Availability: Enterprise
Column mapping allows you to easily pull deal product fields into specific quote builder columns in PandaDoc.
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Enable column mapping
Column mapping needs to be configured on a template level. By default, data merge for column mapping is enabled for all newly added quote builder blocks in your templates. You can easily verify this by looking at the top-left corner of the quote builder block, where you will find a label 'Data merge is on' if it is enabled.
If data merge is disabled for a quote builder block in the template you're using to create documents from Pipedrive:
Then, select a quote builder you’d like to set column mapping for, or add a new one.
Select properties on the floating panel.
On the right, select Set up data merge.
Next, access the data merge in quote builder settings on the right and click Enable.
Set up column mapping
In the data merge pop-up, select Product field mapping, then type field names from Pipedrive (on the left) to be matched with quote builder column names (on the right).
The Pipedrive field name can be any of the following default product field names in Deals — Name, Description/Product Comments, Price, Quantity, sku, Discount, RateTax — and it’s crucial that you spell the name exactly as it’s spelled here.
Warning: Make sure to use 'QTY' in column mapping and avoid any other spelling. Otherwise, the quantity of products will be mapped and calculated incorrectly in the PandaDoc pricing table.
You can also use the following custom fields map with PandaDoc qupte builder columns: Text, Long Text, Autocomplete, Numeric, Multiple Options, Single Option, Phone, and Date fields.
If you’d like to map more pricing table columns, close the data merge set-up, then add columns by selecting the plus sign on the right.
Then, access the data merge rules via Product field mapping. You’ll see the newly added columns on the right. Now enter the field name from Pipedrive on the left and select Save button.
That's it! Whenever you create a document from Pipderive using this template, the product fields will populate the corresponding columns.