customer saved search to calculate days between invoicing transactions

AI generated answer (using internal Slack threads):

To calculate the average number of days between invoices for a customer, you can create a saved search with the following steps: 1. Create a new Transaction Saved Search. 2. Set the criteria to filter for the specific customer and transaction type (Invoice). 3. In the Results tab, add the following fields: -

Date

(with summary type

Minimum

) -

Date

(with summary type

Maximum

) -

Internal ID

(with summary type

Count

) 4. In the Formula field, use the following formula:

COUNT(internalid) / ({today} - MIN(transactiondate))

This will give you the average number of days between invoices. To calculate the number of days since the last invoice, you can use a similar approach but change the formula to:

today - MAX(transactiondate)

For customers with overdue balances that have not made a payment in 45 days, you can create a saved search with the following criteria: 1. Transaction Type: Invoice 2. Main Line: True 3. Due Date: > 45 days 4. Status: Open In the Results tab, add the

Name

field. To check if they made a payment even if it was on a different invoice, you can add another criteria: 1. Applied To Transaction Date: > 45 days Remember to set the Main Line to False for this criteria. For calculating the quantity invoiced from the last 30 days from the time when it was last invoiced, you can create a saved search with the following steps: 1. Create a new Transaction Saved Search. 2. Set the criteria to filter for the specific customer and transaction type (Invoice). 3. In the Results tab, add the following fields: -

Date

(with summary type

Maximum

) -

Quantity

(with summary type

Sum

) 4. In the Formula field, use the following formula:

SUM(quantity) / ({today} - MAX(transactiondate))

This will give you the quantity invoiced from the last 30 days from the time when it was last invoiced. ****** Disclaimer: This response was generated by an artificial intelligence assistant based on previous conversations from multiple Slack channels, and may contain inaccuracies or mistakes. ******