Walmart sales dashboard overview

Using POS data from your Walmart Retail Link account, the dashboard succinctly displays insights on your sales and product performance across locations (which you can also filter by). 

In this tutorial, you will learn about each visualization available through the Walmart dashboard. Quickly jump to a specific visualization by clicking the links below.

Sales
Sales, Products, Locations Scanning
Sales by State
Sales by City and Sales by Product
Units Per Store Per Week Over Time
Number of Stores with Markdowns
Markdown Dollars Over Time
Units Per Store Per Week
Sales by Zip Code
Product Share Over Time
Sales by Store Type

Walmart Sales Dashboard Visualizations

Sales

View sales trends over time. Along with adding filters to hone in on specific products or time periods, you can also hover over data points for more info. This visualization is especially useful for recognizing seasonal and cyclical patterns, analyzing promotions and item success, and demonstrating growth to other retailers or investors.

Sales, Products, Locations Scanning

These tiles add more context to the Sales graph and together provide high-level information about your sales performance and patterns. When you enable a cross filter, these tiles offer more granular insights, helping you better understand sales and distribution within a particular area.

Right click the number above Locations Scanning to see the sales for actual locations that are scanning your product.

Right click the number above products to show actual sales from those locations.

Sales by State

This regional heat map allows you to quickly observe states where product popularity is high versus states that are underperforming. States can drilled into by zip code by right-clicking, enabling your team to make more strategic decisions on where to allocate attention and resources.

Sales by City and Sales by Product

These sortable tables can help you spot top-performing cities and products, which can aid in geo targeting, product-placement decisions, and in analyzing recent demo performance.

Units Per Store Per Week Over Time

This clickable visualization shows product velocity by week and can assist in identifying if an item is growing or declining, as well as if a product promotion has elevated the average sales. Note: If the number of units per store per week drops below 1, the related line in the graph will drop to 0 during that time. 

Number of Stores with Markdowns

This graph displays the amount of stores with markdowns by week with a comparison to sales. At a glance, this can help you see the extent of markdown activity. The location count line indicates how many stores reported markdowns. Total POS quantity refers to the number of units sold at the marked down price. 

Markdown Dollars Over Time

This graph allows you to identify which products are being hit hardest by markdowns. Markdowns can also give you an idea of when shelf resets are occurring. Negative markdowns suggest that Walmart has marked up the price your product. Clicking within this visualizations will apply a filter by product and date.

Units Per Store Per Week

This table, which can be used to track product velocity, may also be leveraged in selling into other retailers. In conjunction with the other visualizations, this helps you note rises, falls, and stagnations by product and store.  

Sales by Zip Code

Similar to the heat map at the top of the dashboard, this displays sales by zip code and provides insights useful for geo targeting and seeing how demos or promotions have performed. Hover over the colored portions for granular insights into specific areas. Click to apply as a cross-filter.

Product Share Over Time

This graph assists in seeing how product share expands or shrinks over time. This can help you make decisions about product mix geographically and make assortment and distribution recommendations to Walmart.

Sales by Store Type

See at a glance POS data by store type, helping you identify which products do better in which format. When used with a date filter, you can see which formats do better at certain times of the year.