Artificial Intelligence, one ofthe most searched technology word these days on Google’s search engine which in itself is being managed by AI, has made its presence felt in every conceivable domain. Manufacturing, healthcare, business, teaching, space research, entertainment, every industry is being transformed at the speed of thought and the time it takes for a machineto understand the patterns in a data set. However, we have barely scratched the surface of its limitless potential. There are many sectors which have yet to implement AI-powered methods, or the implementation of which has not become common knowledge yet. India’s rental real-estate, for instance, presents such a scenario.
The typical Indian rental home seeker checks 14 properties over 12 days with 5-6 different brokers before finally being able to select a preferred house. In the meanwhile, a long and arduous process happens which involves nagging agents, long periods of complete inactivity and days spent in uncertainty. The process is inefficient, cumbersome and fragmented. The Indian home search process even in this day and age is largely an offline process – much like it was 30 years back. Not for much longer, however. Today, data and AI technology is being used to fundamentally transform the way people rent homes. Let us see how.
Umang works with an IT firm in DLF Phase 3, Gurgaon. He is looking for a two BHK house for his family which includes his wife and a kid. His budget is 25000 per month. He is ready to travel upto 8 KM but wants a gated community with a park for his kid. In Gurgaon, 8,000 home seekers rent a house every month. 100s of them have similar profile and requirements as Umang. Expand that frame to a year and you will find 1000s of people who would have/are going through/are likely to undertake the same journey as Umang. Can Umang benefit from previous user experiences to get his ideal house? Can he in turn benefit others?
This is where AI comes into the picture, through a method known as collaborative filtering. It is a process of making intelligent predictions (filtering) about the interests of a user by collecting preferences from many previous users (collaborating). This technique is widely used across social media, retail, and streaming services. It requires authentic data in abundance to make meaningful & accurate recommendations, and what better way to source data than from the users themselves? AI allows true democratization of the information space as the data provided is completely unbiased and empowers prospective home seekers much like TripAdvisor’s user reviews help potential tourists. However the impact is much greater as such authentic data helps an individual or a family decide upon a property to stay for a long-term.
Finding a home also involves analyzing a lot of variables, which can be fundamentally segregated across three variables-Location, Aspiration and Budget (LAB). Within this broader framework lie numerous preferences, queries, concerns, suggestions and information shared by thousands of users which allow AI-based algorithms to make the home seeking experience much easier for each successive user. As more customers are served, this collaborative filtering system keeps getting better.
Anyone in the real-estate industry would agree that a large database of inventory is one of the key factors for success in this domain. It improves one’s ability to better serve the home-seeker by offering more choices and a large canvas to pick and choose from. Although homes cannot be customized entirely, AI driven data technology helps to identify the best possible house for a home-seeker from a large selection and can simultaneously compare a large number of parameters in real-time to give precise insights. For instance, we at FastFox have developed a proprietary AI-based algorithm that continuously churns massive inventory data of the entire Gurgaon region to regularly supply its users with relevant data on properties that suit the users based on their list of preferences and profiles. The algorithm after analyzing each property on 108 parameters, informs users about a list of best-suited properties, which they can evaluate independently at designated times through our unique ‘Open Houses’ inspection model. Thus an end-to-end customer service framework is created without the involvement of any third party, with the AI-based technology playing a central role.
Huge data and its correct analysis is the key to developing better experiences in the times to come. By preparing a Knowledge graph of all possible home inventories, whether linked or unlinked, helps users to take smarter decisions. From being at the mercy of agents with ulterior motives to being empowered with a smartphone and a plethora of choices, the modern Indian home-seeker’s journey to tech-transformed home-searching has just begun.
(The author is CEO & Co-founder, FastFox.com)