Understanding frontline needs to optimize AI functionalities and boost competitive edge in talent, Sinyi Realty’s General Manager, Chen Li-Hsin, collaborates with the Data Application Development Department to advance AI services. These services not only meet the stringent requirements of buyers but also enhance the efficiency of the real estate agents.
A buyer’s specific wishlist for a multi-level home with separate living rooms on each floor and a spacious terrace for gardening led to an exhaustive half-year search by Sinyi Realty’s agent, Hsu Nai-Da, which ended in no deals. However, leveraging the company’s advanced AI system unexpectedly identified an apartment that wasn’t initially considered, resulting in a successful deal upon first viewing. Hsu acknowledged that previously, sales agents manually sifted through properties to fulfill clients’ requests, a time-consuming process.
Since being introduced in 2022, the system has seen growing adoption among agents. Approximately 60% now use the tool, witnessing an almost 20% increase in performance metrics as compared to traditional methods. With the AI system, Sinyi Realty not only shows properties realistically but also anticipates the unspoken needs of clients.
Using critical indicators as “locomotives”, Sinyi Realty started with a clear goal of increasing individual agent transaction volume and extended this to new customer acquisition and repeat sales. Chen Li-Hsin, who has a background in information technology and previously worked in brokerage services, plays a pivotal role in spearheading the company’s technological transformation. All efforts in the transformation aim to improve the quality of transactions, with the growth in individual transaction numbers serving as one aspect that leads to higher overall revenue.
To inspire imagination, the data application team collected detailed field information, combining it with external datasets to feed the AI, simplifying the tasks of property agents.
Embracing AI to solve tasks and engage in human-machine competitions, Sinyi Realty allows employees to understand the benefits of AI over traditional methods and opt to utilize the technology willingly, leading to a more valuable use of their time and opening new avenues for better customer service. Chen illustrates how routine administrative tasks like preparing reports are now AI-driven, shifting the responsibility of data interpretation to the staff, creating a future where embracing AI evolution becomes key to staying competitive in the real estate business.
Most Important Questions:
1. How does AI-powered property matching improve real estate sales?
2. What challenges do real estate agencies face when implementing AI technologies?
3. What are the potential controversies surrounding the use of AI in real estate?
4. How do real agents and buyers benefit from AI-powered property matching systems?
Answers:
1. AI-powered property matching improves real estate sales by efficiently analyzing large datasets to find properties that meet buyers’ specific needs quickly, often uncovering options buyers or agents may not have considered. This leads to faster and more targeted matches between buyers and properties, increasing the likelihood of sales.
2. Challenges include the high cost and complexity of implementing AI systems, the need for high-quality data, and the requirement for agents and company staff to adapt to new technologies. Additionally, there is a continuous necessity to update and maintain the AI system to keep it effective and relevant.
3. Potential controversies may revolve around privacy concerns, as AI systems require access to extensive personal data to offer personalized recommendations. Another contentious issue might be the potential for AI to displace human jobs, although in this context, AI is used to assist rather than replace real estate agents.
4. Real agents benefit from AI-powered property matching systems by experiencing increased efficiency, reduced manual workload, and the ability to provide high-quality service to clients, leading to potential increased sales and revenue. Buyers benefit from a more personalized property search experience and quicker identification of real estate that meets their preferences.
Key Challenges or Controversies:
– The accuracy and bias of AI algorithms can pose challenges. Biases in the training data can lead to unfair or discriminatory results, which can harm clients and the company’s reputation.
– Integration with existing systems and workflows can be difficult, requiring substantial initial investments and adjustments to business processes.
– Data privacy is a concern as the system needs to handle personal information responsibly to maintain client trust and comply with regulations like GDPR (General Data Protection Regulation).
Advantages:
– Increased efficiency and productivity by automating matching processes and reducing time-consuming manual searches.
– The ability to identify unique buyer preferences and uncover hidden property gems that meet these needs.
– Enhanced customer experience due to more accurate and faster property matches.
Disadvantages:
– High implementation costs which may include purchasing AI software, integration, and training employees to use new systems.
– Risk of unemployment or role change for real estate agents if AI begins to replace tasks traditionally handled by humans.
– Dependence on data quality; inaccurate or incomplete data can lead to poor recommendations and unsatisfied customers.
To explore more on real estate and technology, here are suggested related links:
– National Association of Realtors
– Zillow
– Realtor.com
– Institute of Real Estate Management
These are reliable and well-known sources offering varying perspectives on real estate and associated technologies.
The source of the article is from the blog mivalle.net.ar