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Quick Summary: As data is becoming a critical differentiator for industries across the world, the real estate sector is poised to make the most of it! Explore what data analytics in this sector is and how it is making its place in the domain. Get to know the six major use cases that make heads turn. Also, decode everything about the real estate analytics software, tools that could come in handy to you, and how Radixweb can lead you through this heavy transformation in the industry. Keep reading to get your answers.
21st century bets high on data. Data has become the new driving force of almost all industries across the globe, and companies are harnessing its potential sooner or later. One industry that is rising with the scope of data is ‘real estate.’ Today, this sector has moved from instinct-based to statistics-based decisions.
Yes! Data analytics in real estate transforms how properties are managed, sold, bought, and valued. This has led to more efficient transactions in the sector, with stakeholders making smarter, data-backed decisions, which results in high profits. The growth and implementation of data analytics has paved the way for the increased use of real estate software solutions.
As per a report published by Coherent Market Insights, you can expect the real estate software market to value around USD 12.7474 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 10.10%.
In this blog, we will explore the untapped potential of commercial real estate data analytics and know its influence on the industry as a whole. So, keep your eyes on the line and dig deep!
Data analytics for real estate is all about implementing different data-backed techniques to collect, assess, interpret, and conclude actionable insights from large volumes of property data. The real estate market is massive, with a value of USD 654.39 trillion (Year:2025).
So, this data needs to be processed systematically to benefit its stakeholders, help them make informed decisions, increase profitability in deals, and optimize processes. In this case, data analytics solutions involve property price prediction, market trend analysis, property management optimization, and improving customer experiences.
For example, if you are a real estate agency that wants to enhance its property valuation process, you will need to use data analytics. With predictive analytics in this commercial sector, you can improve the accuracy of property valuations, resulting in more informed investment decisions and better customer experience.
You will need a comprehensive data set with historical property sales records and other information like size and location. Further, you will also require neighborhood data, such as crime rates in that location or school quality.
There would be a seasoned process through which this data would be processed, right from data collection and predictive analysis to geospatial analysis and real estate data visualization. Ultimately, you will get a competitive edge over others by getting a data-backed report, which would be a valuable asset for your clients.
In the next section, we’ll explore how integrating data analytics across multiple use cases proves advantageous to the real estate industry.
Data analytics for real estate has been reaching heights, with companies adopting various ways to leverage its power. Listed below are the top use cases that will give you a glimpse of how the sector is harnessing the IT advancements -
The entrepreneurs are rightly using data analytics to analyze property values precisely. The historical sales data, property features, and market trends are assessed thoroughly for property valuation. This further provides buyers, investors, and sellers with more accurate and wise valuations.
Property data analytics is the foundation to monitor and predict market trends. Property dealers leverage it to track demand patterns, price fluctuations, and inventory levels. This further helps companies decide which property to buy/sell, when, and to whom.
Customer base segmentation and building exhaustive customer profiles are vital to real estate agencies, for which they use data analytics. It helps them roll out personalized property recommendations and targeted marketing campaigns for better customer experiences.
Developing real estate apps has become the go-to option for businesses that provide users with property recommendations. Such solutions help clients quickly locate the right property based on search history, location, and user preferences.
Companies use data analytics in commercial real estate to evaluate investment risks. It helps them understand critical factors such as economic indicators or market volatility. They could even gauge the tenant’s reliability with it to make investment decisions.
Big data analytics for real estate is imperative for property management companies that constantly need to simplify operations. Such analysis lets them know when the property would require maintenance, leading to cost-efficiency and tenant satisfaction.
As we saw earlier, the stats and numbers for real estate analytics software are on the higher side, denoting growth and profit. And why not? The software takes these businesses in the right direction for making valued decisions. It helps you evaluate risks, improving fraud detection and compliance maintenance.
Additionally, real estate analytics software is a buzz because of its user-friendly properties, search platforms, and ability to simplify complex data for layman's understanding.
Moreover, the potential of analytics software in this sector has been pumped up with the advent of Proptech (Property Technology.) You heard it right! The Proptech market is also booming, with a CAGR of 6.5% in the 2023-2030 timescale.
With the integration of emerging technologies like cloud computing, IoT, AI/ML, mobile solutions, and more, the efficiency of real estate data analytics software has multiplied. This has further led companies to adopt it on a larger scale to improve their service quality, increase proficiency, and mitigate costs.
Now that you have a basic understanding of data analysis for real estate, let’s learn which tools can come in handy for you for property data analysis. A data platform is an advanced tool comprising ample property-related information.
It could be helpful to analysts, professionals, and investors to know details like property listings, demographics, historical sales data, and more. Also, several real estate investment software solutions focus on examining the financial feasibility of different properties. They do this by evaluating rental income, purchase price, return on investment, expenses, and other factors. RealData and DealCheck are the best tools for this purpose and help you mitigate risks by expanding on the profit rates.
You can also use tools like Zillow’s Zestimate, Redfin’s Estimate, or PropStream to evaluate the property. Market research reports from companies like CoStar, RealPage, Placer.ai, and CoreLogic are the best options for market analysis.
Lastly, you can consider using property management software such as AppFolio, Propertyware, and Buildium to simplify the management of your rental properties. So, regardless of your role in this major industrial sector, you must consider adopting advanced technologies and optimizing your real estate endeavors.
Data-Driven Real Estate Decisions: How Radixweb Can Help?At Radixweb, we specialize in developing custom-made real estate software, which our clients find user-friendly, accurate, and intuitive. Our experts are proficient in building top-notch digital solutions that deliver visibility and precision into what the property buyers want to reap from their investments.Our trailblazing solutions ensure that our clients can easily extract valuable and meaningful insights from the data to implement them in strategy and profit-making productively. Are you thinking of optimizing the way you analyze real estate data? Then, contact us and let our experts guide you on which software suits you best. Get Started Today!
Disha works as a Technical Innovator and her 11 years of experience in the domain make her a market-fit solution architect for innovation-first businesses. She possesses deep technical expertise and has developed unparalleled solutions with React Native, Android and Android Jetpack.
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