When considering whether to upgrade to hardwood floors and granite countertops during a renovation, or add hot new amenities like rooftop pools and lounges, developers usually base their decision on a combination of industry trends and gut instinct. But that’s not always the case. Amenities and finishes differ from market to market, and some markets are willing to pay more than others for those upgrades.

A company called Enodo, formerly known as Enodo Score, wants to standardize the renovation process by tapping into the apartment industry’s wealth of data to help owners and investors decide whether the extra expense for these upgrades is worth the potential return. Enodo, a predictive analytics platform, uses regression analysis to track the relation between rent and specific apartment features, such as gyms, bathtubs, and walk-in closets.

“There’s been no quantification of adding or removing amenities or locating a development in a specific neighborhood,” says Enodo co-founder Marc Rutzen. “This [product] conducts a full market analysis on a granular level.”

The platform evaluates three primary values: how a new property would perform, how a current property could perform with different features, and how a current property would perform if it were replicated in other markets.

The platform also breaks down incremental rent increases associated with various features. For example, if a developer wanted to add a rooftop pool to a project because it would make the property stand out, he or she could identify whether the market would pay the expected return.

“The platform’s set up to be really flexible, meaning you can make your own investment planning decisions,” says Rutzen. “What you want to charge for rent, what you want your occupancy to be, the amenities you want to upgrade, even the level of the building, and see how that affects every other variable in the equation.”

Data From a Wealth of Sources
Enodo’s database is composed of public and private data, including census data and data from roughly 800,000 apartment properties across the country. Enodo’s learning algorithm will also rely on user data in the future to monitor shifts across markets.

The biggest challenge Rutzen says his team is confronting is making sure the data are accurate. “If you search for market values in various different platforms, you’re probably going to get various different results,” he says. “We’re trying to solve this [problem] by analyzing the data in bulk for one aggregate data set.”

Enodo launched its platform in early 2016 and conducted its first closed beta test with multifamily partners over the summer. Based on testers’ feedback, as well as input from friends and mentors, Enodo has quadrupled the size of its database and improved its user interface to suit the needs of a professional audience.

“The [user interface] needs to be very professional looking in order for a financial analyst to want to interface with it,” says Susan Tjarksen, co-founder and CEO of Enodo. “In the beginning, our UI was a little too consumer facing. We’ve spent a lot of time on the front end making sure it looks like a professional tool, because it is a professional tool.”

The project entered open beta on June 1, 2017, and the developers are seeking feedback from early adopters. Features in development include the Enodo Score, an objective composite score of a building’s expected performance in a given market, and Enodo Financial, which will allow developers to determine ROI from current income and expense statements.