CRM migration

Migrate from Fieldy to HighLevel

Field-level mapping, validation, and rollback between Fieldy and HighLevel. We move data and schema; workflows are rebuilt natively in HighLevel.

Fieldy logo

Fieldy

Source

HighLevel

Destination

HighLevel logo

Compatibility

100%

12 of 12

objects map 1:1 between Fieldy and HighLevel.

Complexity

BStandard

Timeline

48–72 hours

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Teams move from Fieldy to HighLevel when they want to consolidate field service data with marketing automation and CRM under one subscription. Fieldy stores jobs, estimates, invoices, staff, and custom properties in a field-service-centric schema. HighLevel models everything as contacts, companies, and opportunities with pipeline stages and custom fields, plus a separate workflows engine for automations. FlitStack AI maps Fieldy's jobs to HighLevel opportunities (using the pipeline and stage fields), Fieldy's estimates and invoices to opportunities with custom fields holding monetary values, and Fieldy's staff records to contacts with a staff-role custom field. Custom properties on Fieldy objects migrate as HighLevel custom fields — the platform supports both contact-level and opportunity-level custom fields. Fieldy's tags map to HighLevel tags natively. FlitStack sequences the migration so foreign-key relationships resolve correctly: companies migrate first, then contacts with company lookups, then opportunities referencing those contacts. Workflows, scheduling rules, and dispatch logic do not migrate — they must be rebuilt in HighLevel's Workflows engine using Fieldy export documentation as a reference. The migration runs via HighLevel's Bulk CSV import API and REST API with a 24–48 hour delta pickup window for in-flight work orders.

Field-level fidelity

Every standard and custom field arrives verified.

Schema-aware mapping

AI proposes the map; you confirm before any record moves.

Relationships preserved

Parent–child, lookups, and ownership stay linked.

Full activity history

Calls, emails, meetings — with original timestamps.

Attachments & notes

Documents, uploads, and inline notes move with the record.

Why teams make this switch

Two sides of the same decision

Leaving

Fieldy logo

Fieldy

What's pushing teams away

  • Lack of API documentation or public bulk export endpoint makes data portability a manual, error-prone process that frustrates teams with large historical records.
  • Limited third-party integration ecosystem compared to established FSM platforms, creating friction for businesses relying on accounting or ERP connections.
  • The white-label offering referenced in reviews suggests feature limitations that become apparent as businesses scale beyond basic field service needs.

Choosing

HighLevel logo

HighLevel

What's pulling them in

  • Agencies choose HighLevel to consolidate CRM, email, SMS, scheduling, and funnels into one subscription, eliminating monthly bills for five to ten separate SaaS tools they previously stitched together.
  • The flat-rate pricing model bills per sub-account rather than per contact, so growing a contact database from 1,000 to 100,000 records does not trigger a billing surprise—a common pain point avoided by migrating customers.
  • White-label and sub-account capabilities let agencies resell HighLevel access to their own clients, turning a software cost center into a recurring revenue stream that justifies the subscription.
  • The platform ships a 14-day free trial with no credit card required, giving teams a low-friction entry point to validate fit before committing to the $97/month Starter tier.
  • Marketing agencies managing multiple client accounts use sub-accounts to maintain data isolation per client while operating under a single agency billing relationship with HighLevel.

Object mapping

How Fieldy objects map to HighLevel

Each row shows how a Fieldy object lands in HighLevel, including any object-level transformations, lookup resolution, or schema-design dependencies.

Typical mapping — final map is confirmed during the sample migration step.

Fieldy

Contact (Customer)

maps to

HighLevel

Contact

1:1
Fully supported

Fieldy customer contacts map directly to HighLevel contacts. Fieldy stores name, phone, email, and address on contacts. HighLevel requires contacts to be associated with a company (company_id field) — contacts without a company in Fieldy attach to a default placeholder company in HighLevel during migration.

Fieldy

Company/Client

maps to

HighLevel

Company

1:1
Fully supported

Fieldy company records (client businesses) map to HighLevel companies. Fieldy stores company name, domain, address, and custom properties. HighLevel companies have a Name, Website, and custom fields — address data migrates to the contact-level address associated with the primary contact or as a custom field on the company record.

Fieldy

Job/Work Order

maps to

HighLevel

Opportunity

1:1
Fully supported

Fieldy jobs are the core work-order record and map to HighLevel opportunities. The job name becomes the opportunity name, job amount maps to opportunity Amount, job status maps to a pipeline stage, and the close date maps to CloseDate. Job custom properties migrate as opportunity-level custom fields in HighLevel.

