Today, the most critical ‘raw material’ driving the real estate market is data. From scrutinising different surveys and analysing products to formulating future policies and solutions, real estate data intelligence has developed into a separate discipline of study. Data science employs machine learning models and advanced-level analytics to gauge information and enhance policy making in the real estate sector.
Soon to become an integral part of real estate businesses, data intelligence helps comprehend consumer behaviour, optimise business strategies, predict market trends and mitigate risks, serving customers, agents, and investors alike.
In this article, let’s see how the various promising use cases and applications of data science and big data contribute to the ever-evolving real estate industry.
Table of contents
Use Case of Data Science for Real Estate
If you are pondering the role of data science in real estate, here are its five significant use cases.
Price Indices and Investing
Results reaped via data science help investors make astute decisions based on hard insights and high-quality data. The progress in data technology helps investors make precise forecasts regarding the properties they are investing in. Previously, these decisions were taken via historical information on property values, high-value local amenities, neighbourhood’s nature, etc. – all of which are subject to constant change and variations. Data science helps overcome these issues by not only analysing past data but also offering viable future predictions.
Valuation of Property
Property valuation could be a resource extensive and time-consuming task as it requires human interaction. Data science programs, however, make this task significantly simple and easy by probing key information and calculating the property’s market value.
The perks of shifting to an automated valuation system are:
- Clients get a reliable and fair property price due to real-time market data. Since the system is updated incessantly, the displayed prices are up to date and appropriate.
- Some details might skip a human’s eye, but this is where a machine’s artificial intelligence in real estate comes into play. Data intelligence software detects vital trends and patterns that we humans might neglect.
- The automated process can help real estate agents save their precious time to focus on other important events.
Improved Forecasting
Forecasting is not all fun and games with crystal balls in the world of real estate. Time series forecasting is an asset that helps potential clients estimate the future value of their favoured properties. Data science models use massive quantities of data from multiple sources to create a forecasting layout. This information leads to better financial returns, innovations, and hence, intelligent investments.
Cluster Analysis
The real estate output is hugely dependent on the venue. Local factors like demand-supply trends and macroeconomic situations result in the price variations of different locations. This is why mass-market houses, luxury condos, townships, or sub-sectors vary in prices within a city. The cluster analysis process examines the differences and uses data science to unravel the intricacies of these factors. It helps identify the nature and behaviour of the properties, time periods, and the real estate market’s performance. The accurate analysis and data lead to increased clientele trust and satisfaction.
Location Analysis
It is a given that a property’s location is one of the most important factors a client explores before investing. Easing this process, the Geographic Information System or GIS mapping software has been a game-changer. It helps understand the statistics of a location and its impacts on property values. The tools of the GIS assists in analysing and understanding the locality intelligence constructively. Open data sources are a huge help in receiving information about the entire locality. It is used for mapping localities for clients to pin down their commute time and define the location’s compatibility to the latter’s preferences, directly affecting the buying and purchasing decision.
How is Data Intelligence Transforming Real Estate?
Let’s see how the real estate industry uses multiple functions of data science to put its best foot forward.
Location
Since commercial real estate is a more complex network than residential real estate, data science provides insights into the current market patterns and trends. It determines the feasibility of the different locations depending on rental income, traffic, occupancy, investment return, and ratings.
Customer Trends
Investing in a commercial or residential property requires awareness and an in-depth understanding of the market trends. It is crucial for investors to understand the needs of the customers, and this is where the importance of data in real estate slides in. For instance, better investments can be made if an investor is aware of the factors like primary rivals, demand for a shopping mall, parents’ need for a new school, clustered housing necessities, affordability, etc.
Scrutinising Competition
Thoroughly monitoring a sector and its activities also means being aware of the competitor’s position. Data analytics helps in examining the rival’s performance. It helps in clearing the competitor’s stand and the customer’s perspectives. A careful analysis of the same can help one in creating powerful strategies.
