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• In this PropTechBuzz podcast, Michelle Suarez, Head of Product Innovation, PropTechBuzz hosts Anil Kaul, CEO of AstraNest AI for an engaging conversation on the present and future of AI technologies in the PropTech sector revolutionizing the real estate industry.Â
• Experts predict that the global market share of data analytics in real estate will reach $ 15 billion by 2027.Â
• Even though real estate data related to market volume, price trends, demography, etc. is widely available, there is a lack of tools and resources that can analyze this data in simple terms for the consumers.Â
• AI-based data analytics platforms aggregate data based on factors like comparative pricing of similar properties, market trends, and condition of the property. These tools also predict the future appreciation in the market value of the property.Â
• Anil Kaul and his team at AstraNet have led several innovations in AI-based conversational interfaces. Their chatbot can customize its questions for each unique visitor and each response generated goes through a second round of fact-checking before going LIVE.
In this PropTechBuzz podcast, Michelle Suarez, Head of Product Innovation, PropTechBuzz hosts Anil Kaul, CEO of AstraNest AI for an engaging conversation on the present and future of AI technologies in the PropTech sector revolutionizing the real estate industry. Anil Kaul has led several successful projects with Fortune 500 companies in the field of data analytics optimized by ML and AI technologies and is currently the founder of AstraNest, a cutting-edge AI-powered data analytics platform for the US residential real estate industry.Â
Apart from experience in firms like McKinsey and Company, Anil Kaul holds a PhD in Marketing from Cornell University and has published articles in major academic and industry journals. As a seasoned professional and thought leader, he is regularly invited by prestigious universities such as Cornell, Yale, and Dartmouth to share his insights.
Anil Kaul began his journey in this field 20 – 25 years ago by bringing data into decision-making. Anil Kaul founded and led the predominant AI and machine learning services firm, Absolute Data which he successfully sold to the Silicon Valley-based Infogain Corporation in 2020.
Data analytics has emerged as the game-changer in the real estate industry as clients, property owners, agents, and real estate professionals are increasingly turning to data to make informed decisions. Experts predict that the global market share of data analytics in real estate will reach $ 15 billion by 2027.
Anil Kaul and his team realized the untapped potential of data in the real estate industry quite early. From a sector where data was scarcely available, real estate has witnessed an information boom in the last ten years. Data related to historical market volume, price trends, demography, and various other facets of real estate is available even in the public domain. However, a steep learning curve is involved if real estate agents or customers want to analyze this data for their decision-making.
AI-powered data analytics platforms provide a set of tools and techniques to users that are capable of processing large volumes and data and can generate actionable insights based on users’ queries. Anil Kaul explains the impact of these technologies on buyers’ decision-making through an illustrative example.
The most critical decision that buyers have to make is bidding at the right price. Buyers must make an offer that reflects the most accurate valuation of a property. If they bid too less, they might lose the offer. But if they bid too high, it’s going to have a long-term impact. Overbidding by a marginal sum can lead to a drastic accumulation of debt over long mortgage periods of 15 – 20 years. Making the most accurate offer based on a number of factors can significantly improve a buyer’s chances of acquiring a property and lessen the long-term risks associated with mortgage payments and re-selling.
AI-based data analytics platforms aggregate data based on factors like comparative pricing of similar properties, market trends, and the condition of the property. Tracking real-time changes in the market is of key value in making these calculations as real estate market prices can fluctuate constantly. Another significant information that buyers seek is whether there are other properties in a similar range available in case they lose this bid. These tools also predict the future appreciation in the market value of the property.
Based on key data points informing the algorithm, buyers can arrive at their final decision of making an offer with precision and confidence. That’s what advanced analytics is all about. Traditionally, the buying process involved a rudimentary analysis of easily available data but AI is changing that. It pulls in data from various sources, analyzing it using advanced algorithms, and most importantly, providing accurate predictions to buyers in an easy-to-understand format.
Anil Kaul explains that real estate is one of those industries where every deal is unique. Even though 90 – 95% of the transactions tend to be standard, there are always little details and quirks unique to every property. While technology takes care of the standard processes, real-life guidance is ensured to close the deal comprehensively.
There are a lot of market and regulatory changes that mark the current landscape of real estate. Real estate advisors have to ensure that their services add value to the customers’ interests. New-age technologies like AI and ML have played a huge role in today’s markets by integrating real-time market data available from various proprietary and public sources. AI has evolved to a stage when large language models (LLMs) and predictive analytics can be combined to generate actionable insights from data.
The success of customer-friendly companies like Amazon has proved that leveraging data and AI technologies to meet customer demands faster and more efficiently is the most preferred future strategy for businesses. AI-driven data analytics in the residential real estate market in the US offers cutting-edge innovations to transform the consumer experience through proactive data-driven guidance to buyers, sellers, and agents.
Conversational interfaces integrate the power of LLMs and predictive AI to understand customer prompts and give them accurate responses to help them make the best property-related decisions.
Anil Kaul and his team at AstraNet have developed a number of innovations in the field of AI-based conversational interfaces. Often, these conversational AIs ask the users a series of questions to assess their needs and make appropriate suggestions. Through a unique algorithm, the AstraNet chatbot is enabled to customize its questions for each unique visitor. This approach reduces the redundancy of questions and derives maximum information in each go.Â
To ensure that the users get only the most accurate and relevant responses, there is another in-built AI model that tests the first AI’s responses before it goes LIVE. The second AI acts like a fact-checker which gauges the response on a number of parameters including legal and regulatory norms. The two-step approach significantly improves the accuracy of the model from 80% to 96% (based on statistical probability). This step is crucial to ensure that the AI generates advice based on factual accuracy and follows the legal and ethical regulations that govern real estate.
AI-powered data analytics will prove decisive in marking real estate’s shift into a new era of digital decision-making. The massive availability of data from MLS (multiple listing services), proprietary data providers, and publicly available platforms has accelerated the growth of data technology in real estate. Information is available on the different types of homes available in a particular neighborhood, amenities, likely appreciation of property value, and condition of the property. AI-based data analytics platforms not only empower consumers but also boost agent productivity by an impressive four to five times.
As AI-based data analytics tools provide critical suggestions related to real estate investments, developers should be cautious of the quality of data and the responses made by AI. Most AI and data analytics innovations are focused on reducing redundancies in data and on providing the most accurate responses based on customer queries.
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By Proptechbuzz
By Ravi Kumar
