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Pipedrive

Signals reads deals, leads and contacts from Pipedrive on a recurring schedule and sends the mapped fields onward.

Pipedrive keeps leads and deals apart. The Leads Inbox holds unqualified enquiries, and a lead becomes a deal when it is converted. They are separate modules, so which one you read decides what you can report. If you are measuring lead quality, the deal is usually what carries the outcome.

  • A Pipedrive account holding the records you intend to sync, in the module you intend to read: Deals, Leads or Contacts.
  • Administrator access to your Pipedrive account, on a plan that includes API access. You need it to authorize Datahash and grant read access to the modules and records you map.
  • A single-select field on the module you sync holding each record’s stage, such as New, Contacted, Qualified, Won or Lost. Each value maps to a conversion event, so a record left on a stale stage reports the wrong one.

In Studio, open Sources, find the CRM category, and click the Pipedrive tile. This connector uses single sign-on, so no Pipedrive credentials are entered into Datahash.

  • Click Sign in with Pipedrive.
  • Sign in to the Pipedrive account you want to read.
  • Approve the requested access.

Select the Integration Type based on where the data needs to be sent. The options are Offline Events, Audience, Meta CAPI CRM, Google Leads, TikTok Leads, Snapchat Leads and LinkedIn Leads. The choice decides which fields you are asked to map and which destinations the connection can feed, so settle it first. Then choose the Pipedrive module Signals reads from, one of Deals, Leads or Contacts, and give the instance a name. Only modules the authenticated user can see will appear in the list.

Map your Pipedrive fields onto the schema Signals expects. Each field is a dropdown of your own fields, so nothing has to be renamed in the CRM. What you are asked to map depends on the integration type.

GroupFields
ConfigurationEvent name, event time, last modified date, lead lifecycle stage.
Personal informationEmail, phone, first name, last name, city, state, country, postcode, gender, date of birth, Facebook click ID, Google click ID, OpenAI identifier, source URL.
ProductTotal value, currency, product type, name, category, ID, brand, price, quantity, transaction ID, number of items.

Click Test Connection before finishing. It checks both that the credentials still work and that the mapped fields actually contain data, so a mapping pointed at an empty field fails here rather than silently later. The latest records are shown against your mapping, with any errors visible in the table itself.

One instance is configured for one module. To read another module, configure it on a new instance from the Manage existing instance table. To change an existing one, open it from the Manage existing instance table, click the edit option in the menu to the top right, update the fields and click Finish.

Only the fields you map are read. Personal identifiers are normalized and SHA-256 hashed before they are sent to any destination.

Email, phone, name and location are what destinations match on. Product and transaction fields describe the conversion rather than the person, so they do not affect match rates.

  • If you map a platform lead ID such as the Meta Lead ID, keep that field as text. A numeric field truncates long IDs, which is the most common cause of lead conversions never matching.
  • Fix formatting in Pipedrive, not downstream: lowercase email, phone in E.164, no trailing whitespace. A badly formatted value hashes to something that will never match.

A mapped custom field stopped working. It was deleted and recreated rather than renamed, so the internal key changed. Remap it.

The wrong email address is being sent. The record holds several. Check which one the mapping points at.

Lead outcomes are not reflected at the destination. Stage is mapped instead of status.

Lead conversions never match at the platform. The lead ID field is numeric and the IDs are truncated. Change it to text and re-sync.

Match rates are low. Map more identifiers and fix formatting at source. A hash only matches if both sides normalized the value the same way.