We help commercial real estate investors with analytical services that they may not have in-house. This includes exploring new markets for investments and building compelling marketing material for potential investors.
Where is wealth growing, by neighborhood, within a market?
Demand and Supply Analysis
Client Question: Where does demand exist, and how does this compare to existing (and planned) supply?
Approach: WP calculates demand using American Community Survey (ACS) data to estimate our client’s office or multi-family target tenants. Data generally includes income, age, occupation, and rental statistics. WP calculates supply using existing office or multi-family inventory along with planned permit data. Imbalance is then calculated by subtracting supply from demand in relevant geographies, either at the census tract or submarket level. The purpose of the imbalance “answer map” is to identify localized regions of a market where demand is predicted to outpace supply.
Planned Development Data
Client Question: How many competitive units are planned to be built by other investors for the markets that we are considering?
Approach: WP finds that real estate inventory databases, like Costar, have accurate data for existing inventory, but generally capture less than 50% of planned, permitted developments. We find the exhaustive data on planned developments by contacting and working with every city’s building department to gather the most recent permit data. We then clean and merge this data to deliver “the universe” of competitive developments to clients.
Client Question: Which opportunity zones (OZ’s) are most attractive for investment?
Approach: WP studies all 8,700 opportunity zones in the US in terms of the rate of income growth historically to find which OZ’s have the most “wind at their backs” in terms of projected real estate prices. This analysis was covered by Bloomberg and the Forbes, among other publications.
Client Question: Which neighborhoods are within a 10-minute walk of a subway station?
Approach: WP builds a walking network in the market to calculate travel times to specific subway stations. We use this approach for other travel methods, including drive, walk, train, and bus. We study proximity to a wide array of city data, such as public green space, water, social clubs, and high quality grocery stores.
Visit this link for an interactive version of the map.
Point of Interest Data
Client Question: Which Points of Interest (POI) are attractive to our target tenants?
Approach: Webster Pacific utilizes its POI database and an assortment of available API’s to gather information on proximity to places like high-end restaurants, cozy coffee shops, luxury supermarkets, rowing clubs, and hipster bars. Webster Pacific also creates custom metrics for every census tract about proximity to particular POI’s.
Wealth Growth Predictions
Client Question: Where is wealth growing, by neighborhood, within a market?
Approach: WP develops wealth growth maps, which estimate where wealth of all income levels is increasing in neighborhoods within a city. These maps are based on both proprietary analytics and publicly available data. The analysis uses historical census data about income, households, and population, and is backtested with recent real estate prices. This information is then organized on a drive-time basis and displayed in the form of a heat map. This work received coverage by Bloomberg among other publications.
Visit this link for more wealth growth maps of US cities.
San Francisco & Chicago
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