CRM migration
Field-level mapping, validation, and rollback between Fieldy and Pipedrive. We move data and schema; workflows are rebuilt natively in Pipedrive.
Fieldy
Source
Pipedrive
Destination
Compatibility
10 of 10
objects map 1:1 between Fieldy and Pipedrive.
Complexity
BStandard
Timeline
24–72 hours
Overview
Fieldy is a field-service management platform built around Jobs, Customers, Staff, and Work Orders — an object model optimized for dispatch, technician tracking, and service delivery. Pipedrive is a sales CRM built around Persons, Organizations, Deals, and Activities — an object model optimized for pipeline management, lead conversion, and sales reporting. These different orientations mean the migration is a data-model translation, not a simple record copy. We export Fieldy jobs as Pipedrive deals, customers as persons and organizations, line items as products, and service-visit activities as tasks. Pipedrive has no native work-order or field-dispatch object, so Fieldy job status maps to Pipedrive deal stage via a value-by-value translation table, job priority becomes a custom pick-list field, and service-type metadata becomes a custom text field. Original job-create dates and owner assignments are preserved as custom datetime and user-lookup fields. Workflows, automation rules, dispatch logic, and route-optimization settings in Fieldy have no Pipedrive equivalent — these are exported as a structured reference document for your team to rebuild in Pipedrive's automation builder. The migration runs through Pipedrive's REST API using batched upsert operations, with a delta-pickup window capturing any records modified during cutover.
Every standard and custom field arrives verified.
AI proposes the map; you confirm before any record moves.
Parent–child, lookups, and ownership stay linked.
Calls, emails, meetings — with original timestamps.
Documents, uploads, and inline notes move with the record.
Why teams make this switch
Leaving
What's pushing teams away
Choosing
What's pulling them in
Object mapping
Each row shows how a Fieldy object lands in Pipedrive, including any object-level transformations, lookup resolution, or schema-design dependencies.
Typical mapping — final map is confirmed during the sample migration step.
Fieldy
Customer
Pipedrive
Person + Organization
1:1Fieldy stores each customer contact as a flat record with company details embedded. We split these into a Pipedrive Person record (name, email, phone, title) and an Organization record (company name, domain, address). The organization is created first so the person can link via the org_id field on import.
Fieldy
Job
Pipedrive
Deal
1:1Fieldy Jobs map to Pipedrive Deals as the primary migration object. Each job carries customer, staff, location, status, priority, and line items. In Pipedrive the deal holds the work summary, linked person, and linked organization, with custom fields capturing the FSM-specific metadata that Pipedrive's native schema does not cover.
Fieldy
Job Status
Pipedrive
Deal Stage
1:1Fieldy job lifecycle states — Scheduled, In Progress, On Hold, Completed, Cancelled — map value-by-value to Pipedrive deal stages. We match the source status labels to existing Pipedrive stage names or create new stages that mirror Fieldy's workflow, preserving the original transition sequence for reporting continuity.
Fieldy
Job Priority
Pipedrive
Custom Pick-list Field
1:1Fieldy job priority (Low, Medium, High, Urgent) has no native Pipedrive equivalent. We create a Priority__c custom field on the Deal object and populate it from Fieldy's priority value. This field is visible on the deal detail view and usable in Pipedrive filters and automation conditions.
Fieldy
Work Order Line Item / Product
Pipedrive
Product + Deal Product
1:1Fieldy work-order line items — parts, labor, service fees — migrate as Pipedrive Products. Each product carries name, code, pricing, and currency. During deal migration, products are attached to the deal via the deal_product association so the deal view shows the full service itemization.
Fieldy
Staff / Technician
Pipedrive
User
1:1Fieldy Staff records represent field technicians and dispatchers. We resolve staff by email against Pipedrive users and assign migrated records to the matched owner. Unmatched staff are flagged as a pre-migration action — either invite them to Pipedrive first or assign their jobs to a fallback owner.
Fieldy
Job Activity / Site Visit
Pipedrive
Activity (Task)
1:1Fieldy site visits, service appointments, and scheduled activities migrate as Pipedrive Activities (Task type). Each activity records the subject, due date, assigned user, and linked deal. Original visit timestamps and duration data are preserved in the activity notes field for service-history continuity.
Fieldy
Job Notes / Description
Pipedrive
Deal Note
1:1Fieldy job descriptions and internal notes are written to Pipedrive Deal Notes. Notes preserve the original text, author (where resolvable), and creation timestamp. Rich-text formatting from Fieldy is flattened to plain text to ensure clean rendering in Pipedrive's note format.
Fieldy
Job Location / Address
Pipedrive
Custom Fields on Deal + Organization
1:1Fieldy stores the job site address separately from the customer address. The service-site address is preserved as a custom text field on the Pipedrive Deal. The customer address remains on the Organization record. If Fieldy stores GPS coordinates, these migrate to a custom lat-long text field for reference.
