Retail sales of specific packaged goods (coffee, laundry detergent, shampoo) broken out by U.S. region, brand, size, packaging material, UPC, and price.

Abstract

NielsenIQ Retail Scanner Data

Methodology

Through a relationship with NielsenIQ, the Kilts Center at the University of Chicago Booth School of Business provides multiple consumer datasets to academic researchers around the world.

Columbia has an agreement with the Kilts Center. Authorized faculty, graduate students, and research staff can apply to access this dataset.

Annual funding of the dataset is shared between the Program for Economic Research and the Libraries.

Funding for data analysis using the Columbia Data Platform is provided by the Program for Economic Research.

Usage

The Retail Scanner Data (also referred to as RMS data) consists of weekly pricing, volume, and store merchandising conditions generated by participating retail store point-of-sale systems in all US markets. Depending on the year, data are included from approximately 30,000-50,000 participating grocery, drug, mass merchandiser, and other stores. Products from all NielsenIQ-tracked categories are included in the data, such as food, non-food grocery items, health and beauty aids, and select general merchandise. Currently, the years 2006-2021 are included. We expect to update the data on an annual basis. Updates are expected to be available in the first quarter of each calendar year, and will always lag by 2 years (e.g. 2022 Retail Scanner data is expected to be released in Q1 of 2024).

There are three major types of files associated with the Retail Scanner Data: Stores, Product Description, and Movement (i.e., weekly sales and pricing). The Stores file contains information about each individual store location. The Product Description file contains information about each UPC. The Movement files contain the price and quantity of goods sold at specific stores on a specific week.

The Consumer Panel Data comprise a representative panel of households that continually provide information about their purchases in a longitudinal study in which panelists stay on as long as they continue to meet NielsenIQ's criteria. NielsenIQ consumer panelists use in-home scanners to record all of their purchases (from any outlet) intended for personal, in-home use. Consumers provide information about their households and what products they buy, as well as when and where they make purchases.

PopFacts Premier Demographic Flat File.

Retail Scanner Data consist of weekly pricing, volume, and store environment information generated by point-of-sale systems from more than 90 participating retail chains across all US markets.

Store Demographics: Includes store chain code, channel type, and area location. Retailer names are masked to protect identity.

Weekly Product Data: For each UPC code, participating stores report units, price, price multiplier, baseline units, baseline price, feature indicator, and display indicator. Products: Weekly product data for 2.6-4.5* million UPCs including food, nonfood grocery items, health and beauty aids, and select general merchandise aggregated into 1,100 product categories store environment variables (i.e., feature and display indicators) from a subset of stores. The 1,100 product categories are categorized into 125 product groups and 10 departments. The structure matches that of the consumer panel data. All private-label goods have a masked UPC to protect the identity of the retailers.

Product Characteristics: All products include UPC code and description, brand, multipack, and size, as well as NielsenIQ codes for department, product group, and product module. Some products contain additional characteristics (e.g., flavor).

Geographies: Scanner Data from 35,000-50,000* participating grocery, drug, mass merchandiser, and other stores, covering more than half the total sales volume of US grocery and drug stores and more than 30 percent of all US mass merchandiser sales volume. Data cover the entire United States, divided into 52 major markets, and include the same codes as those used in the consumer panel data.

Retail Channels: Food, drug, mass merchandise, convenience, and liquor.

description: These data contain store-level information on UPC coded products, including store characteristics, sales, and detailed information on the products. There are three separate data series: the New England data, U.S. beverage data, and the WIC/Infant formula data. The New England data contain information on all food and beverage products sold in 8 major chains in New England. The U.S. beverage data include data on all non-alcoholic beverage products sold in grocery stores across the U.S. The WIC/Infant formula includes data on infant formula, ready-to-eat cereal, baby food, and peanut butter as well as demographics such as household size, income, race, and age and presence of children.; abstract: These data contain store-level information on UPC coded products, including store characteristics, sales, and detailed information on the products. There are three separate data series: the New England data, U.S. beverage data, and the WIC/Infant formula data. The New England data contain information on all food and beverage products sold in 8 major chains in New England. The U.S. beverage data include data on all non-alcoholic beverage products sold in grocery stores across the U.S. The WIC/Infant formula includes data on infant formula, ready-to-eat cereal, baby food, and peanut butter as well as demographics such as household size, income, race, and age and presence of children.

Nielsen PrimeLocation Web and Desktop Software Licensed for Internal Use only: Pop-Facts Demographics Database, Geographic Mapping Data Layers, Geo-Coding locations.

The Quarterly Food-at-Home Price Database provides food price data to support research on the economic determinants of food consumption, diet quality, and health outcomes.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Web page with links to Excel files For complete information, please visit https://data.gov.

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