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How KIG Analytics Is The Intersection Of Real Estate And Technology


Although the idea of big data has been kicked around boardrooms and conventions for almost a decade, Susan Tjarksen, principal of Chicago-based commercial brokerage KIG, points out the real estate industry has been painfully slow to embrace technology and data science. Through its wholly owned subsidiary, KIG Analytics, Susan’s team is bucking that trend by analyzing a wealth of data from local government websites, such as Chicago’s Open Data Portal, to help clients make better, more informed real estate decisions.

“The intent was always to be predictive rather than reactive in our analyses, which was a game changer for KIG’s clients,” says Susan, “but the depth of need in the market for data interpretation and analysis showed us KIG Analytics could be viable on its own.”

The team has created a wide variety of data visualizations, including this recent video of development trends in Chicago, which bring another dimension to real estate analysis. KIG data analytics officer Marc Rutzen (left) and financial analytics officer Jay Zukanovic (right) say that as KIG’s team grew more sophisticated in the use of technology, clients started asking if they offered these services for special products.

“Our work at KIG Analytics helps us deliver deeper, more valuable insight for our brokerage clients,” said Marc. “We look at everything from demographic and cultural trends to things like the placement of bike lanes and even the rising cost of a martini in River North to better understand renters’ mindsets.”

To respond to the growing demand, KIG Analytics began partnering with property managers, leasing brokers and real estate tech startups to exchange data for insight. “The question from most of our clients is not 'where do I get more data' but rather 'what can I do with the data I already have?'” Marc notes.

When looking through KIG Analytics' website, you’ll see research on apartment absorption in downtown Chicago, but you’ll also find studies on things like bike accidents throughout the city (video above). Susan says it’s all about how the data is interpreted. While seemingly insignificant, the bike data can help developers determine whether it is worth the investment to install a buffered or traditional bike lane. This holistic approach to data analysis has really helped the KIG team stand out in the market.

Interestingly, KIG Analytics’ team members both started their careers in more traditional real estate and business roles, but quickly found themselves working with data and technology. Jay, who has an MBA from the University of Chicago Booth School of Business, previously worked as a treasury manager. Marc has a Master of Science in Real Estate Development from Columbia University and an Illinois Managing Broker License, and spent four years in real estate development, consulting and project management roles prior to joining KIG. Marc and Jay both believe these experiences were fundamental in helping them see the real estate industry’s lack of efficiency and technological innovation.


“The best way to describe our approach is that it’s essentially the difference between a developer saying 'My past experience tells me this is going to work' and 'I have empirical data proving this will work' when considering a real estate investment,” Marc (pictured) says. “We give our clients the quantitative support for what they understand intuitively, and it really helps when they have to make their own case to potential investors in a development project.”


Jay recently used his background in econometrics to build a multi-factor regression model to predict the impact of a federal funds rate increase on multifamily cap rates, and used his background in investment management to quantify how Chicago submarket returns change relative to macroeconomic conditions. These models allow KIG clients to assess their portfolio exposures comprehensively and to diversify or hedge their risk, Jay says.

But Marc believes the true benefit of data analysis is the confidence it can bring to a developer during investor presentations. You can be sure the team’s information is always updated and accurate—since much of the Open Portal Data they use is so well maintained—but what’s most important, Marc says, is how all that information is conveyed.

“Data analysis is a science,” he says, “but communication of insight is an art.” Marc expects that “predictive analytics” will continue to be a big factor in making smart, efficient real estate investment decisions as real estate technology continues to advance and more products using predictive algorithms hit the market. In fact, he says, KIG is working on its own multifamily predictive analytics tool, which will improve investors’ ability to measure the impact of demographic changes on market rents.

“Being curious has helped us be more insightful and better brokers,” says Susan. “We’re delving into each of the internal and external factors that drive real estate returns to help investors make better investment decisions. The insights we’re uncovering now will ultimately serve as the foundation for our analytical product.”

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