Sales dataset

Sales dataset containing aggregated daily sales per product-location, used by the Rebuy & Replenishment capability of the Merchandising solution to understand demand patterns over time.

The sales dataset contains aggregated daily sales for each product at each location. This dataset represents actual customer demand and is used by the Rebuy & Replenishment capability of the Merchandising solution to understand demand patterns over time.

For Rebuy & Replenishment, sales provide the demand history signal in place of order-level customer orders.

Purpose

The Rebuy & Replenishment capability uses sales data to analyze demand volatility at the product and location level. This analysis is used to calculate inventory parameters and support replenishment and stock optimization recommendations.

During presales, this dataset is also used to assess historical inventory performance and understand the factors influencing demand and service levels.

Required fields

About the Constraint column: every field listed must be provided in your data. Non-null means its value cannot be null; Nullable means the value may be sent as null (or left blank in your source). Primary key, Unique, and Foreign key describe the field's role in the data model; a Primary key is always non-null.

Field	Description	Type	Constraint
product_id	Unique identifier for the product SKU.	string	Primary key
location_id	Unique identifier for the store or distribution centre.	string	Primary key
day_date	Date corresponding to the reported sales.	datetime	Primary key
sales_units	Number of units sold for the given product, location, and date.	float	Non-null
sales_value	Revenue value of the units sold for the given product, location, and date. Should correspond to the value of sales_units.	float	Non-null

Usage notes

• A daily historical record of sales is recommended to support accurate demand analysis.
• Historical data should ideally cover up to two years, where available.
• The dataset should reflect actual sales, not forecasts.
• Consistent identifiers (product_id, location_id) must align with the corresponding Products and Locations datasets.