RPR's commercial analysis tools rely on demographic and consumer spending indicators that are provided by data partners to support our calculations and analytics. RPR updates all the data annually, in the first quarter of the year, to display data from the previous year. These are the main types of variables used in RPR's analysis:
Esri is RPR's source for consumer spending data. Esri uses the latest Consumer Expenditure Survey from the U.S. Bureau of Labor Statistics to calculate the spending data. These data are based on a “Diary Survey” for daily purchases and an “Interview Survey” to get a snapshot of general purchases. In the Diary Survey, consumers record what they spend on each item for two weeks to account for a consumer’s small, daily purchases. The Interview Survey is gathered by interviewing consumers five times every three months. Its purpose is to make sure to account for bigger-ticket items that might have been missed in a two-week sample. Esri integrates data from both surveys to provide a comprehensive database on all consumer expenditures.
The demographic variables in RPR include age, gender, counts of households and people, income, and more. The U.S. Census Bureau provides census data. The current year and five-year forecasts are built by Esri. RPR receives these data from Esri and PolicyMap.
In addition, the American Community Survey from the U.S. Census provides data on poverty, education, workforce, commute times, marital status, ancestry and languages spoken. RPR receives these data from Esri and PolicyMap.
Tapestry is a classification of U.S. residential neighborhoods in 67 distinct demographic segments based on socioeconomic and demographic characteristics, provided by Esri.
Esri's Retail Marketplace data — shown in the analysis of where to place a business and what business to place in a location — compares supply and demand for given retail products. The results are presented as the gap between the two in any given area. RPR receives these data from Esri.
The supply side estimates used in the calculation of retail sales start with the “Census of Retail Trade” from the U.S. Census Bureau and then are enhanced with sales statistics from the Infogroup business databases and the Census Bureau’s Nonemployer Statistics (NES) division. The NES data helps to account for small businesses and independent contractors who represent more than half of the retailers in the United States.
The market potential side of the equation is calculated by looking at the amount of money spent by consumers on products in this retail market. Esri draws these estimates from the U.S. Bureau of Labor Statistics' annual Consumer Expenditure Surveys, which provide calculations for more than 700 products and services.
Esri then compares the supply with the market potential in each area. “Not enough” results in an area represents a condition where market’s supply is less than demand and retailers outside a market area are fulfilling the demand of consumers for retail products. “Too much” in an area represents a condition where supply exceeds the area’s demand and, therefore, retailers are attracting shoppers that reside outside a trade area.