Migrate from FunnelMaker to Pipedrive

Discovery and export planning

We audit the FunnelMaker account to understand the current contact tier, record volumes across Contacts, Companies, Deals, and Activities, count of custom fields and custom objects, pipeline and stage configuration, active workflows and drip campaigns, tag and group taxonomy, and lead scoring rules. We identify any records approaching or exceeding the FunnelMaker contact tier cap to flag before extraction begins. We also map FunnelMaker exportable fields to Pipedrive field types and create a preliminary field mapping document. If FunnelMaker's export wizard does not expose certain custom objects or nested relationship data, we coordinate with the customer on manual pre-extraction steps before migration design is finalized.

Pipedrive schema setup

We configure the Pipedrive destination account before any data import. This includes creating the Pipeline object with stages matching FunnelMaker pipeline stages, creating all required custom fields with correct Pipedrive field types (string, number, date, single-select, multi-select, user) to match the FunnelMaker field schema, setting up Labels to match FunnelMaker tag and group lists, and creating any Custom Objects in Pipedrive (available on Premium and higher plans) using the itemSchemas API endpoint. We verify that the destination Pipedrive plan includes the required feature set for custom objects and multiple pipelines before schema deployment.

CSV export, staging, and cleansing

We extract data from FunnelMaker using the in-product CSV export tools for Contacts, Companies, Deals, and Activities. We stage the raw exports in a controlled environment, run a data quality audit to identify duplicate contacts, inconsistent formatting (email, phone, date), and missing required fields, and apply cleansing transforms before mapping. We match FunnelMaker Owner email addresses to Pipedrive User records in the destination account and flag any owners without a matching Pipedrive user for the customer's admin to provision before import proceeds.

Test migration and mapping validation

We run a test migration using a subset of the staged data (typically 100-200 records per object type) to validate field mappings, verify that Person-Organization and Deal-Person associations are resolving correctly, and confirm that custom field values are appearing in the right Pipedrive fields. The customer reviews the test migration output and approves mapping corrections. This step is critical because FunnelMaker's export format does not include Pipedrive field IDs, requiring manual mapping that is validated before production load. We do not proceed to full production migration until the customer signs off on the test results.

Production migration in dependency order

We run full production migration in record-dependency order: Pipedrive Users (validated against owner list), Organizations (from FunnelMaker Companies), Persons (from FunnelMaker Contacts with org_id resolved), Deals (with pipeline stage, person_id, and organization_id resolved), Activities (calls, emails, tasks, notes linked to Person and Deal), Labels (associated to Persons), custom object records (using itemSchemas/items endpoints), and lead scores as numeric field values. Each phase emits a row-count reconciliation report before the next phase begins. We apply the same cleansing transforms used in staging to the production data.

Workflow and drip campaign documentation

We document every active FunnelMaker workflow and drip campaign as a written automation inventory. For each workflow, we capture the trigger conditions, step sequence, time delays, action types, associated contact segments, and any conditional branching logic. We provide a recommended Pipedrive automation equivalent for each rule using Pipedrive's automation trigger and action system, noting where a Campaign add-on may be required for email sequence cadence features. The customer reviews the inventory and rebuilds automations in Pipedrive post-migration. We do not rebuild workflows as code inside the migration scope.

Cutover and post-migration validation

We freeze new-record creation in FunnelMaker during the cutover window, run a final delta import to capture any records modified or created after the last full load, then enable Pipedrive as the system of record. We validate a random sample of migrated records against the FunnelMaker source (record counts, field completeness, association integrity, and activity timeline continuity), validate that Deals are appearing in the correct pipeline stages with accurate values, and confirm that Labels are correctly applied. We provide a written migration summary and remain available for a one-week post-migration window to resolve any data integrity issues surfaced during initial team use.