Build a saved search to export the customer price ...
# ask-stanley-ai
d
Build a saved search to export the customer price list for all customers and calculate the sales unit of measure
c
AI generated answer (using internal Slack threads):
To build a saved search to export the customer price list for all customers and calculate the sales unit of measure, you can follow these steps: 1. Navigate to Reports > Saved Searches > All Saved Searches > New. 2. Select Transaction as the record type. 3. In the Criteria tab, set the following: - Type is Sales Order. - Main Line is F (False). - Status is Sales Order:Pending Fulfillment or any other status that suits your needs. 4. In the Results tab, add the following fields: - Name (this will give you the customer name). - Item (this will give you the item name). - Quantity (this will give you the quantity of the item sold). - Amount (this will give you the total amount for the item). - Formula (Numeric) with the formula as
{amount}/{quantity}
(this will give you the unit price). 5. In the Summary Type field for each result, select Group for Name and Item, and Sum for Quantity and Amount. 6. Save and run the search. This will give you a list of all customers, the items they have purchased, the total quantity and amount for each item, and the unit price. Please note that this is a basic example and you might need to adjust the criteria and results to fit your specific needs. For example, you might want to add more filters in the criteria to only include certain customers or items, or add more fields in the results to include more information. ****** Disclaimer: This response was generated by an artificial intelligence assistant based on previous conversations from multiple Slack channels, and may contain inaccuracies or mistakes. ******
Slack thread 1: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.82184726
Slack thread 2: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.814304829
Slack thread 3: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.813604057
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