Question 1

Which Pipedrive objects can Polytomic sync?

Accepted Answer

For reads: deals, persons, organizations, activities and activity types, leads with their labels and sources, projects, and the field definition objects for deals, persons, organizations, activities, and leads. Notes and products are not available as standalone sources despite appearing in Pipedrive's API. For writes: persons, deals, and organizations only. That covers the objects teams actually push data onto, but it does mean activities and leads are read only.

Question 2

How does Polytomic handle Pipedrive's hashed custom field keys?

Accepted Answer

Pipedrive returns custom values keyed by an opaque hash rather than a readable name, which makes raw exports painful to work with. Polytomic syncs the field metadata objects alongside your records, and those provide the mapping from each hash to its display name, type, and any picklist options. So you join the metadata to the values in your data warehouse and get labeled columns. On the write side you map to the hashed key directly, and only fields Pipedrive marks as bulk editable with types Polytomic understands are offered.

Question 3

Does Pipedrive sync incrementally?

Accepted Answer

For the four objects where it matters most: deals, persons, organizations, and activities. Those are requested sorted by update time descending, passing the previous checkpoint so only changed records come back, and the checkpoint advances to the newest record seen. Everything else, including leads, projects, activity types, and all the field metadata objects, is a full read on each ETL execution. Those are small enough that it rarely matters. Note that the older model based source path does full reads rather than using this incremental behavior.

Question 4

How are existing Pipedrive records matched when writing?

Accepted Answer

Most reliably by Pipedrive record ID. If you do not have that, persons can be matched on an exact email search, deals on title, and organizations on name. The important caveat is that these use Pipedrive's search and take the first result, so if two persons share an email or two deals share a title, the match is ambiguous and could update the wrong record. Where your data allows it, sync Pipedrive IDs into your data warehouse first and key off them on subsequent writes. There is no delete mode.

Question 5

Why use reverse ETL with Pipedrive instead of a native integration?

Accepted Answer

Because the data reps need usually is not in another SaaS tool, it is derived. Product usage trends, health scores, payment status, and lead scores are computed in your data warehouse from several systems, and no point to point integration produces them. Reverse ETL writes those onto the deal, person, or organization so they show up in the CRM where selling happens. It also runs the other direction on the same platform, so Pipedrive data feeds the models that generate those scores, which is what makes the loop work.

Pipedrive

Perfect pairings

Bi-directional syncing

Custom fields decoded

Incremental core objects

Example workflows

What you can sync

From Pipedrive

To Pipedrive

How it works

How to set up

Frequently asked questions

Why teams choose Polytomic

No engineering required

Flexible data modeling

Handles scale automatically

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