Fieldy

Job Pipeline (Fieldy status workflow)

maps to

HighLevel

Pipeline + Stage

1:1
Fully supported

Fieldy's job-status workflow (e.g., New → Scheduled → In Progress → Completed → Invoiced) maps to a HighLevel pipeline with matching stage names. Each Fieldy status value becomes a HighLevel stage within the pipeline. Stage probability values are applied per stage during migration configuration.

Fieldy

Estimate

maps to

HighLevel

Opportunity + Custom Fields

1:1
Fully supported

Fieldy estimates have line items, totals, and approval status with no direct HighLevel equivalent. FlitStack migrates estimates as Opportunities with custom fields capturing estimate total (Estimate_Total__c), status (Estimate_Status__c), and line items serialized as a JSON custom field (Line_Items__c) for reference. Rebuilding formal estimates in HighLevel requires a third-party quoting tool or custom development.

Fieldy

Invoice

maps to

HighLevel

Opportunity + Custom Fields

1:1
Fully supported

Fieldy invoices carry line items, tax, total, and payment status. No native invoice object exists in HighLevel. FlitStack migrates invoices as Opportunities with custom fields for Invoice_Number__c, Invoice_Total__c, Amount_Paid__c, and Balance_Due__c. Actual invoice recreation requires connecting a HighLevel-supported payment provider (Stripe, Square) or rebuilding invoices manually.

Fieldy

Staff/Technician

maps to

HighLevel

Contact + Custom Fields

1:1
Fully supported

Fieldy staff records include name, phone, email, certifications, and availability. HighLevel has no staff object — staff migrate as Contacts with a custom Role__c pick-list field set to 'Technician' or 'Field Staff'. HighLevel user accounts are separate and map by email match. Permissions are set via HighLevel user roles and profile assignments post-migration.

Fieldy

Location/Service Address

maps to

HighLevel

Contact Address + Custom Fields

1:1
Fully supported

Fieldy stores service location addresses on jobs and contacts. HighLevel contacts have a native address block (street, city, state, zip, country). Fieldy location coordinates (lat/long) migrate as custom fields (Service_Lat__c, Service_Lng__c) since HighLevel does not store geocoordinates natively on contact records.

Fieldy

Tag

maps to

HighLevel

Tag

1:1
Fully supported

Fieldy tags on contacts, companies, and jobs map directly to HighLevel tags. Tags are a native HighLevel construct applicable to contacts and opportunities. Multi-value tags on a single Fieldy record preserve all values in HighLevel's tag array. Additionally, tags can be used for segmentation and automation triggers in HighLevel workflows.

Fieldy

Note/Attachment

maps to

HighLevel

Note

1:1
Fully supported

Fieldy notes on jobs and contacts migrate to HighLevel notes attached to the corresponding opportunity or contact. File attachments are downloaded and re-uploaded to HighLevel's file storage. Note timestamps and author information are preserved in the HighLevel note record where supported.

Fieldy

Custom Property (Fieldy)

maps to

HighLevel

Custom Field (HighLevel)

1:1
Fully supported

Fieldy custom properties on contacts, companies, and jobs require corresponding custom fields in HighLevel. FlitStack creates contact-level and opportunity-level custom fields in HighLevel before migration. Field data types are preserved: text, number, pick-list, date, and checkbox map to HighLevel's custom field types respectively.

Fieldy

Workflow / Automation (Fieldy)

maps to

HighLevel

Workflow (HighLevel)

1:1
Fully supported

Fieldy workflow rules (e.g., auto-assign job to technician based on zip code, send SMS on job completion) have no direct equivalent in HighLevel. FlitStack exports Fieldy workflow definitions as a JSON reference document for manual rebuild in HighLevel's Workflows engine. The migration does not move automation logic automatically.

Gotchas + challenges

What specifically takes care here

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 logo

Fieldy gotchas

High

No documented public API or bulk export endpoint

Medium

Custom workflow automations do not export as portable rules

Low

Pricing tiers and per-user limits not publicly confirmed

HighLevel logo

HighLevel gotchas

High

Sub-account architecture creates isolated data silos per client

High

Usage-based telecom and AI costs are not in the subscription price

Medium

Workflows have no native equivalent in most destination CRMs

Medium

API rate limits cap bulk migration throughput at 100 requests per 10 seconds per sub-account

Low

White-label configuration and branding assets do not export via API

Pair-specific challenges

  • Job-to-opportunity transformation loses native scheduling context

    Fieldy jobs carry scheduling data (assigned technician, scheduled time window, dispatch route) that HighLevel's opportunity model does not store natively. FlitStack migrates the technician assignment as a custom contact lookup field and the scheduled date as a custom date field, but the dispatch board, route-optimization data, and availability calendar from Fieldy do not have HighLevel equivalents. Scheduling logic must be rebuilt using HighLevel's calendar booking and Workflows engine after migration.

