Import Pipedrive Data

Deprecation

From December 2021, we are no longer supporting the new version of importing data from Pipedrive. Please check out the announcement and suggested solution here.

Here is a quick 3-step process for querying Pipedrive data in Holistics. Pipedrive reporting in Holistics requires you to connect your Pipedrive database.

ETL for Pipedrive

Step 1: Set up a new data source to allow data import#

Set up your database to allow write access for a given data source. Setting up separate schema that allows write access is recommended. Please have a look at our docs on how to connect your database to Holistics.

Step 2: Create a new data import#

Click Add new data import in Manage -> Data Imports

Add new data import

Next:

  1. Choose Pipedrive as import source.
  2. Choose the data source from which you want import.
  3. Select a table in your database to preview it.

Choose pipedrive as data source

Step 3: Select/Create Destination Table#

Select your destination data source and schema name. Then enter your destination table name.

Setup Destination

Step 4. Validate input and destination table structure#

Specify the destination data source, schema name and table name that you would like to import the data into. Choose your sync configuration, and click on the Validate Sync Config button to validate the table setup. The column definitions are also automatically generated from the source data. The data type of each column can be modified as you see fit.

Validate Pipedrive Sync

Schedules for the current data import can be modified by selecting +Add Schedule. Optionally, data imports can be executed manually by clicking on the Execute link from the list of available data imports, after you have saved the import job.

Step 5. View data import status from job list#

Once a data import has been executed, either manually or based on its schedule, a new job corresponding to the import job will be created to track its progress.

Pipedrive Import Job

Users can click on the Job History tab to refresh and keep track of jobs that have run. Users can also click on the Logs link to view the detailed logs of each job execution.

Pipedrive Job History

Additional data#

Here are details for our supported API endpoints.

Activities#

COLUMNTYPE
idint
company_idint
user_idint
doneboolean
typevarchar
reference_typevarchar
reference_idint
due_datedate
due_timevarchar
durationvarchar
add_timetimestamp
marked_as_done_timetimestamp
subjectvarchar
deal_idint
org_idint
person_idint
active_flagboolean
update_timetimestamp
gcal_event_idvarchar
google_calendar_idvarchar
google_calendar_etagvarchar
notevarchar
participantsjson
person_namevarchar
org_namevarchar
deal_titlevarchar
assigned_to_user_idint
created_by_user_idint
owner_namevarchar
person_dropbox_bccvarchar
deal_dropbox_bccvarchar

Deals#

COLUMNTYPE
idint
creator_user_idint
user_idint
person_idint
org_idint
stage_idint
titlevarchar
valuedouble
currencyvarchar
add_timedate
update_timedate
stage_change_timedate
activeboolean
deletedboolean
statusvarchar
next_activity_idint
last_activity_idint
lost_reasonvarchar
visible_toint
close_timedate
pipeline_idint
won_timedate
first_won_timedate
lost_timedate
products_countint
files_countint
notes_countint
followers_countint
email_messages_countint
activities_countint
done_activities_countint
undone_activities_countint
reference_activities_countint
participants_countint
expected_close_datedate
last_incoming_mail_timedate
last_outgoing_mail_timedate
stage_order_nrint
rotten_timedate
weighted_valuedouble
cc_emailvarchar
org_hiddenboolean
person_hiddenboolean
average_time_to_wonnumeric string
average_stage_progressdouble
agenumeric string
stay_in_pipeline_stagesjsonb

Organizations#

COLUMNTYPE
idint
company_idint
owner_idint
namevarchar
open_deals_countint
related_open_deals_countint
closed_deals_countint
related_closed_deals_countint
email_messages_countint
people_countint
activities_countint
done_activities_countint
undone_activities_countint
reference_activities_countint
files_countint
notes_countint
followers_countint
won_deals_countint
related_won_deals_countint
lost_deals_countint
related_lost_deals_countint
active_flagboolean
category_idint
country_codevarchar
update_timedate
add_timedate
visible_toint
next_activity_idint
last_activity_idint
address_countryvarchar
cc_emailvarchar

Persons#

COLUMNTYPE
idint
company_idint
owner_idint
org_idint
namevarchar
first_namevarchar
last_namevarchar
open_deals_countint
related_open_deals_countint
closed_deals_countint
related_closed_deals_countint
participant_open_deals_countint
participant_closed_deals_countint
email_messages_countint
activities_countint
done_activities_countint
undone_activities_countint
reference_activities_countint
files_countint
notes_countint
followers_countint
won_deals_countint
related_won_deals_countint
lost_deals_countint
related_lost_deals_countint
active_flagboolean
phonevarchar
emailvarchar
update_timedate
add_timedate
visible_toint
next_activity_idint
last_activity_idint
last_incoming_mail_timedate
last_outgoing_mail_timedate
cc_emailvarchar

Stages#

COLUMNTYPE
idint
order_nrint
namevarchar
active_flagboolean
deal_probabilityint
pipeline_idint
rotten_flagboolean
rotten_daysint
add_timedate
update_timedate