The real estate industry is seeing a paradigm shift towards the use of AI and advanced analytics to improve efficiency, profitability, and to make it more service-oriented. The key focus being improved customer experience with digitalized and data-driven solutions.
Leveraging data and creating value from it, is the new goldmine in the real estate sector. The amount of data that is available and accessible, is much more than what it was a few years ago. Information such as net effective rents, market demand, tenant information, etc. along with datasets from IoT sensors, social media, geospatial information, and satellite imagery is being used to deliver industry differentiated solutions.
AI can streamline and transform operations where large amounts of data are involved. It makes sure that the expensive decisions are data-driven and unbiased. It also augments the current market with different tools which would fasten the process and improve the customer experience.
Key use cases in the industry
Challenges Faced by the Real Estate Sector to Leverage AI and Advanced Data Analytics
According to the Morgan Stanley Digitization Index, real estate is the second least digitized industry in the world. So, the challenges to adapt to the new trends will be:
Brillio’s digital transformation strategy for real estate companies is based on our core principles of a product-centric approach with an increasing focus on insights-driven operations/decision making. Our expertise in data analytics and experience in the real estate industry will help to speed up the process of adopting the latest trends and building a competitive edge. Using AI and advanced analytics, we will help provide a solution that focuses on leveraging the data and improving customer experience to optimize the processes and costs.
We chalked out a solution for two major use cases in the industry. Our Solution guiding principles being.
Image Analysis and Interactive Maps
Interactive maps to visualize and to understand the data better for planning and investment decisions using location and Image analysis to detect change over time.
Effective Resource Allocation:
Using actionable insights to effectively allocate the resources for building management and maintenance.
Predictive analytics to make ideal decisions on the investment /planning.
Data from different sources is consolidated and standardized for generating insights.
Secure by Design
Secured design and wired with the right telemetry to ensure seamless access for devices and data.
Property valuation using advanced property analysis
Our solution helps owner/investors derive actionable insights which help them make decisions on property/portfolio investments. This is done by consolidating appropriate data, standardizing it, and deriving insights using our advanced analytical capabilities. We unlock insights on property price-influencing factors, non-linear relationship patterns between data and property desirability, and risk factors. Data points analyzed for our advanced property valuation
Smarter Real Estate Management
Automating building operations management in personal spaces will improve the overall occupant experience and reduce maintenance costs with effective resource allocation. In corporate spaces, it leads to improved experience and productivity of employees.
Brillio’s automated workflow for operations management:
Spatial analysis using all relevant data gives us actionable insights on space optimization for better building planning/remodeling. Key data points considered in our solution are employee data, teamwise details, footfall vs timings, common area usage, etc. Insights are derived to optimize the space usage, maximize the existing space value, and minimize the need for extra space.
Major data points for spatial analysis:
How does the future look like
AI might seem like a threat to many agents and brokers in the real estate sector, but if used in the right way, it can augment their skills and take the whole customer experience to a new level. AI still has many use cases to be explored and going to grow extensively in the coming years.
I thank Mr. Arun Kumar, Senior architect who has worked on our solution and helped me to put the article together.
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