There are five main Item Attributes. Also known as Product Attributes. As such, retailers and their solution providers should understand them. Because merchandising systems require them. They are key inputs for merchandising and space planning systems.
There are five main Item Attributes:
- Identifying Attributes
- Data that helps you understand the product itself. Thus, they identify relationships between products.
- examples: Name, Manufacturer, Brand, UPC or Category
- Static Attributes
- Product data that does not change. They are true no matter where it is merchandised.
- examples: Gluten Free, Flavor or units per case
- Performance Attributes
- Data about the sales and profit for a product. May be at the chain, region or store level.
- examples: 12 week average unit sales per store, 52 week $ sales ranking in the chain, current Gross Margin %
- Temporal Attributes
- Data passed to the merchandising system that is true for a specific time period.
- examples: assortment instruction (add or delete), promotion start date, allocation quantity, price
- Calculated Attributes
- Product data that changes depending on the planogram or stores where it is merchandised.
- examples: Number of Facings, Average Price or Number of Days of Supply (DOS) on the shelf.
More Item Attribute Details
Primarily, the data for Product Identification and Static Attributes come from the SKU Master. Otherwise known as the repository for product set up data. Changes may occur. For example, package size or cases change. Or retailers reconfigure their product hierarchy. Surely changes are infrequent. But account for changes when creating data integrations.
Product Performance data comes from the POS system. Try to understand if it includes scan backs for returned items. This is a continuous feed. It may even be in real time. In other words, tabulating online and in store purchases as they occur. So let’s say your system uses averages or time period sums. (Quarter to date sales, for example.) Either calculate values on the fly to enhance recency. Or update and store them frequently to improve reporting performance.
Temporal attributes originate from other systems. Examples include pricing, promotions, assortment planning and inventory management systems. In general, they provide continuous information about the status of an item in their system. During the initial implementation, these integrations often get deprioritized. Then they become the root cause of misalignments. (For example, macro space analytics for space allocation is commonly skewed. That is because it is unaware of items that had display locations during key sales.)
Finally, calculated attributes originate in the space planning system. They are important metrics for other systems. Examples include:
- Item store authorization to confirm assortment placement by store
- Shelf capacity by store to feed inventory allocation systems
- Product position and shelf type to feed price tag printing systems
Listen, Item Attributes are not sexy. But getting them right makes a huge impact on a retailer’s line of sight for all kinds of data analytics and operational efficiencies. Whenever you would like to evaluate your implementation – or guidance on how to make your space planning system more useful – contact us. We’d love to geek out with you about this.