Stockr is a Patchworks tool that handles stock levels across multiple Shopify stores which share the same pool of stock.
As orders are received, Stockr ensures that stock levels are aligned for all linked stores in real-time. So, if an item drops out of stock, all linked stores are updated simultaneously, ensuring that overselling does not occur.
Stockr is an add-on for Patchworks. If you would like more information about implementing Stockr for your system, please visit our website to book a demo.
As a Stockr user, you are provided with a unique URL to access a range of views in a DataDog dashboard.
Within the Patchworks dashboard, you can access a Stockr summary for full visibility on processed transactions and associated costs for any given date range. If required, you can choose to download transactions.
The Stockr summary is available for customers who use Stockr to manage stock levels across multiple Shopify stores.
Here, you can select any date range to view a summary of processed transactions and associated costs. You can also choose to download transactions in CSV format.
To access the Stockr summary, select the view account summary option from the left-hand navigation menu:
If Stockr is implemented for your system, a Stockr tab is available:
All options and information for the Stockr summary are accessed via the Stockr tab:
Select the required date range using the :
Transaction are displayed for any selected date range:
Here you can see:
The total number of transactions (i.e. Shopify orders) processed through Stockr
The Stockr charge per transaction
The total cost for selected transactions
The number of transactions for each store (within the given time period) is displayed :
All linked stores are listed in a , so you can choose any combination for download. Having made your required selections, click the beneath this list:
A CSV file is downloaded, containing all transactions within the given date range. The following information is included for each transaction:
Store URL
Order ID
Line items
Completed at date/time
Order logs (if present)