Proptech Lets CRE Companies Fly Virtually Through Data-Decorated Properties

The coronavirus pandemic's onset may have accelerated the rise of real property technology or proptech over the past year. Yet, it is just the latest chapter in commercial real estate's high-tech transformation over the past decade leading to greater property insights when used cautiously.

Beyond virtual tours, DocuSign, Internet of Things devices and robotic furniture, the increasing use of artificial intelligence and geographic information systems technologies has untethered the industry from physically being in spaces and also provided new vantage points from which to analyze properties, though not without challenges.

In 2013, End Point began deploying the Liquid Galaxy system that originated out of Google Earth for use by commercial real estate companies. Liquid Galaxy is an immersive, panoramic data visualization experience that End Point installs and equips with its proprietary content management system that allows commercial real estate companies to add infographics, data and video overlays to the system to help understand properties and locations.

“It’s a great tool,” Prologis L.A. Market Officer Rob Antrobius said. “We use it almost daily because it's literally like being in a helicopter … it has really allowed us to zoom in and look at prospective properties, look at our own properties.”

Prologis was first introduced to Liquid Galaxy by CBRE, which added it to its downtown Los Angeles Workplace360 office after it opened in 2013.

“Liquid Galaxy is a geospatial visualization tool used to support site selection considerations for clients,” CBRE Global Lead of Corporate Real Estate Peter Van Emburgh said. “We use it to ‘fly’ clients through multiple locations in one sitting while telling a story on a digital display, instead of using traditional maps or visiting locations individually. It’s especially useful for clients considering options in multiple cities, states or countries.”

Liquid Galaxy saves Antrobius travel time of having to drive across the L.A. region exploring potential acquisitions. It has also helped strategic planning with customers and troubleshooting issues that arise on existing properties. He said it has been a great efficiency tool but isn’t surprised that it is not more widely found in the CRE industry, given that it is expensive and requires ample space.

Beyond purchase and installation of the system, End Point provides 24/7 technical support, including periodic updates. The standard set-up with seven screens required Prologis to dedicate a specially designed conference room for its use.

“The screens and everything else, we install and provide as well, but it's really the software and the servers that make everything happen,” End Point Liquid Galaxy Support Manager Jandro Ramon said.

Although Liquid Galaxy has cut down Antrobius’ trips to the gas station, he added that the technology isn’t appropriate for all uses as some aspects of his job necessitate in-person visits to properties.

Data and visualizations can work in tandem to tell stories about the built environment. Australian-based Place Intelligence CEO Norion Ubechel presented at the 2021 AIASF International Waterfronts Symposium on Feb. 18 about his company's platform that can be used by urban planners.

In the context of master planning and placemaking strategies aimed at San Francisco’s waterfront, Ubechel said he worked with design firm Hassell to examine about 500 million cellphone signals per month along a stretch of S.F.’s Embarcadero to illustrate patterns of activity in places over time. The “de-identified” signals yielded 20 terabytes worth of data to generate insights and support the design strategy. The signals data were then used to create “heat maps” showing trends regarding where people were going along the Embarcadero, what routes they took to get there and where they went afterward.

“One of the insights that we usually start with is trying to define who our audiences are,” Ubechel said during the presentation. “We can use computational processes to look at signal data and understand the postcodes of origins of our audiences, and we can reference in other data points into that information to understand what percentage of people come from California, for example at the Embarcadero.”

One of the findings using the Place Intelligence platform was that 62% of all Embarcadero visitors live in California, Ubechel said. He explained that Place Intelligence works with companies like Microsoft and Cisco for signals data, Uber and Tesla for data about road utilization and Mastercard for financial information about places. Machine learning algorithms then analyze the data to create predictions about design benefits for specific sites.

Aggregated cellphone data is a gold mine for big data and AI platforms. However, potential pitfalls depend on how the information is used.

