Retail Store Visits

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This dataset has recently been updated

For more information, visit the changelog.

Overview

pass_by's innovative AI-powered Retail Store Visits dataset spans more than 3M POIs, 7,000 brands, 43M devices, and 6B daily data points, delivering critical insights to fuel important analysis of consumer behavior, market trends, brand loyalty, and similar research topics.

Data InformationValue
Refresh CadenceAdhoc
Historical Coverage5 Years Rolling
Geographic CoverageUnited States

Schema

NameDescription
STORE_IDThe unique identifier of the particular store.
NAMEThe name of the store.
BRANDThe name of the brand that the store belongs to.
STREET_ADDRESSThe street address that the store is located on. May contain abbreviations.
CITYThe city that the store is located in.
STATEThe state that the store is located in, formatted as an abbreviation.
ZIP_CODEThe zip code that the store is located in.
WEEK_STARTINGThe start date of the week in YYYY-MM-DD format. This will always be a Sunday.
WEEK_ENDINGThe end date of the week in YYYY-MM-DD format. This will always be a Saturday.
TOTAL_VISITSThe total number of visits seen that week.
DAILY_VISITSThe number of visits seen every day that week.
SUNDAY_HOURLYThe hourly visit counts for the Sunday. This list will contain 24 values for each hour in the day.
MONDAY_HOURLYThe hourly visit counts for the Monday. This list will contain 24 values for each hour in the day.
TUESDAY_HOURLYThe hourly visit counts for the Tuesday. This list will contain 24 values for each hour in the day.
WEDNESDAY_HOURLYThe hourly visit counts for the Wednesday. This list will contain 24 values for each hour in the day.
THURSDAY_HOURLYThe hourly visit counts for the Thursday. This list will contain 24 values for each hour in the day.
FRIDAY_HOURLYThe hourly visit counts for the Friday. This list will contain 24 values for each hour in the day.
SATURDAY_HOURLYThe hourly visit counts for the Saturday. This list will contain 24 values for each hour in the day.

Key Concepts

Quarterly Reinstatements

Pass_by produces a full refresh of their datasets each quarter. This means the historical data may change as they update their algorithm and fix any issues. Therefore, we recommend that you take note of the release “version” you accessed, as noted by the Date included in the product name, and only use one version for your research. Each version will have 5 years of rolling history.

Placekey Matching

Pass_by provides a key matching dataset that allows you to join a Placekey to store_id. This will allow you to easily join this dataset to other Dewey partners that use Placekey as a unique identifier (e.g. Advan Research, SafeGraph). pass_by Placekeys