industry-department-solutions
latest
false
Supply Chain & Retail Solutions user guide
- Overview
- Platform setup and administration
- Platform setup and administration
- Platform architecture
- Data Bridge onboarding overview
- Connecting a Peak-managed data lake
- Connecting a customer-managed data lake
- Creating an AWS IAM role for Data Bridge
- Connecting a Snowflake data warehouse
- Connecting a Redshift data warehouse (public connectivity)
- Connecting a Redshift data warehouse (private connectivity)
- Reauthorizing a Snowflake OAuth connection
- Using Snowflake with Peak
- SQL Explorer overview
- Roles and permissions
- User management
- Inventory management solution
- Commercial pricing solution
- Merchandising solution
Product pricing daily dataset for the Markdown & Promotions module, containing daily selling, list, and cost prices per product and location.
The Product pricing daily dataset contains daily selling, list, and cost prices for each product at each location. It captures the pricing history that influences demand and margin in markdown and promotion decisions.
Purpose
The Markdown & Promotions module uses the Product pricing daily dataset to:
- Provide historical selling, list, and cost prices by product and location
- Support margin analysis for markdown and promotion decisions
- Capture how price has changed over time
Required fields
| Field | Description | Type | Use | Notes |
|---|---|---|---|---|
location_id | Unique identifier for the store or location. | string | Application / Presales | Required. Primary key. Foreign key to location. |
pricing_at | Timestamp the price applies from. | timestamp | Application / Presales | Required. Primary key. |
product_id | Unique identifier for the product SKU. | string | Application / Presales | Required. Primary key. Foreign key to product. |
created_at | Timestamp when the record was created. | timestamp | Application | Optional. |
quote_stage | Stage of the pricing or quoting lifecycle the record represents. | string | Application / Presales | Optional. |
selling_price | Actual selling price per unit. | float | Application / Presales | Required. |
unit_cost_price | Cost per unit. | float | Application / Presales | Required. |
unit_list_price | Standard list price per unit. | float | Application / Presales | Required. |
updated_at | Timestamp when the record was last updated. | timestamp | Application | Optional. |
Usage notes
- Product and location identifiers must align with the Products and Locations datasets.
- Prices should be expressed in the currency of the associated location.
- A daily record supports accurate historical margin analysis.
Why this dataset matters
Pricing history underpins margin and discount-depth analysis. Without it, the solution cannot assess the financial impact of markdowns and promotions.