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Ravi Bhushan

Ravi Bhushan, Group Chief Product and Technology Officer of, and, is an industry expert with close to 12 years of experience in technology and digital domains. He came onboard as a Vice President with key focus on enhancing product and technology functions. In his current role, Ravi spearheads new-age technology innovations to strengthen the ground product, design and engineering aspects.

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Machine Learning Arrives in Real Estate: Opens Up Door to Cost Efficiency and Productivity Improvements

There are many more similar opportunities for companies to reinvent some of the traditional solutions resulting into more cost effective and efficient outcome.

Machine learning, a sub area of Artificial Intelligence, gives computers the ability to learn without explicitly being programmed. Recent advancements in this field has opened up immense possibilities to solve some of the problems which otherwise were very difficult to resolve with traditional system.

Traditionally, most of the problems were solved through a rule based system driven by experts. This approach works well for problems in which experts have complete control of the solution, however there are many problems of which, the solutions evolve with time and experience. The challenge with a traditional approach is that the system can only be as good as experts from the past world, thereby becoming a huge limitation in a fast dynamically changing world. It is very difficult to cope up with complexity of rules and their mutual influences over a period of time.

Due to these reasons, problems which constantly required evolved solutions with input data, were not immensely flourishing. Problems like anomaly detection in large data set, auto classification, efficiency prediction, image recognition etc., were not resolved elegantly until machine learning came out of academia and started finding practical applications in different verticals like automobile, marketing, medicine etc. Real estate is not an anomaly here. In my view, there are many problems which can be solved very smoothly using machine learning., & being a technology-led real estate company, we sensed a big opportunity here to make our systems more efficient and predictable. We applied machine learning approach for various things like lead quality prediction, user recommendation and the likes. It is heartening that it came as a boon for cost reduction supply collection.

Being supply aggregator platform at, we allow developers, brokers and home owners to upload their listings on the platform. Traditionally, a huge team internally used to check all the data points or images being uploaded by these users to check if they were relevant or not. We realised that we have millions of listings in our systems and that over last so many years we have also marked what is right and wrong. We tried semi-supervised machine learning and delegated the task of checking the quality to machines. In few iterations, it was found that computers were able to achieve the objective very effectively. This led to more than 70% reduction in cost and the good part is that the system is getting more and more intelligent with time as it gets more data for learning.

There are many more similar opportunities for companies to reinvent some of the traditional solutions resulting into more cost effective and efficient outcome. As a technologist, I am excited to witness these developments where technology is not only leading to offer better outcomes for our consumers, but also helping companies remain learner for better growth.

Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house

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