How does annotating data, whether images or text, fuel AI applications in real estate?
It's fair to say that right now, it's very rare to find a field that doesn't use AI. Real estate is no exception. Through data annotation and data classification, real estate professionals can leverage AI to improve the efficiency and accuracy of their processes.
Data annotation plays an essential role in real estate AI. By providing accurate and consistent labels to data, experts can train AI models capable of understanding and interpreting real estate-related images and text. Image annotation can identify and tag key elements such as buildings, rooms, kitchens, swimming pools, gardens, etc., making it easier to search and categorize real estate.
Similarly, text annotation is used to classify and label property descriptions, customer reviews and other relevant documents. This data classification step provides a clear structure and enables AI to understand contextual information, helping real estate agents to quickly find the information they need and improve their decision-making.
In this article, you'll discover 5 types of AI products that can be built using supervised learning models and data annotation techniques.
1. Evaluate property prices by annotating unstructured data available on the Internet
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, AI identifies similarities and differences to other similar properties in the same area.
2. Annotate real estate data to accurately predict market trends
AI can predict real estate market trends by taking into account 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 areas where property prices are likely to rise or fall in the future, whether you're an investor or a real estate agent.
3. Manage tenant or landlord files by automating content labeling
As a real estate agent, AI can help you manage your files by identifying the documents needed to create them, extracting the most important information and tracking events through data classification. No more time wasted performing these tasks manually. What's more, AI can help to automatically create ads on a website.
4. Analyze property energy performance accurately and reliably with Data
AI makes it possible to analyze energy cost information to better understand the energy consumption of real estate. DPE diagnostics and their complex calculation methods become obsolete. What's more, AI can be used to regulate energy sources in real time and determine whether they are really needed.
5. Improving customer service with Chatbots
With the installation of a chatbot, customers can ask the AI basic questions. If a more complex problem is present, an appointment will be arranged automatically. Using supervised learning models based on annotated data, chatbots are able to answer basic questions posed by customers. If the problem encountered is more complex, the chatbot is able to automatically schedule an appointment with an appropriate expert. This approach significantly improves customer service by providing fast, accurate and efficient answers, while guaranteeing a personalized and satisfying experience for every customer.
AI has multiple use cases in real estate. If you're a data scientist, developer or professional in this sector, 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.