  • Estimate and invoice objects require manual reconstruction

    HighLevel has no native estimate or invoice object. Fieldy estimates migrate as opportunities with custom fields holding estimate totals and line-item data serialized as JSON. Fieldy invoices migrate similarly with payment-status fields. Formal estimate documents and invoice PDFs cannot be natively generated in HighLevel without connecting a third-party quoting tool (Qvo, Proposify) or building a custom integration. Teams relying on Fieldy's billing features should plan this rebuild as a separate workstream.

  • Staff records do not get HighLevel user accounts automatically

    Fieldy staff members are first-class records with certifications and availability. In HighLevel, staff migrate as contacts with a custom Role__c field — they are not automatically provisioned as HighLevel users. FlitStack flags all staff records that have no matching HighLevel user account by email. Your team must create HighLevel user accounts for staff who need CRM access, and assign HighLevel user roles and sub-account permissions manually post-migration and verify all.

  • Fieldy workflow automations do not transfer and have no HighLevel equivalent

    Fieldy workflow rules (auto-assign jobs, trigger SMS on status change, escalation logic) are platform-native automation constructs with no structural equivalent in HighLevel. FlitStack cannot migrate automation logic. We export Fieldy workflow definitions as a structured JSON reference document so your HighLevel admin can rebuild triggers, conditions, and actions in the HighLevel Workflows engine. This is the most manual-heavy part of any Fieldy-to-HighLevel migration, and should be prioritized early in the project.

  • Custom properties require pre-migration field creation in HighLevel

    Fieldy supports custom properties on contacts, companies, jobs, and staff. HighLevel custom fields must be created before data can load into them. FlitStack audits all Fieldy custom properties during the planning phase and generates a HighLevel custom-field creation checklist. If custom property count exceeds 50, pre-migration field creation becomes a significant planning step and affects the overall migration timeline, and requires coordination with your HighLevel admin to allocate time for field definitions before the migration window opens.

Migration approach

Six steps for a successful Fieldy to HighLevel data migration

  1. Audit Fieldy data model and map custom properties

    FlitStack pulls a full export of your Fieldy account via API, cataloguing all standard objects (contacts, companies, jobs, estimates, invoices, staff), custom property definitions with their data types, and active workflow rules. We generate a custom-field creation checklist for HighLevel and a workflow export JSON. This audit determines the exact number of HighLevel custom fields needed and flags any data that cannot map directly.

  2. Create HighLevel schema and custom fields

    Before any data moves, FlitStack creates the HighLevel custom fields identified in the audit: opportunity-level fields for job data (Estimate_Total__c, Invoice_Number__c, Service_Lat__c, Service_Lng__c, Scheduled_Date__c), contact-level fields for staff role and certifications, and company-level fields for any Fieldy company custom properties. We also configure the job pipeline with stages matching Fieldy's job-status workflow. Your HighLevel admin reviews and approves the schema before migration runs.

  3. Migrate companies and contacts in dependency order

    HighLevel requires companies before contacts can associate via company_id. FlitStack sequences the migration: companies load first, then contacts with their company lookups resolved by name match, then staff as contacts with Role__c set to 'Technician'. Tags on all three object types load as HighLevel native tags. Fieldy-to-HighLevel email matches resolve owner assignments for contacts. Any contacts without a matching company in Fieldy attach to a default placeholder company.

  4. Migrate jobs as opportunities with custom field data

    With companies and contacts in place, FlitStack loads Fieldy jobs as HighLevel opportunities. Each opportunity receives its name, amount, stage from the Fieldy status-to-pipeline-stage mapping, and close date. Opportunity-level custom fields capture scheduled date, service coordinates, estimate totals, and invoice details. Technician assignments resolve by email match to staff contacts and populate the Assigned_Technician__c custom lookup field. Notes and attachments from Fieldy jobs attach to the corresponding opportunity.

