Rsquare is digitising the search for office space

Image courtesy of Rsquare

Property technology – or proptech (i.e. the digitisation of real estate) – is now in the spotlight in Korea. This isn’t really surprising as the lockdowns following COVID-19 have made it difficult to see a property in person before deciding to buy/lease/rent it.

With proptech, individuals and organisations can now virtually inspect a construction site, commercial establishment, or residential property. And that’s just one innovation.

Enter Rsquare, a Seoul-headquartered startup that built an AI-based platform that lets users compare multiple properties and find the right office space. It also helps with logistics centres, interiors and remodelling, building purchases, as well as data analysis.

According to Rsquare CEO Lee Johnwoo, they’re able to provide customers with the right information by building a database with more than 150,000 entries in Korea. The company gathered the information manually via a nationwide survey of the local commercial real estate industry. In cases where new buildings are built, Rsquare executives and employees visited the sites in person to carry out the survey.

“In the case of leaseholders, we have all the information about the tendencies of building owners and building managers, including their preferred type of tenants, the number of parking areas and spots, parking hours, and the number of vacancies,” Lee shared.

For tenants, Rsquare processes information such as when the tenant contract ends, the expected moving date, and if there is a demand for interior design when the new tenant moves in.

Their data can be categorised into three different areas: real estate data, customer data, and data that pertain to relationships between real estate and the customer.

Rsquare, however, isn’t just a database service for commercial property.

“We are also developing a data analysis tool that automatically generates reports when customers seek specific information,” said Lee. “We are also thinking about ways to present our gathered information. Furthermore, we are also steadily adding people to the development team and field data team.”

The Rsquare business models

Lee says that Rsquare’s philosophy on technological advancement can be understood as “data labelling”.

“This allows us to directly generate commercial real estate data and use it for research and consulting purposes. To this end, we collect data directly for sale and handle property deals ourselves,” he explained.

Lee believes that Rsquare’s business models have “tremendous strengths” when applied to technology.

“The first point of strength is the purity of the data for sale,” he said. Unlike other advertising services that are said to have false offerings, Rsquare – claims Lee – has “perfect authenticity” data.

“The second point of strength is the relationship with customers,” he shared. “Rsquare offers direct sales to customers, supports direct brokerage, and even provides interior design to residents.

“We are also applying this business model to overseas markets. For example, in Vietnam, the commercial real estate database was collected directly through locals which includes information on building and office owners. Since Vietnam possesses little public data, Rsquare invests more in securing data in the country than in Korea. We would like to refine and analyse this better, and provide meaningful secondary processing data,” Lee added.

Gazing into the future

Lee also believes that AI and machine learning (ML) will have an influence on the proptech sector for the next three to five years. 

“Proptech companies provide prediction and recommendation services for various metrics through regional and customer analysis. In some instances, companies leverage ML to buy properties when the predicted market value is low, then resell when the value goes up to profit. However, real estate data does not have enough accuracy in prediction results compared to data in other fields,” he observed.

“For example, if the error between the forecast price and the actual transaction price is greater than expected, the company that purchased the building may suffer a huge loss. As a result of this, technology penetration is slow,” Lee added.

The Rsquare CEO predicts that technological growth in affordable price forecasts and transaction automation areas will continue, but it is not expected to get there as quickly as expected. 

“Instead, ‘classification technology’ and ‘recommendation technology’, which structure unique and open information together to assist human judgement, are expected to become mainstream,” he said.

Lee Johnwoo, Chief Executive Officer at Rsquare. Image courtesy of Rsquare.

Lee likens proptech to medical technology, which has been using AI to diagnose diseases and automate prescriptions on behalf of doctors. 

“It is still an analysis technology that assists with people’s diagnosis. AI has the ability to check details – even the remote possibilities that people may miss – so the ability to analyse the primary analysis cannot be compared. You can diagnose cancer by finding small dots on X-rays that are not even visible to the human eye and diagnose the possibility of diabetes while analysing years of records in periodical terms. Therefore, the misdiagnosis rate of doctors is greatly reduced, and this is how AI technology and the medical community collaborate efficiently,” he explained.

“We believe that the real estate sector is similar. It may not be at the level of human life, but it will be difficult to rely entirely on AI’s judgement for quite some time because it has so much to do with ownership of large amounts of funds and assets being transferred. Instead, if you analyse decades of information, and information around a surrounding area in multiple ways, and provide experts with all the possibilities that can occur, experts will be more efficient and reach conclusions with high accuracy. As a result, we expect significant changes in the market as forecasting, which is an issue in the real estate market, becomes more sophisticated,” Lee predicted.

Tech interests

Rsquare is currently developing some form of matchmaking technology, said Lee.

“Amazon understands the needs of an individual and recommends products tailored to them. Netflix does the same with movie recommendations. However, these customised recommendations have not yet been made for the real estate market. This is because transaction information is difficult to digitise due to the lack of frequency and many variables in the offline market,” he said.

According to Lee, Rsquare plans to provide customised recommendation services by analysing the company’s pure sales data and customer data.

“We have a strong interest in the blockchain and metaverse as well. Currently, we do our searches on a Chrome browser, but we believe in the future, we will be able to enter the metaverse and ask avatars of each company, or have transactions using virtual currency. We think blockchain technology is likely to be used to guarantee the authenticity of information even offline,” he concluded.