5 AI use cases in Real Estate
🧐 How does the annotation of data, whether images or text, fuel AI applications in real estate?
It can be said that at this moment, it is very rare to find a field that does not use AI. Real estate is no exception. Through data annotation and data classification, real estate professionals can take advantage of AI to improve the efficiency and accuracy of their processes.
Data annotation plays a critical role in real estate AI. By providing accurate and consistent labels to data, experts can train AI models that can understand and interpret images and text related to real estate. Image annotation makes it possible to identify and mark key elements such as buildings, rooms, rooms, kitchens, pools, gardens, etc., making it easy to find and categorize real estate.
Likewise, text annotation makes it possible to categorize and label property descriptions, customer reviews, and other relevant documents. This data classification stage provides a clear structure and allows AI to understand contextual information, helping real estate agents quickly find the information they need and improve decision-making.
In this article, you will discover 5 types of AI products that can be built using supervised learning models and data annotation techniques.
1. Evaluate real estate prices using the annotation of unstructured data available on the Internet
The AI uses several criteria such as location, current prices and compares the different properties available for sale on various websites. By analyzing and processing a considerable amount of data, AI can accurately and objectively assess the price of a specific property. By taking into account the unique characteristics of each property, the AI identifies similarities and differences compared to other similar properties in the same region.
2. Annotate real estate data to accurately predict market trends
AI can predict real estate market trends by considering factors such as economic fluctuations, interest rates, demographic trends, upcoming infrastructure projects, as well as demand and supply trends. By analyzing this annotated data, AI can identify potential investment opportunities and provide valuable insights into regions where real estate prices are likely to rise or fall in the future, whether you are an investor or a real estate agent.
3. Manage tenant or owner files by automating the labelling of their content
As a real estate agent, AI can help you manage your records by identifying the documents needed to create them, extracting the most important information, and tracking events through data classification. No more time wasted doing these tasks manually. In addition, AI can contribute to the automatic creation of ads on a website.
4. Analyze the energy performance of goods accurately and consistently using data
AI makes it possible to analyze information about energy costs in order to better understand the energy consumption of real estate. DPE diagnostics and their complex calculation method are becoming obsolete. In addition, AI can be used to regulate energy sources in real time and determine if they are really needed.
5. Improving Customer Service with Chatbots
With the installation of a chatbot, customers can ask basic questions to the AI. If a more complex problem is present, an appointment will be organized automatically. By using supervised learning models based on annotated data, chatbots are able to answer basic questions asked by customers. If the problem encountered is more complex, the chatbot is able to automatically schedule an appointment with an appropriate expert. This approach makes it possible to significantly improve customer service by providing quick, accurate, and effective responses, while ensuring a personalized and satisfying experience for each customer.
💡 AI has multiple use cases in real estate. If you are a data scientist, developer, or professional in this sector, do not hesitate to contact us to find out more and use our Data Labeling Services! Make an appointment to be accompanied and to use our services to accelerate the construction of your AI products.
