Migrate from Bloomr to Pipedrive

Discovery and API exploration

We begin every Bloomr engagement with live API exploration to confirm whether authentication is accessible, which endpoints respond, what pagination behavior exists, and what rate limits apply. We profile the data structure for Contacts, Companies, Deals, Activities, and custom fields by querying the API or, if the API is inaccessible, by documenting the Bloomr UI export capabilities. This phase produces a written data inventory with record counts per object type, field names and types discovered, and a confirmed migration path (API-based or manual CSV). Bloomr's undocumented nature means this phase cannot be skipped.

Pipedrive destination configuration

We configure the Pipedrive destination account before any data is imported. This includes creating custom fields on Person, Organization, and Deal to match the Bloomr fields discovered during profiling. We set up the Pipeline and Stage structure in Pipedrive, mapping Bloomr deal stage values to Pipedrive stage labels in the configured order. We provision the customer on the appropriate Pipedrive plan (Essential at minimum for basic CRM; Advanced for workflow automation needs) and ensure all active users are invited and active.

User reconciliation

We extract every distinct Bloomr Owner referenced on Contacts, Companies, and Deals and match by email against the destination Pipedrive User table. Owners without a matching Pipedrive User are placed in a reconciliation queue. The customer's Pipedrive admin provisions any missing users before production migration begins. Owner assignments on migrated records are resolved via the User ID mapping at this stage.

Data profiling and field mapping workbook

We produce a field mapping workbook that documents every Bloomr field (standard and custom) mapped to its Pipedrive equivalent, including field type, transformation logic (if required), and dedupe key strategy. This workbook is the source of truth for the migration script and is reviewed with the customer's admin before production migration. Bloomr's lack of public schema documentation means this workbook is built from live data profiling rather than published reference.

Sandbox migration and reconciliation

If the customer maintains a Pipedrive Sandbox or a trial account, we run a full migration into that environment first using production-like data volume. The customer's admin reviews record counts, spot-checks 25-50 random records against the Bloomr source, and validates the Pipeline and Stage configuration. Mapping corrections are made in the field mapping workbook and validated in the Sandbox before production migration begins. This step prevents remediation work in a production environment.

Production migration in dependency order

We run production migration in record-dependency order: Organizations (from Bloomr Companies), Persons (from Bloomr Contacts with OrganizationId resolved), Deals (with PersonId and OwnerId resolved), and Activities (with PersonId and DealId resolved). Custom fields are created in Pipedrive before their parent records are imported. Each phase emits a row-count reconciliation report before the next phase begins. All import runs use Pipedrive's REST API with batch chunking and rate-limit handling.

Cutover, validation, and automation handoff

We freeze writes in Bloomr during cutover, run a final delta migration of any records modified during the migration window, then enable Pipedrive as the system of record. We deliver the automation audit template to the customer's admin for documenting existing Bloomr workflows and rebuilding them in Pipedrive. We support a one-week hypercare window for reconciliation issues. We do not rebuild Bloomr automations as Pipedrive workflows inside the migration scope.