Developer John McNellis of McNellis Partners had authored an enthusiastic opinion piece in Wolf Street about Placer.ai, a tool that generates insights about retail properties by applying a virtual perimeter called a geo-fence and using consumer foot traffic data harvested from cellphone signals. Placer.ai recently studied U.S. malls finding that the visits to the nation’s top-performing malls plummeted in spring 2020 but then increased in summer and fall, as reported by a CNBC broadcast.

McNellis had heard from others in the industry that Placer.ai is a “great tool” but hadn’t yet tried it due to the expensive pricing. In general, AI solutions can cost companies tens of thousands of dollars per year, according to WebFX.

However, McNellis was subsequently contacted by a broker who said he conducted a Placer.ai study on one of the McNellis firm’s supermarket properties showing poor performance, something McNellis said he knew was false as the store had excellent sales.

“It's not entirely accurate,” McNellis said. “It doesn't count telephones — it counts apps, and it gets complicated [because] people turn their apps off, their location services off, and the geofence may or may not be set up accurately.”

While potentially not suitable for all applications, McNellis said that it could be a useful tool for those in the industry who already have their own data and want to compare performance with a nearby competitor.

“Whatever mistake Placer is making on your store count, you can extrapolate that to the competition’s,” McNellis said.

Although geared for retail, a platform like Placer.ai could potentially be useful to the industrial sector that is being transformed by e-commerce in a way that makes data about the transport of goods from last-mile facilities to customers increasingly relevant to companies like Prologis.

As part of Prologis' digital transformation initiative, the company is looking to potentially develop its own AI platforms and invest in third-party ones, Antrobius said.

AI is also being applied to the multifamily sector. Zumper just announced its PowerLeads AI launch, a product used to analyze renters’ behavior to predict a given renter's likelihood of signing a lease. One of the tool’s features is Power Prospects, which flags renters who statistics show are up to twice as likely to sign a lease immediately. Additionally, PowerLeads AI offers leasing agents with over 50 unique renter characteristics.

“Our studies showed that the vast majority of leasing teams want a way to understand which prospects are more likely to lease, so we knew that it was vital to solve this challenge with an industry-first solution,” Zumper Chief Growth Officer Tanguy Le Louarn said. “In fact, 78% believe having more data on prospects would help them convert more leads. By using cutting-edge AI and machine learning to provide predictive insights and data, we’ll not only provide higher quality leads, we’ll also enable a faster leasing process.”

One of the common concerns with AI systems generally is that though they may quickly yield accurate predictions, there are more subtle aspects of the human experience that they don’t take into account. For example, when comparing similar rental applicants, a leasing agent might rely on nuances in interpersonal interactions to inform decision-making. Furthermore, while a credit report's inaccuracies can be contested, a potential renter is blind to what data sources an AI is drawing from to make behavior predictions.

It is likely that as AI advances, algorithms will be continuously modified to achieve greater accuracy. It is also possible that big data and predictive models could be increasingly paired with tools like Liquid Galaxy.

According to Ramon, one of the fundamental aspects of Liquid Galaxy lends itself to the integration with other tools as it uses a modular software framework, where modules, such as an interactive web application, can be added and removed.

“[Liquid Galaxy] is more of a visualization system,” Ramon said. “You have a bunch of data that you then put into a visual place and put it on the system. The system isn't necessarily processing that, although it could if necessary. There are other systems it can integrate with. For example, one that comes to mind is if somebody wants to get traffic data over time, if they already have that data, we can then just visualize it and place it on the system to have it in a digestible way. But it's not like the system itself is doing the processing and collecting of the data.”

So far, End Point hasn’t done much integration work with AI platforms but it is currently focused on expanding videoconferencing and screen-sharing capabilities to take the technology from the conference room wall to the living room, according to End Point Product Marketing Manager Ben Witten.

"We're kind of data-agnostic. We can put anything on the system that people want to see, so it's really nice to be able to support our commercial real estate clients and evolve based on the needs of the industry,” Witten said.