Real estate businesses make decisions based on intuition, professional experience, historical data, and limited analysis of trends. But there is so much data to track to find hidden or subtle patterns. If these patterns aren't identified, it could lead to loss of money or profits not maximised. This is where big data comes in.
Big data refers to large volumes of data that are difficult to process using traditional techniques. Such data in real estate would include demographic data, geographic data, level of pollution, number of entertainment locations and so much more. By using predictive models to analyse big data, real estate businesses can identify subtle trends, prime opportunities, and assess risk accurately.
Compiled by property auctioneers group over in the UK, below are current big data trends in the global real estate industry.
Thanks to big data analysis, real estate businesses can more accurately evaluate a property. Traditionally, professionals use their expertise and experience to evaluate a home taking factors like neighborhood and schools into consideration. But the truth is that there are so many factors that affect the evaluation of a home and no single person can make sense of these data to accurately evaluate a property.
However, by feeding datasets into AI models and predictive models, real estate businesses can price houses based on current trends. Many quick home buyers use big data to fairly value properties regardless of their condition to ensure they don't make losses.
Big data solutions allow real estate businesses to better understand customers' needs from data insights gathered through social media, CRM systems, and other platforms. This allows businesses to target prospective customers through emails and social media. Also, personalised offers can be made to customers based on data insights.
This technique has proved very successful for luxury homes where prospective customers are more concerned about the high-end features of the home. And real estate businesses can provide them with potential homes that meet their preferences. This also results in improved customer experience as they are served based on their requirements.
Gone are the days when real estate trends were based on guesswork. Now, predictive analysis and AI models can forecast market fluctuations in real time. This is becoming the basis for real estate investments especially when real estate agents, quick home buyers, or investors are looking for low-risk properties that can appreciate over time. It could also look for properties that will retain their values in a declining market.
By tracking data points like income levels and employment trends, businesses can gain significant insights into potential future events like foreclosures, spikes or declines in price, or specific needs of some members of the population.
Building a property isn't cheap. It's a huge financial undertaking that must be done right to yield profits. This means that the time of the construction, location of the construction, and type of building to be constructed must be gotten right. The good news? Big data solutions can provide accurate insights into these factors and help businesses make informed decisions to make smarter investments and maximise profit.
As you can see, real estate decisions are now guided by a wider scope of analysis which is now possible through big data solutions. This analysis requires large volumes of data that require experienced analysts. The data itself isn't what is valuable but the insights that can be derived from the data.
Real estate businesses can do big data analysis in-house if they have the capability. However, it's more common to see real estate companies using third-party specialists to manage the sheer scale of data and make sense of it.
BIO: Roy Cohen is a freelance writer and SEO specialist that has helped countless websites like Property Solvers, Decusoft and Lifehack.
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