How is the multi-billion real estate sector doing in a data-driven world? The industry sits on loads of data gathered about property, their use and its inhabitants. However, its players can’t benefit from this wealth of information due to slow digitization — internal data is frequently enclosed in silos, and access to external data sources is limited.
This technological gap provides great business opportunities for investors and technology companies. Forward-thinking real estate players have already partnered with IT providers and started raising awareness of data value by actively experimenting with data use cases in real estate software development that boost customer-centricity and cost-efficiency.
Let’s review a variety of data sources in real estate, popular data use cases, and challenges for data-driven real estate companies.
Sources of Real Estate Data
Real estate players, be it investors, landlords, property buyers, or tenants, have access to multiple data sources that help them see a bigger picture and better estimate opportunities and risks.
For instance, investors used to give their best guess of property value based on rent rolls, net revenue, and their intuition. Now, they take into account detailed market reports, local infrastructure development plans, demographic reports, and earthquake and flood maps in order to accurately evaluate property.
Property owners and landlords can source a wealth of data about the building and tenants from the IoT ecosystem of embedded sensors, actuators, and cameras, which could help them provide better tenant experience and boost building efficiency. At the same time, they can better evaluate prospective tenants by screening their renting, financial and criminal background and even analyzing their social media accounts.
Tenants can use powerful real estate search engines to see beyond basic characteristics and choose their future home based on the amount of sunlight it gets, noise levels, nearby schools and gyms, expected construction projects, and more. They can also take a look at Yelp reviews or take a virtual tour to the neighborhood.
Popular Use Cases for Real Estate Data
In order to accumulate data and benefit from it, the real estate sector needs to implement smart technologies. Ideally, companies would need a digital ecosystem with shared access to important assets and collaborative tools for all real estate players. A platform of such a kind can be used for the following purposes:
Making Buildings Smart and User-Friendly
A real estate platform that’s able to communicate with embedded objects, such as sensors and cameras, automatically accumulates property- and user-related data. The collected data can touch upon real estate operations, space usage, utilities, technical state of the building and its systems, and more.
As a result, property managers are able to spot and eliminate problems in the shortest period of time and build proactive maintenance workflows. Data empowers managers to decrease energy consumption and operational costs, enhance the building reliability and sustainability, and align services with tenants’ requirements. For instance, smart systems can recognize when tenants leave the space and adjust the temperature and lighting accordingly.
Evaluating Investment Opportunities and Property Costs
Unified data on local and global real estate market trends, prominent deals, capital, and up-to-date ‘for sale’ offers ensures a high level of flexibility for property investors. Real-time analytics helps them react fast to opportunities, provide stakeholders with relevant reports, and ensure process transparency.
Alternatively, accumulated data enables property owners to expertly evaluate properties and set the most adequate selling or renting price. While such common factors like the property’s size, the number of bedrooms, the neighborhood, and historical transactions usually help estimate the price, AI-powered data analytics can pick up additional non-linear relationships between the property characteristics and its desirability. As a result, real estate professionals are able to see price-impacting differences in even seemingly identical units in the same building and quote them accordingly.
Optimizing Development Costs
With necessary data at hand, such as development possibilities, requirements of future residents, financial, construction and architectural information, it’s possible to automate preliminary property analysis and substantially save time and costs. Process digitization allows considering more development options than it was possible before and making alterations to the project without missing the target deadlines.
Digitizing Paperwork
Paperwork digitization is not only a must-have of real estate automation but also an additional data source. Digitizing lease contracts, insurance policies, bank statements, and other documents helps prepare the documents for due diligence and ensures process transparency.
Data Challenges in Real Estate
Being a late adopter of digital technologies, real estate faces both unique and common data-related challenges:
Absence of a Data-Centric Mindset
As mentioned earlier, real estate generates loads of data. However, this data is distributed across organizational silos and fails to spread evenly throughout the real estate value chain. An aggravating factor is the absence of the right mindset geared towards supporting important decisions with data.
The push to developing a data-centric mindset should be promoted by stakeholders who need to ensure unification of data from internal and external sources, develop in-house expertise, and enable top-down data-related changes. For instance, to handle data efficiently, each data user should learn how to read and see data from different angles and apply this analysis in their decision-making process.
Sensitive Data
Real estate accumulates highly sensitive data, such as personal and financial information, and holds valuable corporate intellectual property. As the industry gets digitized, data protection becomes a key priority. The failure to detect and solve security breaches can severely impact the company’s reputation, since gaining control of critical business systems can lead to not only data theft but also physical harm and operational interruption.
As a result, data processing workflows have to comply with data privacy regulations and provide protection from data leaks and cyberattacks. Unfortunately, data protection laws in different countries may collide with industrial digital processes and hinder technology adoption. For example, integrated Google Street View may violate someone’s privacy and thus be banned in a particular country.
Additionally, to build user trust, real estate companies need to encrypt and anonymize personal data, provide restricted role-based access for employees, and run audits for identifying possible security gaps.
Tech Companies vs Property Managers
When it comes to property management, owners prefer partnering with technology service providers to implement software that will let them use data in a profitable way. Eventually, such technology companies become intermediaries between tenants and real estate owners, taking over property management responsibilities.
In such a situation, property managers have few options — they either learn to apply advanced tools and analytics or leave the market. Considering this, real estate companies are likely to be attracting a completely different kind of talent right now — technically-savvy real estate software operators rather than traditional property managers.
Data is an Asset
The real estate industry is getting digitized, rapidly shifting towards conscious use of data both in daily routine and strategic decision-making. Data has become integral to making buildings smart, personalizing tenant experience, and automating time-consuming processes. In these circumstances, real estate players have to not only invest in new technologies, but also re-evaluate their skills and adopt new digital-first methods.
