Leads

The Leads pipeline can be used to request and retrieve all leads sorted by the time they were created, from oldest to newest. Leads are potential deals stored in Leads Inbox before they are archived or converted to a deal. Each lead needs to be named (using the title field) and be linked to a person or an organization. In addition to that, a lead can contain most of the fields a deal can (such as value or expected_close_date). Read more about this here

Configuring the Credentials

Select the account credentials which has access to relevant Pipedrive data from the dropdown menu & Click Next

Credentials not listed in dropdown ?

Click on + Add New for adding new credentials

Data Pipelines Details

Data Pipeline

Select Leads from the dropdown

Setting Parameters

Parameter Description Values

Fetch Mode

Required

Specifies the manner in which data will fetched from the Pipedrive API : INCREMENTAL fetches new records after the latest update whereas FULL fetches everything.

Full, Incremental

Insert Mode

Required

Specifies the manner in which data will get updated in the data warehouse : UPSERT will insert only new records or records with changes, APPEND will insert all fetched data at the end, and REPLACE will drop the existing table and recreate a fresh one on each run. Recommended to use "Upsert" option unless there is a specific requirement.

{Upsert, Append, Replace}

Default Value: UPSERT

Datapipeline Scheduling

Scheduling specifies the frequency with which data will get updated in the data warehouse. You can choose between Manual Run, Normal Scheduling or Advance Scheduling.

Manual Run

If scheduling is not required, you can use the toggle to run the pipeline manually.

Normal Scheduling

Use the dropdown to select an interval-based hourly, monthly, weekly, or daily frequency.

Advance Scheduling

Set schedules fine-grained at the level of Months, Days, Hours, and Minutes.

Detailed explanation on scheduling of pipelines can be found here

Dataset & Name

Dataset Name

Key in the Dataset Name(also serves as the table name in your data destination).Keep in mind, that the name should be unique across the account and the data source. Special characters (except underscore _) and blank spaces are not allowed. It is best to follow a consistent naming scheme for future search to locate the tables.

Dataset Description

Enter a short description (optional) describing the dataset being fetched by this particular pipeline.

Notifications

Choose the events for which you’d like to be notified: whether "ERROR ONLY" or "ERROR AND SUCCESS".

Once you have finished click on Finish to save it. Read more about naming and saving your pipelines including the option to save them as templates here

Still have Questions?

We’ll be happy to help you with any questions you might have! Send us an email at info@datachannel.co.

Subscribe to our Newsletter for latest updates at DataChannel.