Understanding Commercial Real Estate Data Analytics Software
The commercial real estate (CRE) industry has experienced massive growth and success in terms of technological advancements to the office, bringing out new-age obstacles that landlords, property teams, and tenants have to face. As CRE adapts to a modern workforce through the addition of tech-enabled consumer experiences, it is simultaneously establishing a new set of office standards moving forward. Likewise — as these experiences continue to evolve — the role of commercial real estate data analytics software has become a centerpiece of discussion for CRE leaders who are looking to triumph over the inevitable ebbs and flows of a recently disrupted market.
By accessing meaningful real estate analytics on your building’s end-users (its tenants), you will be able to maintain a competitive edge in the market by differentiating your assets through real-time commercial real estate insights. Now, creating an office space that will address every tenants’ needs is easier than ever before — as is generating value for office buildings.
What Is Commercial Real Estate Data Science?
In today’s world, commercial real estate analytics have taken on a data science approach. According to a Towards Data Science article, there are plenty of opportunities to apply data science practices — or using scientific methods, processes, algorithms, and systems to extract and apply insights and knowledge from all forms of data — to commercial real estate data. As they explain:
“There is huge pressure on the real estate industry to unlock the potential of big data and incorporate machine learning and evidence-based approaches in their workflows. In the KPMG Global PropTech Survey 2018, 49% of participants thought that artificial intelligence, big data, and data analysis were the technologies likely to have the biggest impact on the real estate industry in the long-term.
Consequently, some forward-thinking top executives at real estate institutions with long operating histories are pushing their firms to unlock the potential of their decades of records of transaction, valuation, asset management, listing, and other data. Simultaneously, the data provision space is maturing (possibly even overcrowding) with successful startups such as HouseCanary and Reonomy joining established players like CoStar and Real Capital Analytics, making it possible for any company interested in real estate to quickly obtain large amounts of relevant data.
However, as noted in a recent NAIOP article, real estate professionals are facing challenges figuring out how to actually utilize data. The KPMG Global PropTech Survey 2019 confirms that 80% of firms still do not have ‘most or all’ of their decision making led by data. The same report also hints at a “skills gap” — only 5% of real estate firms have transformation efforts led by someone with knowledge of data analytics.”
With this in mind, there are several ways to leverage data science in real estate portfolios. Below are just a few:
- Property Prices: Today, data-driven computer models account for up to 80% of trading and finance transactions. Thus, data science methods can help property teams aggregate and understand large data sets to cut through the noise and understand individual sub-market performance. Through property price indices, “millions of rows of noisy transaction data can be combined with information about locality, property characteristics, demographics, and more, to produce granular sub-market indices. For example, indices can pinpoint property returns in specific postal districts e.g., a WC1-index or E1-index in London, or for specific property types e.g., a 2-bed-condo-index vs a 3-bed-condo-index, while taking into account the implications of all transactions in the full dataset.”
- Automated Valuation: Technology and software play huge roles in properly estimating a property’s market value. Data science can leverage similar techniques to indexing, but instead, provide a more precise fair market value associated with a property — one that is produced almost instantaneously and at little to no cost.
- Geographic Information Systems (GIS): A geographic information system can help visualize and analyze intelligence based on one’s location. There is an abundance of information that exists on this topic, such as public amenities, population by neighborhood, and more. A GIS can help reveal public transit options, prices based on location, commuting times, and even help find properties based on preset criteria.
- Time Series Forecasts: Times series forecasting, much like predictive analytics in real estate, helps us determine where property markets are heading. Such intelligence on the market helps teams make better investments and deals, and produces higher financial returns. Data science methods can help make accurate predictions based on a set of data, determining future real estate property performance such as inflation, interest rates, GDP, and more.
The Top Commercial Real Estate Data Companies
In order to stay on top of the latest building insights, owners and property teams need to know their options in terms of commercial real estate data providers. Below is a quick list — in no particular order — of commercial real estate data companies that provide comprehensive property research software, and serve as a reliable source for any commercial investor or property owners’ database:
- CoStar Group: CoStar Group is a provider of information, analytics, and marketing services to the commercial property industry in the United States, Canada, the United Kingdom, France, Germany, and Spain.
- CoreLogic: CoreLogic is a corporation providing financial, property, and consumer information, analytics, and business intelligence. The company analyzes information assets and data to provide clients with analytics and customized data services
- PropStream: PropStream is real estate investment software that helps professionals find the best deals based on its comprehensive analytics services. Investors can view complete property profiles to target pre-foreclosures and potential off-market deals from motivated sellers, as well as determine accurate costs.
- Reonomy: Reonomy leverages big data, partnerships, and machine learning to connect the fragmented, disparate world of commercial real estate. By providing unparalleled access to property intelligence, Reonomy products empower individuals, teams, and companies to unlock insights and discover new opportunities.
- CompStak: CompStak is the leading crowdsourced commercial real estate data platform. They handle millions of data points each week to create a comprehensive, robust CRE data set.
Conduct Your Own Real Estate Market Analysis
Though it’s possible to access third-party commercial real estate research tools and resources to gain actionable insights, we know it’s not always the more effective solution. Instead, placing commercial real estate market analysis capabilities directly into the palms of owners and property teams can streamline processes and create efficiencies for any portfolio. Just imagine: You can champion a commercial real estate data analytics job, without needing to pay for outsourcing.
In order to start collecting more meaningful information about your assets, we first need to discuss how CRE owners should think about their strategy for making more data-driven decisions. With HqO, you can access all the commercial real estate insights you need with world-class technology partners who activate your building features and generate granular data. In order for CRE owners to find the metrics that will ultimately increase their portfolio’s net operating income (NOI), they need to start looking for correlations between four key metric categories: outcomes, outputs, activities, and resources.
It starts with tuning in to the problems you want to solve most for your portfolio and defining your desired outcomes. Once defined, you can then use them to inform which metrics you need to look at — such as the measurables you can leverage immediately (outputs), the strategies you enact to achieve your goals (activities), and your inputs (resources) — and what other data you need to collect. Since not all metrics and data are equal, and some are better predictors of desired outcomes than others, the data you gather should help answer questions to take action today, while still getting you closer to your larger goals.
For example, to enhance your amenity offerings you may look at digital engagement (or clicks) with content/information on your amenities, tenants’ satisfaction with those amenities, mobile access data to those amenities, equipment sensor data associated with those amenities, class or service bookings, and so on. The more activations your building features have, the more data points you can combine to paint a more holistic picture of which amenities see the most traffic, which ones need improvement, and more — showing you how your building is actually being used.
With the HqOS™ end-to-end operating system for CRE, your building’s data sources can be aggregated into our easy-to-use commercial real estate analytics software offering called the Digital Grid™. The Digital Grid takes the data collected by our tenant engagement app and combines it with any integrations from our growing Marketplace of best-in-class technology partners to organize tenant behavior, amenities, technologies, and building data all in a single location. By centralizing and structuring data within our CRE-specific data model, it helps owners and operators uncover insights, take action to differentiate their assets, and make intelligent decisions across their portfolio. It can also help benchmark your building’s performance against others to accelerate best-in-class experiences for any tenant.
Commercial Real Estate Analysis Software Free Demo
The more you learn about your building occupants and building performance, the more you will be able to create the full, well-rounded experiences that generate value throughout an office portfolio.
For more information about HqOS and its commercial real estate analysis tools, schedule a free demo today.
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