, business strategies can be improved, promising market trends can be weighed and any predicted risks can be tactfully averted and dealt with. 

Let’s take a look at how data science can bring about major changes in the commercial real estate sector by helping professionals make well-informed decisions. 

  • Evaluating Data to Estimate Market Trends

Commercial real estate data analytics can assist in predicting property market trends and any risks that might come up in the investment. By using data that comprises a combination of various variables and predictive analysis; it can assess how consumer groups have been behaving over the years, what kind of properties are in demand, the type of leisure activities that consumers like, and how the rent charges have evolved over time. These factors play a huge role in deciding how well or poorly an investment would be able to perform. 

  • Creating the Property Price Indices 

One of the most vital applications of data for commercial real estate is to gather and leverage details connected to the adjoining local areas. Qualitative and quantitative variables play a role in influencing the pricing of commercial properties. Moreover, these elements also work to provide us with a fair idea of which areas might emerge as popular in the future. 

  • Comprehending Performance of Investments 

In the real estate sector, no two properties can be similar. Variables are different even with properties that exist in the same building, not to mention the fluctuating value of properties over time. The evolving rate of an asset, pertaining to the lifecycle and current/future infrastructure, can be traced over the years by making use of data science in this field. 

  • Recognizing & Segregating Leads 

A great way to leverage the power of data science in commercial real estate is to nurture leads. Generally, it is tough for agents to follow up on all the leads that are generated from the many online and offline marketing campaigns. Nevertheless, real estate data providers who have relevant applications and software can provide a ‘seller or buyer score’ to leads that are more likely to sell or purchase properties. This evaluation is made by assessing elements such as demographics, income changes, and buying behavior. 

  • Gauging Profitability of Investment & Construction 

If you’re planning to invest in a commercial real estate space, location intelligence is an extremely significant feature to measure whether the investment would be able to deliver the anticipated profits in the future. Data science in real estate can also prove to be useful to assess environmental conditions so as to finalize a suitable time for the commencement of the construction activities. 

CRE Matrix is India’s best real estate data analytics company that uses data science to help stakeholders across various sectors to assess and compare leasing data and more. 

For more such exciting analysis and details on real estate, visit CRE Matrix.