How Do Real-Estate Businesses Leverage Machine Learning Apps?
Like many other industries, real estate is slowly but steadily adapting to the “data-driven” world and making headway in developing use cases for artificial intelligence. Tech-savvy CEOs and development managers are quietly learning how to use data analytics to achieve a competitive advantage.
Indeed, with AI pervading every industry, it makes perfect sense to investigate what machine learning technology can achieve for your company. A number of use cases have already surfaced, demonstrating promise in a variety of sectors that can help a company’s market position.
Many real estate agents and brokers may be intimidated by the technology, but a better grasp of the possible applications for AI and machine learning could lead to a new respect for the opportunities that lie ahead.
Why Machine Learning Matters in Real Estate
It makes strategic sense to keep an eye on the evolution of AI technology. However, much of the material regarding AI and machine learning provided is based on wishful thinking (or hype) rather than reality. What should business leaders pay attention to and what should they ignore? AI should be on the radar of forward-thinking CEOs, but just as a blip on the screen.
The main goal is to promote a realistic view of enterprise AI in general and real estate AI in particular. This will enable decision-makers to distinguish between the 5% of AI features that will be beneficial to a business and the 95% that will not.
Five Major Ways Ai And Machine Learning Are Likely To Impact The Real Estate Sector
1# Property Recommendation Based on Customer Preferences
In eCommerce, real-time product suggestion algorithms are becoming a reality. Amazon Personalize, for example, is an AI-powered tool that promotes goods, customizes funnels, and provides tailored search results based on real-time data.
If they utilize it on a listing website, an app, or a CRM system, real estate companies can train a self-learning AI algorithm to make recommendations based on customer preferences like prior purchases, views of specific properties, and search filters. As a result, your business will be able to personalize client interactions and digital product experiences.
2# Identify Strong Client Leads for Agents
With the help of AI & MLdevelopment can also help agents find their perfect clients. For example, one quickly finds hundreds of data markers that distinguish genuine buyers and sellers from those who are just “daydreaming” or “window browsing” homes.
This method of precise identification aids specialty agents, such as a hyper-local expert, in narrowing the pool of possible clients who fit their niche or company emphasis.
3# Refine the Transaction Process
Machine learning, which enables faster closing times, better mobile apps, strong compliance checks, detailed reporting, and auto-fillable data that lowers human data entry and errors, can only assist agents and teams give the most frictionless and surprise-free experience for their clients. At the end of the day, it will provide smart, robust reports that will allow brokers and teams to accurately measure how they’re performing.
4# Predict Appraisals and Market Values
AI technology may also assist agents and brokers in better estimating the future value of a home in a certain region by merging CRM and marketplace data. For example, the system might compile information from a range of sources, such as transportation, local crime, schools, and market activities.
Because most buyers consider a new house to be an investment, having a more accurate projection of its future value can provide them peace of mind when making such a large purchase.
The volume of property features or market data points can be in the tens of thousands, making this an analysis that no human analyst or market research can handle. In fact, this is exactly what Or Hiltch of Skyline AI mentioned earlier in this study.
5# Property Management
AI software can help real estate companies keep track of rental and property listings, maintenance requests, tenant applications, and other data. These tracking statistics can aid in the identification of the most common maintenance concerns, tenant traits and preferences, price trends in certain areas, and seasonal availability.
Conclusion
As you can see, AI may benefit real estate enterprises in a variety of ways. As you read this, many sector decision-makers are clearly aware of the disruptive potential of AI-enabled algorithms, and they’re investigating application cases.
Of course, Machine learning development is only scraping the surface of the real estate industry at this moment, but it’s realistic to imagine that very powerful algorithms are already in the works.
