Shift4Shop automatically compiles statistical information about each product sold in your store. This can be useful in determining if a specific product sells better during a particular season, so you can determine when and how often to keep it in stock.
To view Customer and Product stats, please be sure to enable the "Advanced Statistics - Products and Customers" module in your online store manager's Modules page.
To view product statistics
- Go to Products and search for the product that you'd like to review.
- Click on the item's name (or you can look to the far right and click on the item's "Action >Edit" button
- Next, click on the Stats tab.
Below is a list of the information contained in the product's Statistics Page.
- Product Rank:
The first ranking number is the ranking score based on the total number of items historically sold in the store. The second ranking number is the ranking score based on the total amount (value) historically sold in the store.
This comparison between total number sold vs total value sold can be useful in determining the ranking of a product by taking into consideration its value as well as its popularity. For example, you may have a very high-priced item that doesn't sell very often due to its price. Therefore, it wouldn't rank very high on the first line (number of items sold). However, when it does sell, it ranks very high in the second line (value ranking).
- First/Last Sale:
The first and last dates the product was sold.
- Average Cost:
The average cost of the product (internal/your cost).
- Total Sold:
Total amount (Value) sold of the product - total number of the product sold. The second line is the percentage of the total store sales (Value) the product makes up in your store
- Average Price:
The average price the product is sold for.
- Average Qty.:
Average number of the product each customer purchases per order.
Alternately, the product's statistical information can be used simply to determine the product's popularity in general terms for your business. For example, if a product doesn't sell all that well, you can use its statistical information to determine if perhaps you shouldn't order it from your supplier as often as normal and (hopefully) minimize your costs during restocking.