Artificial intelligence applications, like AI property valuation, house agent search, and AI listing aggregation tools, are taking the real estate realm by storm. From automating contract generation and review to simplifying property search and recommendations, custom AI property valuation can facilitate many of the core functionalities of the industry, enabling property businesses to scale at ease. In this post, we’re going to discuss one of the most popular AI applications in real estate- AI property valuation software. This category of software has revolutionized the decision-making processes for real estate businesses, helping them make more lucrative decisions to reach long-term business goals.
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What is AI, and How is it used in Property Valuation?
In simple terms, Artificial intelligence or AI is the simulation of human intelligence. It uses devices like edge computing tools and computer systems to perform actions like natural language processing, computer vision, deep learning, speech recognition, etc., to enable machines to perform tasks that have hitherto been done by humans through their cognitive capabilities.
In property valuation, AI has proved its mettle by helping realtors make the most beneficial decisions of their careers. AI can take multiple considerations like the area’s population, location, accessibility to amenities, and other finer details of a property. It can then match these variables with purchasing considerations like budget and market conditions. By evaluating both kinds of variables and then matching them with historical data of property valuations, it can pick up subtle nuances that determine the most reasonable listing price of a property.
More advanced AI development services can be used to build such property valuation software that are capable of understanding relationship between even the seemingly unrelated variables like employment growth, demographics, topography, etc., with more discrete information like rental and occupancy rates. Such an evaluation helps in predicting the more accurate price of a property, offering several competitive advantages to commercial real estate businesses.
How to Implement AI for Property Valuation?
Now we have a better understanding of the role of AI in real estate and its application in modern property valuation software. Let’s have a deeper dive into the working of the software and understand how you can implement AI for property valuation for your real estate venture.
Calculating the value of a property requires a deep understanding of multiple variables. Now, while discovering the hidden relationship of these variables with the estimated price of a property is the primary task of an AI property valuation software, it needs to have data in the first place to make the evaluation.
A sudden boost in the population in a given area can lead to an increase in a similar sudden spike in demand for property there. This shows population growth has a positive coefficient with the price of a property in the given demographics, making related data important to collect and evaluate for the price prediction model. Other than population, other demographic details like the presence of supermarkets, public transportation, work offices, and educational institutes also help in adjusting a more accurate price determination.
The current market trends also have a huge impact on the listing and selling prices of a property. If a certain kind of property has witnessed a surge in demand, the demand and supply law will result in an increase in the price of that particular kind of property. For example, when first contactless and checkout-less shopping stores were first launched, they became hugely popular among consumers raising the investment costs and, consequently, the property valuation of smart store buildings.
Many economic factors also influence the pricing of a property, both residential and commercial. For instance, the increase in the employment rate can lead to more people becoming eligible for home loans, which could result in increased demand for residential property. Similarly, wage growth can also lead to an increase in house listing prices, and improvement in economic growth can have a positive effect on the costs of commercial properties.
Other than the above-mentioned macro data, micro-details of the property itself plays an important role in determining its listing and selling price. This data comes in both structured and unstructured formats. Structured information like the number of bedrooms, area of the property, parking spaces, etc., usually has a positive impact on the property valuation. Similarly, unstructured data, like pictures, and reviews, can help the deep learning sub-domain of an AI application to gather the condition of the property and thus help decide its accurate price.
Machine Learning Model Building for Price Prediction
Once you’ve collected all the relevant data for predicting price, you can begin the model-building process for your custom application of AI in real estate. It would involve data cleaning, exploratory data analysis, univariate analysis, and then eventually building the model and testing it.
While building the model, you need to clean all data to remove biases and improve the quality of both the model and the predictions it would make. The cleaned data can then be processed through univariate and multivariate analysis. Later you can remove the variables that are co-dependent on each other; here, correlation tests would be useful.
When building the model, the price would remain the target variable and the rest of all other independent variables. This is why it’s important to ensure that no variables have any correlation with any other individual or composite variables.
Post EDA, you can use any of the following algorithms to build the model and then test them to find which best suits your requirements.