Fieldy
Route / GPS / Dispatch Data
Pipedrive
Custom Fields (Historical Reference Only)
1:1Fieldy's live dispatch board, GPS technician location, and route-optimization data have no Pipedrive equivalent. Historical location snapshots can be written to custom datetime-stamped text fields on the deal as an audit record, but the real-time dispatch board cannot be migrated. Organizations relying on Fieldy's field-service operations need to evaluate whether Pipedrive's task management is sufficient for their coordination needs.
| Fieldy | Pipedrive | Compatibility | |
|---|---|---|---|
| Customer | Person + Organization1:1 | Fully supported | |
| Job | Deal1:1 | Fully supported | |
| Job Status | Deal Stage1:1 | Fully supported | |
| Job Priority | Custom Pick-list Field1:1 | Fully supported | |
| Work Order Line Item / Product | Product + Deal Product1:1 | Fully supported | |
| Staff / Technician | User1:1 | Fully supported | |
| Job Activity / Site Visit | Activity (Task)1:1 | Fully supported | |
| Job Notes / Description | Deal Note1:1 | Fully supported | |
| Job Location / Address | Custom Fields on Deal + Organization1:1 | Fully supported | |
| Route / GPS / Dispatch Data | Custom Fields (Historical Reference Only)1:1 | Fully supported |
Gotchas + challenges
Platform-specific issues from each side, plus the pair-specific challenges that don't show up on either platform's page on its own.
Fieldy gotchas
No documented public API or bulk export endpoint
Custom workflow automations do not export as portable rules
Pricing tiers and per-user limits not publicly confirmed
Pipedrive gotchas
Custom field hash keys differ per account
Export access gated by visibility groups
Token-based API rate limits since December 2024
Sequences and Automations not exposed via REST API
Cost escalates via workflow caps and add-ons
Pair-specific challenges
Migration approach
Audit Fieldy data export and scope the migration map
We connect to Fieldy via scoped read-only API access and export all active jobs, customers, staff, line items, and activities. We audit record counts, identify custom field usage, and map Fieldy's job-status values to Pipedrive deal stages using a value-by-value translation table. This step produces the field-level mapping document and a pre-flight report flagging any owner-resolution gaps before migration runs.
Configure Pipedrive pipelines, stages, and custom fields
Before data lands, we create Pipedrive pipelines and stages that mirror Fieldy's job workflow states, set up custom fields for work type, job priority, GPS snapshot, and original job dates, and define activity types for site visits and service inspections. We also resolve Fieldy technician emails against existing Pipedrive users, flagging any unmatched owners for your team to invite or reassign before the migration begins.
Run a sample migration and generate a field-level diff
We run a representative sample — typically 100–500 records spanning jobs across different statuses, priority levels, and staff assignments — and generate a field-level diff comparing source values to destination values. You verify job-to-deal mapping, stage translation, owner resolution, and line-item association before the full run commits. Any mapping corrections are fed back into the migration configuration before the production run.
Execute full migration with delta-pickup window
The full dataset migrates via Pipedrive's REST API using batched upsert operations. A delta-pickup window of 24–48 hours runs after the main migration to capture any jobs modified or created in Fieldy during the cutover. Pipedrive rate-limit backoff logic keeps the migration within API constraints. Audit log captures every record operation with source ID, destination ID, and field-level change summary.
Reconcile and deliver the automation rebuild reference
We run a reconciliation report comparing source record counts and field totals against the FlitStack audit log and Pipedrive destination records. We deliver the automation reference document listing Fieldy workflow rules, dispatch triggers, and notification logic as a structured guide for rebuilding in Pipedrive's automation builder. One-click rollback reverts the destination to the pre-migration state if reconciliation finds critical discrepancies.
Platform deep dives
Fieldy
Source
Strengths
Weaknesses
Pipedrive
Destination
Strengths
Weaknesses
Complexity grading
Standard CRM migration. 3 of 8 objects need a mapping; the rest are 1:1.
Overall complexity
Standard migration
Derived from compatibility, mapping clarity, API constraints, and data volume across Fieldy and Pipedrive.
Object compatibility
3 of 8 objects need a mapping; the rest are 1:1.
Field mapping clarity
Field mapping is derived from defaults — final spec confirmed during the sample migration.
Timeline complexity
8-object category — typical timelines run 2–7 days end-to-end.
API constraints
Fieldy: Not publicly documented..
Data volume sensitivity
Fieldy doesn't expose a bulk API — REST + parallelization used for high-volume runs.
Estimator
Rule-based pricing — no per-record fees, no manual quotes. Migrations over 2M records are scoped individually.
Step 1
Pick a category, then your source and destination platforms.
Category
FAQ
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