Data Science in the Real Estate Industry

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Artificial intelligence and data analytics are changing the way we look at things and are impacting most businesses in a major way. It is already a data-driven world to some extent and even if not, it will soon be. Data and utilizing the data is key for any business to thrive and make decisions and strategies accordingly. AI is doing most of the data related operations and making things a lot easier for analysts and scientists. Like most other industries, AI and data analytics can help the real estate business largely as well. 

The real estate industry has drastically grown in recent years and is continuously evolving by inculcating various advanced technologies. The world is becoming data-driven with each passing day and every industry requires a vast amount of data to process and carry out operations in an efficient manner. The real estate industry is rapidly shifting towards data analytics technology as it has the ability to analyze structured and unstructured data and help the industry to drive strategic decisions and predict recent trends that help these industries to channelize their activities in a particular direction.

The real estate business is not just about locations and properties. It involves numerous data about buyers, sellers, finances, preferences, and a lot more. All these can be used to boost the business hugely. And thanks to data science this is all easy now. 

Let’s take a look at some of the benefits data science and analytics offers to the real estate industry:

  • Recommendations: It can often turn out to be difficult for agents to find the right properties for the right customers. AI and data analytics can help with this greatly. By using the collected data, the larger the better, AI helps in finding the right set of properties for customers using the Recommender Systems. Real estate websites for agents use this feature a lot. The AI can come across data in many ways and eventually come up with the most suitable properties using its algorithms. This saves a lot of time and helps realtors who are struggling to find the right place. The recommendations are dependable and give great results.
  • Availability: Unlike manual effort, an AI can work all the time. It can help people all the time according to their convenience. Chatbots are really helpful in communicating with customers by automating conversations and leads towards building healthy relationships. Dependable and available at all times, chatbots can increase the customers and improve relations as well, in the absence of humans. Chatbots can be built by using Natural Language Processing techniques. Some of the open-source frameworks like RASA and DialogFlow can be used to make contextual AI assistants that are far beyond traditional FAQ interactions. They consider the context of what has been said before in order to give context-based interactive human-like replies. 
  • Useful predictions: Using predictive analysis like regression or classification models one can make very meaningful predictions that involve customer priority with the data provided to it. Regression models can predict things like the prices of specific areas based on geographical location and future and upcoming development or changes that the area may go through. Classification models can classify areas as safe or unsafe depending where crimes and thefts are more as it is a very important aspect when it comes to buying or renting a property. Various other useful predictions can also be made by these predictive models by just simply changing the input parameters supplied to them and the label to be predicted. The larger the data, the better the results.
  • Automation of property listing: There is numerous nitty-gritty when it comes to dealing with property. The realtors and agents need to pay a visit to the property in order to verify it and then take out pictures and videos in order to list them on their website. This can be time-consuming and costly. All these can be easily handled and automated by using Deep learning-based image processing technology. For initial verification of the property listed, the agents can request the property sellers to send them pictures of their property for verification of the mentioned details. Then by using Convolutional Neural nets one can easily do some basic image classification in order to verify the details provided by the seller automatically.
  • Virtual tours: People often find it difficult to manage time to go and see the properties. Thanks to AI and virtual reality, people can now take a virtual tour of the homes. The virtual walk gives a much better idea than pictures and saves a lot of time as well. More and more real estate website development services are trying to implement virtual tours to provide ease and convenience to customers. All these virtual tours 
  • Sales growth: Combining data science and analytics, real estate agents and companies can get a better idea of what the customers need and want. This, in turn, helps in delivering better and improving sales. One can easily use Google Analytics to extract the different metrics provided by them in order to draw insights from their AD Campaigns and then device their marketing strategies solely based on user interaction data and response to those specific ADs. Such analytical platforms really help a lot in boosting the sales and market recognition of any Real estate company hence helping them to draw road maps to become the market leaders.

So here were some of the possible use cases of Data science and analytics in the Real estate industry and how the vast industry can benefit from this advancing technology. In later posts we can have an in-depth understanding of each technology like Classical machine learning models, Deep Learning, Natural Language Processing, etc. and how they can be implemented for any particular use case. Till then stay tuned.

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Mightynews
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