- Ridge regressor
- SVM regressor
- Random Forest Regressor
- Light GBM Regressor
Develop AI-based Property Valuation Software
When it comes to real estate software development, you don’t act on a hunch. With so many variables to consider and legacy systems to integrate, it is ideal that you follow a sophisticated approach.
Evaluating the existing property valuation solutions is an important step in creating a better and more competitive solution for your business. This stage is also known as the product discovery process, and the purpose here is to find solutions that offer some (if not all) of the functionalities that you are looking for. Many of these software programs are hard to customize. Still, they can offer important insights around interface and software wireframing. One more benefit of this stage is that you can find some features that you may not have considered before but has the potential to be useful for you.
Features to Include
Once you’re done with the market research and functionality feasibility evaluation, you can finalize the important features for the AI property valuation software development. These features should be chosen in a way that empowers MVP development, meaning the dependency of the features must be clear in the first stage itself, so you can plan the sprints in a more reliable way. Here’s a list of primary features of AI property valuation software. This excludes the features that are common for every real estate software, like user registration, listing management, document management, etc.
The foremost thing a property valuation software needs to do is enable data ingestion. It would be ideal if the software could be integrated with various sources for automated data entry. However, it is essential that the data is entered into the system in the predefined schema so the model can make price-related predictions without any flaws.
This valuation software of AI in real estate will allow you to manage all your leads, the ones who have shown active interest in your listing, as well as the ones that fit your target lead criteria. Having property valuation software powered with AI helps you determine the target audience effortlessly, allowing you to automate your marketing and lead conversion process.
With the help of artificial intelligence and machine learning, the property valuation platform can fetch all the relevant data and give it a visual presentation to find hidden trends that only human eyes can pick. For example, a graph between the vicinity of a supermarket and the price of a property has a higher correlation than the area of the property, which can help realtors plan their marketing efforts more effectively.
Having a feature that allows the admin to enter manual variables to help make a better prediction over the price will help real estate businesses to customize the model as and when required. This will help the users tweak the back-end processing of the software itself, making effective changes in the reports more flexibly.
The property valuation software without a report and proposal generation feature is bound to increase the workflow overhead for real estate companies. By automating the report generation, the real estate agents only need to update the data in the model and then simply select the variables on which they want to generate the property valuation report. They can also automate assessment reports for various variables and eventually create the proposal with the most effective one.
Not all the time a report needs to be published. In fact, most of the time, realtors only need to evaluate many variables in real-time and derive their personal insights from the same. Having a comprehensive dashboard in the AI property valuation software will help them do so efficiently.
Hire Development Team
With all the features decided, you’re now ready to begin the development process. For the purpose, you can take AI development services from a company or augment your staff with the skills you don’t presently have. You can also consider hiring real estate software development services and then let the team manage all of the development lifecycles. The only thing you need to ensure when hiring for comprehensive software like AI property valuation is that you have the following resources dedicatedly to working on it.
- Graphic Designer
- Project Manager
- Testing Engineer
- QA Engineer
- Business Analysts
Deploying enterprise solutions like AI property valuation is not a simple plug-and-play job. The software will need a regular stream of data to help the model keep learning and be more accurate with its results. Moreover, if yours is a multi-branch property business, you may want to explore the benefits of containerization for improved consistency in information, scaling benefits, and better utilization of resources. You would also need to integrate your AI property valuation software development process with other legacy systems, including the listing management software. This will ensure that all of the systems are in complete synchronization, and you won’t even need to enter data manually for recurrent training of the price prediction model.
While AI property valuation sounds like a futuristic solution, you’d be surprised to know that many companies are already using such custom real estate software. If you’re in the real estate industry, most of your competitors must already be using AI property valuation software to make better pricing decisions. Regardless, if you think the software can help you give a competitive edge, we suggest you fill out this form with your custom requirements and request a free quote for your project. Our developers have both the experience and skills to create real estate AI solutions. Therefore, they’re more than capable of creating tailored software for you. Matellio, as an enterprise software development company, has years of experience in building real estate solutions. This is why you can also book a free consultation call with us to discuss your ideas for more extensive property software.