2024 Retail Demand by Industry

Esri Methodology Statement, June 2024

Overview

The Retail Demand by Industry database represents an extension to Esri’s 2024 Consumer Spending (by product and service) estimates. Spending is estimated for all 12 three-digit North American Industry Classification System (NAICS) subsectors in Retail Trade (44-45) plus the Food Services & Drinking Places subsector (722). In addition, the data is available for 30 four-digit NAICS industry groups to provide additional detailed insight.[1]

While Esri’s Consumer Spending dataset provides a broad list of what households are likely to spend their budget dollars on, Retail Demand by Industry highlights where they are likely to spend it. In all, these estimates provide an alternative view of spending potential based on the industries where such market transactions may occur.


Core Methodology

The core of the methodology starts with Esri’s current year spending potential estimates by product and service. These estimates are modeled from the Interview and Diary survey data in the Bureau of Labor Statistics’ (BLS) Consumer Expenditure Survey and Esri Tapestry Segmentation and current Esri household income estimates. For more information describing Esri’s product-oriented database, refer to the Consumer Spending  methodology .

Retail Demand by Industry is based on a subset of retail and related products captured in Esri’s Retail Goods product summary variable (X15001) in the Consumer Spending database. Industry estimates are modeled using a product-to-industry crosswalk from the 2017 Economic Census Products by Industry tables based on the  North American Product Classification System  published by the U.S. Census Bureau. The crosswalk links a portion of product expenditures to industries beyond NAICS 44-45 and 722. Therefore, spending associated with out-of-scope industries is not reported in Retail Demand, which means total industry expenditures will not equate to X15001 in the Consumer Spending database.

Retail Demand by Industry includes annual total industry expenditures, annual average industry potential spending per household, and an industry-specific Spending Potential Index (SPI). The total industry expenditures value represents the potential aggregate spending by all households within an industry in an area.

The SPI compares the average potential spending locally within an industry to the average potential spending nationally in that same industry. An index of 100 reflects the average. An SPI of 120 indicates that average potential spending by local consumers is 20 percent above the national average.

It serves to remind data users of the limited scope of the BLS survey data used as the primary input to develop spending potential estimates. For example, the Personal Consumption Expenditures data published by the Bureau of Economic Analysis covers a broad range of the U.S. population, source data, and spending channels, while the BLS survey is based on a sample of the civilian noninstitutionalized population in households. Therefore, Esri’s estimates of goods and services do not represent a measure of market size. They instead should be analyzed as a measure of budget allocation. Specifically, given the income of a typical household in an area, Esri’s potential spend by product provides the expected distribution of annual budget dollars attributable across more than 700 spending categories.

The Retail Demand by Industry data is available by Esri’s  geographic summary areas  and for custom areas using the ArcGIS GeoEnrichment Service to apportion the data to polygons of any size and shape. Data is reported for the following NAICS industry subsectors and groups (with industry code in parentheses):

Motor Vehicle & Parts Dealers (441) Automobile Dealers (4411) Other Motor Vehicle Dealers (4412) Auto Parts, Accessories & Tire Stores (4413)

Health and Personal Care Stores (446, 4461)

Miscellaneous Store Retailers (453) Florists (4531) Office Supplies, Stationery, and Gift Stores (4532) Used Merchandise Stores (4533) Other Miscellaneous Store Retailers (4539)

Furniture and Home Furnishings Stores (442) Furniture Stores (4421) Home Furnishings Stores (4422)

Gasoline Stations (447, 4471)

Nonstore Retailers (454) Electronic Shopping and Mail-Order Houses (4541) Vending Machine Operators (4542) Direct Selling Establishments (4543)

Electronics and Appliance Stores (443, 4431)

Clothing and Clothing Accessories Stores (448) Clothing Stores (4481) Shoe Stores (4482) Jewelry, Luggage, and Leather Goods Stores (4483)

Food Services & Drinking Places (722) Special Food Services (7223) Drinking Places (Alcoholic Beverages) (7224) Restaurants and Other Eating Places (7225)

Building Material & Garden Equipment & Supplies Dealers (444) Building Material and Supplies Dealers (4441) Lawn and Garden Equipment and Supplies Stores (4442)

Sporting Goods, Hobby, Musical Instrument, and Book Stores (451) Sporting Goods, Hobby, and Musical Instrument Stores (4511) Book Stores and News Dealers (4512)

Food and Beverage Stores (445) Grocery Stores (4451) Specialty Food Stores (4452) Beer, Wine, and Liquor Stores (4453)

General Merchandise Stores (452) Department Stores (4522) General Merchandise Stores, including Warehouse Clubs, Supercenters (4523)

NAICS industry subsectors and groups


Endnotes

[1] Industry definitions used in this product are based on the 2017 NAICS coding structure.  Learn more about the North American Industry Classification System 


Data resources

Learn more about  Esri's Retail Demand by Industry data , or contact sales at 1-800-447-9778.


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About Esri's Data Development team

Led by chief demographer Kyle Cassal, and economist Douglas Skuta, Esri's Data Development team uses sophisticated quantitative methods to produce small area demographic and socioeconomic data to support informed decision-making. The team builds on a rich history of market intelligence to produce trusted independent estimates and forecasts for the United States based on innovative methodologies that use public and private data sources with the power of ArcGIS. Esri's Data Development team provides more than 7,000 proprietary data items to better understand the characteristics of people and places across multiple statistical and administrative boundaries and custom trade areas.

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