RiseSpot Uses Location Intelligence to Guide Multifamily Real Estate Investors

The commercial real estate investment landscape has evolved rapidly in recent years. Elevated interest rates have caused investors to concentrate primarily on operational efficiencies, as acquisition teams see fewer opportunities in their pipelines. But as trends shift toward lower interest rates, deal flow is expected to rise. The industry will need tools that can help investors quickly prioritize opportunities while supporting faster, more confident investment decisions. 

Additionally, established commercial real estate data providers face growing competition from startups that specialize in scraping and aggregating real-time market information. As this data becomes more accessible, predictive modeling with advanced spatial analytics tools will be critical for informing real estate investment decisions. 

An investor’s target is to achieve the highest risk-adjusted returns, even as market conditions grow more volatile. Location is one of the key decisive factors in real estate investment. By choosing the right locations, investors can maximize returns, including net operating income and property appreciation. A property may be highly attractive on its own, but without proximity to essential amenities—such as transportation networks, employment centers and quality schoolsit’s far less likely to attract and retain tenants.

With many desirable locations already saturated, choosing the right places to invest in is crucial. Many investors tend to choose markets based on specific metrics like employment growth. However, no single set of features explains growth across all areas. Location-based insight—down to the census tract level—that reveals where demand is likely to grow before markets peak could solve this challenge.

That’s why RiseSpot, a PropTech company founded in 2022, has built advanced predictive models which score each census tract by expected capital gains (CG prediction tier) within the next three or five years. The product is based on Esri’s ArcGIS Location Platform as its spatial foundation. Its mission is to develop advanced investment-support tools for real estate acquisition teams. The company brings together finance, data science, and geographic information system (GIS) expertise.

“For RiseSpot, spatial reasoning is not a feature added on top of a mathematical model,” said Ruthy Dahan-Portnoy, founder and CEO of RiseSpot. “We needed data interoperability, and GIS is the foundation the predictive models are built on, which made Esri’s ArcGIS technology the natural choice from day one.”

Through RiseSpot’s tools, powered by ArcGIS, investors can identify emerging locations early, using predictive, spatially driven data.

The CG Prediction Tier scores and color-codes every US census tract by expected property capital gains ( price movement) within the next three or five years (depending on the user’s preference). Then, from a map, investors can enter a property address, filter investment criteria, and make decisions that best match their risk appetite and investment preferences. The color-coding is divided into seven tiers, differentiating between saturated tracts and most emerging tracts. Users can also explore current market metrics: sales, rental, and vacancy rates by specific location. Because a tract is a small geographic unit, the data and, consequently, the investment decisions based on it, are much more precise.

“Delivering tier scores across every US census tract requires ingesting, harmonizing, standardizing, and processing data from more than a dozen sources at the smallest unit of geographic analysis for which reliable transaction data exists,” said Dahan-Portnoy. Drilling down to the tract level was one of RiseSpot’s mathematical challenges. However, it wanted a product to direct users to the most precise areas. “Esri’s software provides the interface to make this fast and fluid regardless of how many layers are active,” added Dahan-Portnoy.

This detailed view, organized in tabs, is part of a seamless, faster workflow from market selection to deal closing. Investors are presented with a complete, transparent visualization of all their key performance indicators, which helps them immediately access the full deal flow within a certain area.

With many American cities prioritizing transportation projects to deal with future demand, this location intelligence driven planning for real estate has unique applications. RiseSpot’s platform has already found a large role with Metropolitan Planning Organizations (MPS) in the US that are anticipating future mobility needs and where demand is expected to grow. A proprietary feature integrates all transporation projecgs directly into RiseSpot predictive models. 

In many communities, access to transportation is a large indicator of future growth and with prediction models, investors can better anticipate market shifts before they occur in traditional datasets. MPOs main goal is the close the gap between current transporation infrastructure and future needs. This takes into account major planning initiatives and projected changes in population, employment, and land use. 

Visual demonstration of the transportation projects’ importance to the CG Prediction Tier can be seen by the map, where “bubbles” of project areas are color-coded differently (mostly higher) than the tracts in which these projects are located. In a rapidly changing information technology environment, RiseSpot’s advanced GIS tools are enabling investors and other planners to make decisions with more speed, efficiency, and accuracy, converting their gut feelings into science based investment decisions.