CHICAGO (May 23, 2016) – Enodo Score, a Chicago-based startup, launches its predictive analytics platform for the commercial real estate industry. During Enodo Score’s debut at NMHC’s Emerging Leaders Speaker Series on May 18th, CoFounder Marc Rutzen explained how the platform utilizes a massive database of historic property information, census data and a unique combination of regression analysis and machine learning algorithms to analyze multifamily properties in real time and facilitate data-driven investment decisions. Enodo Score recently received an offer from the Elmspring Real Estate Accelerator, and will be a Disruptor at DisruptCRE in Chicago on May 26, 2016.
The Enodo Score team surveyed a broad segment of multifamily investors, developers and brokers to refine the platform’s functionality. Some of the platform’s features influenced by these conversations include:
· The ability to objectively quantify which property and market characteristics drive multifamily real estate value in markets across the country
· The calculation of the incremental rent a user could charge if they installed improved unit finishes or common area amenities
· Determination of the effects of external factors like transit stations opening nearby on both occupancy and market rents
· Calculation of a risk-adjusted composite score for each property to facilitate comparison of investment opportunities across markets
· A drag and drop feature that lets users place properties in other markets and see how their investment performance might change based on the demographics of those markets
“There is no product available that can quantify the impact of building characteristics, amenities, demographics and other variables and distill that insight into a simple composite score for an investment opportunity,” said CoFounder, CEO Susan Tjarksen. “Without a way to objectively quantify these variables, real estate professionals are forced to make decisions based on intuition and conjecture.”
“A product that can objectively quantify the risk-adjusted returns of any multifamily property in any market, and that allows you to compare those risk-return metrics to any other property in the market, should be an essential tool for any investor or developer looking to mitigate risk and maximize returns,” said CoFounder Lee Kiser.
Over the past few months, the company has amassed a database of over 800,000 multifamily properties throughout the United States, collected ownership and tax data on more than 100 million parcels across the country, and integrated with a number of API data feeds to pull real-time rent and market data into the platform. Enodo Score’s machine learning algorithm processes these public and private sources to score the risk-adjusted investment potential of multifamily properties across the country – facilitating apples-to-apples comparisons of investment opportunities in different markets.
Users have the ability to test investment ideas and instantly see operational impact through the platform. By generating a composite score for each property, the impact of adjustments to amenities, finishes and other variables are easily understood through an increase or decrease in the property’s Enodo Score.
According to Bob Gillespie, Managing Director of the Elmspring Real Estate Tech Accelerator in 1871, Enodo Score is just the type of product the real estate industry needs to make data driven investment decisions.
“We see hundreds of applications from companies and we always have to ask: What distinguishes you from any other product out there?” said Bob Gillespie. “What we love about Enodo Score, and the reason we invited them to work with Elmspring, is that they are actually providing insight from real estate data – helping real estate professionals make sense of the increasingly overwhelming volume of data out there. And this platform is scalable.”
Enodo Score is now looking for Beta Testers in the multifamily industry. Multifamily investors, developers, brokers, lenders and equity partners, acquisition analysts and managers are encouraged to apply on the Enodo Score website and in doing so be the first to utilize this predictive analytics product.
“Beta Testers will have the ability to shape how the product is made and tailor it to their specific needs,” said CoFounder, CTO Marc Rutzen. “Because of this competitive advantage, Enodo Score will be selective in choosing its Beta Testers.”
Enodo Score’s Beta Test release is scheduled for late August, and the full product will be available for the market in Q1 of 2017.
About Enodo Score: Enodo Score is a predictive analytics platform for the commercial real estate industry that generates an objective composite score to represent the institutional investment grade of multifamily properties. Using real-time data from public and private sources, Enodo Score’s machine learning algorithm assigns a composite score to each property to facilitate data-driven investment decisions. In Latin, the word “enodo” means “untangle, unknot, explain, elucidate or unfold.” Enodo Score believes this is the best explanation of what the product will do for the real estate industry. With Enodo Score, real estate professionals will make investment decisions based on real, immutable data. Learn more about the company at EnodoScore.com.