Best Practices: How to combine data from different Pipedrive data entities?
The Pipedrive data source lets you pull data separately from the following entities: Deals, Persons, Organizations, Files, etc. If you need to import a mix of fields from different entities, you can use Coupler’s features to combine them effectively and export to your preferred data destination.
Let’s walk through an example to illustrate how this can be done.
Use case:
We need to import the Persons data that includes their related Deals info. For this case, we need certain fields from Persons ( name, id, org_id.name, org_id.address), and two fields from Deals (people value, value).
Step 1
Set up a Pipedrive data flow with 2 sources: Persons and Deals
Pipedrive Data Flow #1:
- Data entity: Persons
- Fields: name, org_id.name, org_id.address, and People Contact id (id)
That's how the imported Persons data set looks:
Pipedrive Data Flow #2:
- Data entity: Deals
- Fields: People Value, value
The field people_value is needed to join both data entities
That's how the imported Deals data set looks:
Step 2
Now, we need to find the field available in both Persons and Deals data entities, so we can use it to join the data together. In our case, as mentioned before, the field's name in Deals is People: Value
We are going to join data from Persons and Deals using this common field. Learn more about join and data stitching here.
As a result, we can now see the dataset combining Persons with associated Deals columns. We can then filter out the columns to achieve our desired output - see more about Column Management here:
We'll then have a final result which can be sent to your preferred destination - remember to select your joined data set:
