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Over the last few years, predictive analytics has played an increasingly important role in both business and consumer contexts, helping us make more informed decisions in our daily lives. Now, predictive analytics has made its way into the world of real estate, where it’s being applied to help real estate agents and other professionals make smarter property listings, price homes more accurately, attract potential buyers through more relevant advertising, and ultimately drive up home values in their area as well as home sales volume overall.
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Here’s what you need to know about predictive analytics in real estate today.
What is Predictive Analytics?
A type of analytics that uses statistical analysis and other data-mining techniques to forecast future trends. Predictive analytics helps companies anticipate shifts in consumer preferences, product demand, employee behaviors, fraud patterns, and a host of other things—and take action proactively. Some real estate software solutions employ analytics by taking historical sales data and mapping it against current market conditions to identify potential business risks. Used effectively, predictive analytics can help real estate agents understand how best to deal with potential problems before they arise.
Importance of Predictive Analytics in Real Estate Technology Solutions
With real estate becoming increasingly data-driven, predictive analytics has become an essential element for any real estate software solution. Instead of simply relying on historical data to analyze trends and project future performance, analytics incorporate statistical modeling techniques into a real estate software application. Thus, by analyzing past transactions and comparing them to current market data, predictive models allow you to see how your business can grow or shrink based on several potential scenarios.
Here are the Top Benefits of Using Predictive Analytics Real Estate Solutions
- Get a competitive edge
- Improved revenue opportunities
- Enhanced fraud detection
- Optimized processes
- Increase asset utilization
- Improve production capacity
- Quality controls
- Improved collaboration
- Reduce risks
Types of Predictive Analytics
Most real estate firms use predictive analytics for two main purposes: forecasting and analysis.
- Forecasting is a prediction about a variable’s future values, such as predicting how much inventory will remain unsold by quarter.
- The analysis uses data to predict patterns or relationships, like determining if homes that sold quickly last year are more likely to sell quickly again next year.
In both cases, algorithms that incorporate time series models can help identify which variables have an effect on each other; multiple regression analysis can also be used to determine which factors contribute most strongly.
As you work with real estate software solutions, ask providers what types of analytics they support so you know your technology has everything you need.
Roadblocks in Using Predictive Analytics in Real Estate
- The biggest challenge in using predictive analytics in real estate is getting people to talk about it. It’s a nascent field, so real estate agents and owners don’t know to ask for it.
- The second-biggest challenge is getting people to realize what they can get out of it (generally speaking, agents/owners expect predictive analytics tools to predict prices when that’s not really possible).
- A third difficulty comes from showing potential users just how easy some AI solutions are—just as many people think they won’t be able to learn how to use one product, they think all products will be too complicated. This isn’t true!
Reluctance to Adopt Changes
Many companies and agents are hesitant to embrace tech in the industry- but that won’t last long. Computers do all the work- what is there to be afraid of? There’s a wealth of information out there waiting for someone who would just invest time studying it, too! With so many advantages at hand- these advancements can really improve performance; set goals and track them using numbers instead of mere words. Imagine how this system would affect an industry with so many variables involved!
Real Estate Agents Struggling with Technology
As the demand for efficiency increases day by day, many real estate agents are struggling to keep up. Some resist adopting new tech because they don’t know what it has to offer or have no time for whatever it is that this new technology will take away from them.
Too Much Competition
With so many other people using new technologies, real estate agents who use old software and methods may find themselves at a competitive disadvantage–especially if they can’t produce the results their clients want. To avoid getting left behind, some may consider implementing these technologies sooner rather than later.
Future of Predictive Analytics in Real Estate
In just a few years, predictive analytics has advanced from an emerging technology to standard real estate technology solutions. It will continue to gain traction in the real estate industry by improving data capture and analysis across both sides of real estate transactions.
But why?
Data is king, but knowing what questions to ask remains a challenge. This helps solve that problem by identifying patterns within existing data sets and then extrapolating those patterns into new areas.
By extracting value from every scrap of information available, real estate companies can gain a competitive edge over those who don’t know how to get more out of their existing assets or who aren’t willing to invest in new tools for analyzing their business practices.
That means real estate professionals who embrace predictive analytics today have an advantage over their competitors tomorrow—and beyond!
Conclusion
Finally, with real estate being one of the world’s oldest professions, it is only natural that big data and predictive analytics would soon make their way into a space where demographics and lifestyle matter. There are a number of new technologies and software solutions that are being offered by companies offering real estate software solutions for agents to learn about potential buyers for their properties using current trends on mortgage rates, job availability, retail sales growth, and other factors.
