Store Sales
Store Sales provides information about all store sales at item, channel, store, or date level, including a report code indicating whether an item sold was a rollback, on clearance, etc.
What Are Considered “Store Sales”?
Store Sales are any sales made via the following service channels:
- Buy in Store
- Pickup
- Delivery
- Ship from Store
With the Store Sales data, you can:
- Break out store-level sales by service channel
- Identify stores that index higher for in-store vs. OPD (online pickup & delivery) customers
- Identify top and bottom performing stores across key KPIs
- Conduct research and root cause analyses
What Is a Service Channel?
A service channel represents:
- How a customer places an order
- How that order is fulfilled
- How the customer receives the order
Walmart offers a total of seven service channels, four of which are included in Store Sales data:
- Buy in Store
- Pickup
- Delivery
- Ship from Store (historical only)
Service Channel Definitions
Buy in Store (BIS)
Traditional brick-and-mortar in-store purchases where customers select and buy items in person.
Pickup (PU)
Orders placed online, fulfilled by the store, and picked up by the customer.
- Includes scheduled and unscheduled pickup
- Not differentiated in Store Sales data
Delivery (DLV)
Orders placed online, fulfilled by the store, and delivered to the customer’s home.
- Includes scheduled, unscheduled, and in-home delivery
- Not differentiated in Store Sales data
Ship from Store (SFS)
A discontinued service channel:
- Orders placed online with two-day shipping
- Fulfilled by stores
- Delivered via carriers (e.g., FedEx)
Depending on store availability, SFS could be more efficient than shipping from a Fulfillment Center (FC), but only if the store had capacity.
Related Channels
- Ship to Home (S2H) and Ship to Store (S2S) are available in Omni Sales data
- Marketplace / 3P data is not available
Metrics Explained
There are a variety of attributes and measures that can be used to analyze Store Sales data. These metrics can be combined to generate deeper insights.
Examples include:
- Combining Walmart Item Number, Store Number, and metrics to analyze item performance across stores
- Using inventory metrics (e.g., On Hand Quantity, replenishment metrics) to evaluate stock levels and efficiency
- Analyzing Sales Amount by Service Channel to determine which channels drive the most sales
Example Use Cases & Recipes
Below are examples of how to use Store Sales data to analyze performance.
Use Case #1: Performance
Create a report to view sales and in-stock performance for all active items in a store during a selected time period.
Relevant Fields
| Table Name | Technical Name | Business Name |
|---|---|---|
| Store Sales | store_nbr | Store Number |
| Store Sales | wm_item_nbr | Walmart Item Number |
| Store Sales | svc_chnl_nm | Service Channel |
| Store Sales | mds_fam_id | Store Item ID |
| Store Sales | rpt_cd | Sales By Type |
| Store Sales | op_cmpny_cd | Operational Company Code |
| Store Sales | vendor_nbr | Vendor Number |
| Store Sales | vendor_nm | Vendor Name |
| Store Sales | wm_yr_wk_nbr | Walmart Year Week Number |
| Store Sales | sales_amt | Sales Amount |
| Store Sales | qty | Quantity |
| Store Sales | aur | Average Unit Retail Amount |
| Store Sales | scan_cnt | Scan Count |
| Store Sales | geo_region_cd | Geographic Region Code |
| Store Sales | bus_dt | Business Date |
Use Case #2: View the Inventory Pipeline with Sales and Inventory by Item
Assess whether shelf capacity meets demand, ensure compliance with pack size guidelines, and identify potential inventory issues.
Relevant Fields
| Table Name | Technical Name | Business Name |
|---|---|---|
| Store Sales | store_nbr | Store Number |
| Store Sales | wm_item_nbr | Walmart Item Number |
| Store Sales | svc_chnl_nm | Service Channel |
| Store Sales | mds_fam_id | Store Item ID |
| Store Sales | sales_amt | Sales Amount |
| Store Sales | qty | Quantity |
| Store Inventory | mds_fam_id | Store Item ID |
| Store Inventory | ty_in_trnst_qty | Store In Transit Quantity - This Year |
| Store Inventory | ty_in_whse_qty | Store In Warehouse Quantity - This Year |
| Store Inventory | ty_on_hand_qty | Store On Hand Quantity - This Year |
| Store Inventory | ty_on_order_qty | Store On Order Quantity - This Year |
| Store Inventory | ty_pipeline_qty | Store Pipeline Quantity - This Year |
| Store Inventory | ty_repl_instock_numerator | Replenishment Instock Numerator - This Year |
| Store Inventory | ty_repl_instock_denominator | Replenishment Instock Denominator - This Year |
| Store Inventory | ty_traited_cnt | Traited Store/Item Count - This Year |
| Store Inventory | ty_repl_store_item_cnt | Valid Store Item Count - This Year |
| Store Inventory | max_shelf_qty | Max Shelf Quantity |
Conclusion
The Store Sales data table provides a comprehensive view of sales across multiple service channels.
With this data, you can:
- Break out store-level sales by service channel
- Identify top and bottom performing stores
- Conduct detailed analysis and root cause investigations
The ability to analyze data at the item, channel, store, and date level, combined with attributes like rollback or clearance status, enables a deeper understanding of sales performance.
These insights can significantly improve decision-making and overall product performance across distribution channels.