Investment Performance
No two properties can be identical, like two peas in a pod. Variables of the property are unique, which is also applicable to two properties in a single building. These values also change with the passage of time. Hence, it becomes challenging to track the sub-market performance of the properties. Data science helps in monitoring the altering price of the assets over time.
Simplifying Home Buying
Data intelligence is not only for the benefit of the broker class or the investor, but it also simplifies the home buying, renting, and searching process. For instance, the prices of different real estate properties can vary, attributing to varying factors like connectivity, neighbourhood quality, available transportation modes, etc. Here, data analysis helps in the buyer’s decision-making regarding the location.
Overhaul of Marketing Strategy
Data intelligence collects and examines various information from multiple sources. This strategy can help understand the preferences and consumer behaviour so that agencies can market their services in a more creative and cogent manner. Understanding the user preference helps attract the target audience through 3D rendering, visualisation, Facebook or Google ads, listings, and visual staging.
It is essential to remember that today’s audience scrolls through property listings online. Hence, paying special attention to the real estate posts for social media marketing becomes paramount while also sustaining the aesthetics of the content posted.
How Big Data Analytics Helps in Real Estate Analysis?
Big data uses data science approaches to reach beyond the standard analysis and render unique characteristics of each property. Big data analytics can build up granular sub-market guides by considering the property demographics and characteristics.
The Potential of Big Data in Real Estate Analytics
Huge volumes of digital and historical data collected by the owners and users of real estate can leverage the big data tools to churn out the following advantages:
- Implementing big data results in a faster workflow. It helps both customers and real estate players identify more profitable and appropriate properties or projects.
- The risk of selecting the wrong project is reduced.
- With the help of sentiment and predictive analysis, the filtered and customised projects provide a competitive advantage to the customers.
- Big Data helps prevent significant risks in real estate by predicting future price fluctuations accurately.
- With the analysis of big data insights on real-time regional prices and its forecast of price fluctuations, real estate companies can collaborate and offer personalised insurance cover for customers by providing future value.
Use Cases of Big Data in Real Estate
Big data is a trailblazing tool that harbours the potential to transform the data intelligence system. Let’s have a look at its use cases below.
Data Representation and Visualisation
Data intelligence has a crucial role in today’s evolving world, which is now running on technology-driven decision making. According to statistics, 90% of real estate decisions are based on data. Similarly, the presentation of this data decides whether the business will bag a deal or not. Data visualisation helps in client engagement and better communication with the help of web-based and mobile-based applications.
Property Categorisation through Advanced Filters
Advanced filters cater to consumers with real-time access to data. These search filters provide information beyond the regular property details like 3D property visualisation, nearby restaurants, live location tracking, information related to lifestyle, etc., via any internet-enabled device.
Comprehending the needs of the customers helps real estate professionals to not only enhance customer engagement but also modify products and services to make them more customer-centric.
For instance, designing a more easily navigable UI, Square Yards enables its prospective consumers to access robust data intelligent filters that open them to over 140,000 real estate projects and 8.6 million transaction records across 11 major metropolitan cities in India.
Revenue Optimisation
Receiving timely returns on investment is the primary goal of any industry/business to optimise long-term revenue. Big data-enabled analytical tools integrated with advanced technologies contribute to the overall growth and evolution of real estate functionalities. The international real estate market is already adapting big data technology not only for more clarity in market analysis and customer behaviour but to transform real estate into a consolidated manager of space and systems.
Smart Homes
Smart homes are the living spaces and properties which are automated and coordinated with all the functionalities in the house. Integrated with IoT automation, the user information gathered by this technology proves to be a gold mine for real estate agents. The big data constantly collected through this aids realtors in creating a smarter lifestyle for their users as well as build and customise smart homes in a way that matches customer preferences, moulding the future of residential real estate.
A Vision in Reality
The incorporation of modern technologies like data intelligence has been revolutionising the real estate market, driving it into the current phase. Multiple organisations have already shifted to big data to analyse and estimate property purchases, manage portfolios, calculate profits, etc., indicating the prospects of data intelligence in the real estate industry to be extensive and boundless.
