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Restaurant Data Requirements

Standard data requirements for restaurants

J
Written by Jera Malone
Updated over 3 weeks ago

Data Requirements - Locations

Notes:

All locations with addresses.

File name: Locations_YYYYMMDD.csv

Format: Excel file or .csv

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

Sample:

LOCATION_NBR

LOCATION_NM

ADDRESS1

CITY

STATE

ZIPCODE

TYPE

STATUS

OPEN_DT

CLOSE_DT

1

Buxton

2651 S. Polaris Dr.

Fort Worth

TX

76135

HQ

Open

1/1/1994

2

Capitol

1100 Congress Ave.

Austin

TX

20500

End Cap

Open

7/4/1976

3

Location

123 Fake St. Unit 1

Fort Worth

TX

76135

Inline

Closed

6/2/1986

1/9/1986

Overview:

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, drive-thru only, 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

Data Requirements - Monthly Performance

Notes:

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.

Sample:

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

Overview:

Location_Nbr: Matching unique identifier for location from Locations table.

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

Units: Revenue

Data Requirements – Consumers (if applicable)

Notes:

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.

Sample**:

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.

Overview:

Location_Nbr: Matching unique identifier for location from Locations table.

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

Units: Revenue or other

Data Audit Compliance Checklist

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.

General

  • File headers are included in all files

Locations

  • Address information is complete and provided for each location

  • Open date is provided for each location, if possible

Monthly Performance

  • All open 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

Consumers

  • 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: Restaurant, Restaurant Data Requirements, Data Requirements, Restaurant Data, Sales Data

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