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With the help of data science, Housingman helps you choose a house according to your personality

Vishal Krishna
6th Jan 2018
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Bobby Reddy and Rajendran have created enormous amounts of data on what people really want out of a property, which helps builders track and win over their leads better.

While websites like Magicbricks and 99Acres may help you buy and sell a house easily, they do not help match the property with a user’s personality. Say, you are a pub crawler; then, you may prefer a swanky apartment near your favourite bar in Indiranagar.

Making this possible is Housingman.com, which wants to help home buyers with this unique twist of matching property with their personality. Once on their website the buyer has to answer and is matched with the right builder based on the availability of inventory. This portal solves the lead-generation problem for the builder and provides them a ready supply of people searching for homes.

Housingman team

Housingman is the brainchild of Bobby Reddy and Rajendran R. They met in Bengaluru in 2015 over a business meeting and convinced each other that there were several problems that they could address in the real estate industry:

  • In the current sales process there is a colossal wastage of leads due to uncoordinated responses to customer queries.
  • There is no follow up with customers.
  • Leads are not organised by the builder’s team.
  • Sales team follows cold leads, which is at a high cost and is very low in conversion.
  • The tele-calling process is weak because they make cold calls.
  • No proper matchmaking is ever done with the leads and their specific requirements.
  • This method hasn’t changed for over two decades.

“I was leaving for Sydney to work, but Bobby’s idea sounded compelling so I stayed back and began to focus on how technology could solve the persona matching for a person and his house,” says Rajendran R, co-founder of Housingman.com.

Bobby is a serial entrepreneur and has over 20 yrs of experience in real estate and he always felt that there is a huge gap between customers and builders. “There has been a big mismatch between customer requirements and builders inventories,” he explains.

The company was set up in September 2015 with several business models. Initially, in January 2016, they started with deals and discounts on new properties. Through this concept they were able to generate a good number of leads organically for their business and, in turn, for the builders. The company only displayed CREDAI-certified builders on its portal. Initially, it made its money by charging two percent on closure of the deal between the builder and the buyer. “We also used to provide exclusive digital marketing to builders to make additional money,” Bobby adds. However, in April 2017, they realised that they could not scale up this business model because builders did not want to do deals.

They quickly jumped on to a brokerage model where instead of recruiting their own sales executives they started giving leads to street brokers. In this model they share the revenue with the brokers.

The company has launched a broker app where leads are shared to brokers. The brokers work with the lead to connect to the builder. This model enables the company to reach out to as many unsold properties and it doesn’t have to employ a sales team to sign up every builder. They have a lead enrichment engine (ICREM), which has helped them profile customers more effectively. Their conversion ratio is now more compared to other competitors like AnnaRock and PropTiger. They are revisiting a bidding platform and are creating a digital real estate expo. “The platform works on predictive modelling to observe customer behaviour and preference,” Rajendran adds.

He adds that through technology and cognitive tools the company can capture the market in a very short span of time with less capital.

“In real estate segment, we are the only ones to break-even operationally within two years,” says Bobby. Currently, the company is in two cities and by mid-March hopes to reach eight cities. In the last six months the company’s GMV is Rs 150 crore with a revenue of Rs 3 crore.

The company has received seed funding of $1 million from Indus Homes Pvt. Ltd. In Bengaluru they are working with all leading developers such as Prestige, Brigade and Sobha. According to CREDAI, real estate is the second largest employer after agriculture and is slated to grow at 30 percent over the next decade. The Indian real estate market is expected to touch$180 billion by 2020. The housing sector alone contributes 5-6 percent to the country'sGDP.

But there are challenges, which are:

  • Understanding customer needs
  • Providing the right information to the customer
  • Profiling the customer
  • Right matchmaking with builder

“There is immense competition in this field and data is the only driver that can redefine the way builders can discover buyers,” says Sohel I S, CEO of HDFC Red. This is what Housingman.com wants to solve with data science. The company has grown to a team size of 30 and the team is hopeful that the real estate industry wants to bet on matching personas to the property rather than going behind blind leads.

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