Digital Transformation of Real Estate: New Business Models

May 18, 2018 | | Insights

Exclusive minutes from Propteq Europe 2018 session on the Digital Transformation of Real Estate: New Business Models

What is real driver for the real estate technology and digital transformation?

Online investment platforms and bringing home ownership to the masses. That is the key drive for digitalisation.

Attendee: Is that a new business model or transforming an existing process?

Attendee: Nothing new from the property sourcing side, as you can look and access a property portfolio online whether it is £50, £500 or £5000, you can access it all online. You don’t even have to handle the property management element. This can be taken care of by certain platforms, essentially a new business model to access investment.

Attendee: At the time of the recession, things were done in an old way, but the consumer had changed considerably. Things were done online, but when it comes to new build property in particular, you can not get far down in that journey. That’s why in that industry, we’ve realised they need to incorporate more technology.

Attendee: From the rental sector, potential tenants can go through everything online and don’t need to interact with another human being. Real estate seems to pull back a little there, because there is no trust and tools are put in place to ensure trust. What we see is that people pull back from a deal before they get to the end process, so efficiency is not as effective as it should be. The real estate technology industry can make a lot more money once companies put trust in their consumer with the technology.

Attendee: Many buyers still want to connect and negotiate with another human being.

Attendee: In commercial real estate there is a shift in attitude; tenants now want to be using an app to do something in their work environment. One theme is that the company actually wants to own the data, and manage the transaction. This can help in predicting changes in volume, buyer demand, and use machine learning to understand logistics and collect data.

Attendee: I see a lot of companies that are using data and making real estate property a much more attractive investment. They use predictive property analytics and machine learning to estimate what will happen in the future, not based on just previous house price movements but also key infrastructure products that are coming in, to understand which areas will perform.


Attendee: It’s all about collaboration, people coming from different industries into the real estate market and working together, specifically between the logistics and real estate industries. Use the data together to come up with ideas of where people need to be and where consumers currently are.

Attendee: Retail is being taken over by amazon and alibaba, whom are building a lot more warehouses that are quite far away from the city centers. It is going to be interesting what will happen to small to medium size logistics warehouse spaces, who currently the smaller businesses that could well not be in business in the next 10 – 15 years.

Airbnb – what is the future for hotels?

Attendee: Many hotels are already digitised, as is done online.

Attendee: Our technology allows you to very quickly scan a hotel. For example, I can request for a room with a view, on the 3rd floor and the system shows you all the possible rooms. We don’t list hotels, but instead we list the rooms.

Attendee: Customer experience is very important, in Oslo there is hotel where you do everything by yourself. Nobody is there to serve you, so you scan, take card, and get your room number. Nobody works there, however if individual has a problem, not everything is available. You could however, have certain times where people are around to help, rather than for 24 hours.


Propteq Club is leading the digital transformation of Real Estate Technology by bridging the gap between PropTech startups and the Property industry. Our members are at the forefront of the ecosystem and connect with the people that matter. Find out more.