Proptech: Building Happy Communities with adoption of technology. Simplified decision making.

This post is part of our series of blog posts exploring how various industries are taking advantage of digital technologies including big data and analytics. Real Estate Analysis & Research

Traditionally, the real estate game is won or lost due to hard work and old-fashioned business networking. Timing, the ability to detect trends, and sometimes a little bit of luck would determine outcomes of real estate projects.

Data science and analytics changes the way real estate projects are planned, executed, promoted and handed over to home buyers. From the way in which real estate professionals, buyers, sellers, and banks think about transactions involving property, to how these transactions are done today, analytics makes the industry more transparent.

Following are some of the new developments in the industry, made possible due to online data recording, storing, and analyzing capabilities that real estate analytics provides. Credits: Wealth and Financial Wellness

Home Buyers & Retail Investors

Home buyers and retail investors now have access to real estate data at their fingertips. Many new tools offer information obtained through census, consumer surveys, rental yield, employment opportunities, property listings, and geospatial mapping.

Buyers and investors use demographic, location, and crime risk data to make well informed buying decisions.?Ease of living?in proposed location matters most to the home buyers. Analytics also highlight?property value?trends at the city, zip code, and even neighborhood level. Being aware of the market demand and supply trends can help the buyer better negotiate the purchase price.

?Lenders & Banks

Big data helps commercial banks mitigate risk, enabling lenders to offer the best interest rates to their clients. Banks and mortgage lenders also safeguard their investments by leveraging analytics. For example, statistics and trend indicators uncover?potential risks, such as oversupply, calamities, or asset depreciation. Banks can also better determine whether the?price?of a foreclosure or short sale matches what a buyer or investor might be offering. Finally, financial institutions use big data to ensure that they don’t sell their properties for less than what the market will bear.

?Institutional Investors

Real estate investors now gain insights and project future trends using big data. First, it can provide a look into?market trends?and future tenants’ needs/wants. Knowing the energy efficiency, traffic patterns, air quality, and demographics of a certain location gives investors an advantage.

Likewise, predictive analysis can help investors determine future values of properties, such as home appreciation rates, at the spatial scale that is relevant for every transaction. Real estate data can also identify the best prospective tenants, enabling investors to adjust marketing strategies.

Real Estate Agents

Analytics offer real estate agents and their clients’ valuable information on housing trends, demographics, crime data, and ease of living. Agents see what buyers truly covet, and also identify markets where there is changing demand.

?Better Communities

Big data also fuels new ways of looking at community planning.? A great example is the modern township projects which are changing the landscape of various suburban locations. Often these smart cities employ sensors that will track the quality of air, traffic, energy use, and much more.

Using such data, real estate developers can learn what kinds of spaces work best in terms of tenant health, energy efficiency, and other points.

?Building Management

Managing a property is an in-depth, and often tedious, endeavor. Big data can streamline this process by identifying issues, speeding up repairs, and slashing expenses.

For example, equipment information can be used by an algorithm to determine how each component in the building is functioning. As soon as a deficiency is identified, a work order to fix the issue is generated.

Benefits of Data Science in Real Estate Industry:

• Data Science reduces financial risks.
• To help customers to find their dream home.
• To generate property recommendation based on customers behavior and needs.
• To calculate the fair value of a property.
• The algorithms used in Data Science can define the insurance plans for property, considering the risk level.
• Data Science enhances Decision making process for all stakeholders i.e. government organizations, developers, investors, buyers and home finance companies.

https://growthpattern.in/real-estate-analytics/