  5. Run sample migration with field-level diff and validation

    A representative slice of records (typically 100–500 spanning contacts, companies, jobs, and estimates) migrates first. FlitStack generates a field-level diff comparing source Fieldy values against destination HighLevel fields for every mapped column. You verify custom field mapping, pipeline stage assignment, technician resolution, and tag population before the full run commits. Approval of the sample is the go-ahead for the full migration.

  6. Execute full migration with delta-pickup window

    The full dataset migrates in batches using HighLevel's Bulk CSV import API and REST API for records requiring custom field resolution. A delta-pickup window (24–48 hours) captures any Fieldy records modified during the migration run — jobs marked complete, new contacts added, invoices paid. FlitStack applies these delta records to HighLevel so the destination reflects Fieldy's final state at go-live.

Platform deep dives

Context on both ends of the pair

Fieldy logo

Fieldy

Source

Strengths

  • Per-user pricing model that is budget-friendly for growing field service businesses, according to Fieldy's own positioning.
  • Real-time live location tracking for field technicians with scheduling and dispatch automation built in.
  • All-in-one quote-to-payment workflow consolidates what many SMBs manage across multiple disconnected tools.
  • Mobile and web access for field reps with instant onboarding and no mandatory credit card to start a trial.
  • Customizable workflows, checklists, forms, and notifications for 25+ industry verticals.

Weaknesses

  • No publicly documented API or bulk export endpoint, making data portability a manual process.
  • Limited integration ecosystem compared to larger FSM competitors like ServiceTitan or Jobber.
  • Feature set oriented toward small-to-mid businesses; white-label limitations become apparent at scale.
  • No third-party review presence beyond a single G2 review and a 3.3-star Capterra rating, suggesting limited enterprise adoption or market penetration.
HighLevel logo

HighLevel

Destination

Strengths

  • Consolidates CRM, marketing automation, email, SMS, scheduling, and funnels into one platform at a predictable flat monthly rate.
  • Supports unlimited contacts and unlimited users on all paid tiers, removing per-record billing anxiety as databases grow.
  • Offers white-label and sub-account capabilities that let agencies resell access and manage multiple client environments under one billing relationship.
  • Includes built-in review management, reputation monitoring, and AI agents as native features rather than third-party add-ons.
  • Exports Contacts and Companies via a scalable async bulk CSV system that handles multi-million-row datasets without blocking the UI.

Weaknesses

  • The breadth of features creates a steep learning curve; advanced automations and Workflow configuration require significant time investment that smaller teams may not recover.
  • The platform charges usage-based fees for telecommunications and AI features that are not included in the base subscription, leading to bill surprises.
  • Recurring user reports on Reddit and G2 describe bugs, errors, and slow support response times that disrupt live marketing and sales operations.
  • Sub-account architecture, while powerful for agencies, adds migration complexity when identifying which client data lives in which isolated environment.
  • The platform is designed for agencies and SMBs; larger enterprises requiring deep reporting, custom objects at scale, or complex role-based access may outgrow its capabilities.

Complexity grading

How hard is this migration?

Standard CRM migration. 2 of 8 objects need a mapping; the rest are 1:1.

B

Overall complexity

Standard migration

Derived from compatibility, mapping clarity, API constraints, and data volume across Fieldy and HighLevel.

  • Object compatibility

    B

    2 of 8 objects need a mapping; the rest are 1:1.

  • Field mapping clarity

    C

    Field mapping is derived from defaults — final spec confirmed during the sample migration.

  • Timeline complexity

    B

    8-object category — typical timelines run 2–7 days end-to-end.

  • API constraints

    B

    Fieldy: Not publicly documented..

  • Data volume sensitivity

    B

    Fieldy doesn't expose a bulk API — REST + parallelization used for high-volume runs.

Estimator

Estimate your Fieldy to HighLevel migration cost

Rule-based pricing — no per-record fees, no manual quotes. Migrations over 2M records are scoped individually.

Step 1

What are you migrating?

Pick a category, then your source and destination platforms.

Category

FAQ

Frequently asked questions about Fieldy to HighLevel data migrations

Answers to the questions buyers ask most during Fieldy to HighLevel migration scoping. Not seeing yours? Book a call.

Can't find your answer?

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Book a free 30 minute consultation

Most Fieldy-to-HighLevel migrations complete within 48–72 hours for accounts with under 10,000 records across contacts, companies, and jobs. Accounts exceeding 50,000 records or those with extensive custom properties and invoice history extend to 5–10 days. The longest planning step is creating HighLevel custom fields for Fieldy's custom property catalog and configuring the job-to-opportunity pipeline mapping before data can load securely.

Adjacent paths

Related migrations to explore

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