Retail Data Requirements

All stores or locations with addresses.

File name: Locations_YYYYMMDD.csv

Format: Excel file or .csv

Optional Store Characteristics that may be included: Size in square feet, Drive-thru Flag (Y/N, etc.

Location_Nbr: Unique identifier for each location that will match up to performance or customer files.

Location_Nm: Unique name for each location. This will be the name that is displayed in the Buxton platform (SCOUT) and any analysis reports.

Type: Location type that may be relevant for analysis. This might include types for corporate offices, shopping center type, outlet vs full-price locations, etc.

Status: Open, Closed, Pipeline

Latitude: Optional field, locations’ latitude

Longitude: Optional field, locations’ longitude

Sqft: Optional field, size in square feet

Drive_Thru: Optional field, Y/N values

Summed monthly performance per location. This is typically monthly revenue

File name: Performance_YYYYMMDD.csv

Format: Excel file or .csv

All locations listed in this file should be in the locations file.

Need at least 1 full year of performance data.

LOCATION_NBR MONTH DEPARTMENT TOTAL UNITS

1 1/1/2025 Lunch 8558.65 Revenue

1 2/1/2025 Dinner 6135.70 Revenue

2 1/1/2025 Lunch 3017 Revenue

2 2/1/2025 Dinner 2556 Revenue

Location_Nbr: Matching unique identifier for location from Locations table.

Department: Any performance breakouts you have, e.g. dayparts, retail departments, fulfillment method, etc.

Units: Revenue or Member Count

Consumers are customers from prior 12-month period.

File name: Consumers_YYYYMMDD.csv

Format: Excel file or .csv

All locations listed in this file should be in the locations file.

LOCATION_NBR DEPARTMENT FIRSTNAME LASTNAME ADDRESS CITY STATE ZIPCODE

1 Lunch Emma Reynolds 2914 Oakwood Dr San Diego CA 92104

1 Dinner Liam Foster 1258 Maple St Austin TX 78701

2 Lunch Ava Mitchell 473 Lakeview Ave Orlando FL 32801

2 Dinner Noah Carter 847 Willow Lane Denver CO 80203

** Sample data; is illustrative only and does not represent actual customer data.

Location_Nbr: Matching unique identifier for location from Locations table.

Department: Any performance breakouts you have, e.g. dayparts, retail departments, etc. These should match the departments in the monthly performance file. If unable to provide consumers by department, this column/field values can be denoted as “Overall”.

The following checklist denotes common points of failure for the data acquisition process. By confirming that your data complies with each of the items below, you can help ensure that your data is accepted and moves forward in the data transfer process. If you have any questions or concerns regarding any of the items below, please contact your Buxton team.

· File headers are included in all files

· Address information is complete and provided for each location

· Open date is provided for each facility, if possible

· All open stores or locations are present in the monthly performance file

· Each location present in the monthly performance file is also present in the location file

· At least 12 months of monthly performance data is provided

· Locations are not missing any monthly performance data

· Data is not provided for future months

· Any required breakouts by Type are included

· Duplicate customer records are not present

· Address information is complete for at least 90% of consumer records

· All location numbers in this file join to the locations file

Tags: Retail, Retail Data Requirements, Data Requirements, Retail Data, Sales Data