CRM migration

Migrate from Brokerkit to Pipedrive

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

Brokerkit logo

Brokerkit

Source

Pipedrive

Destination

Pipedrive logo

Compatibility

100%

12 of 12

objects map 1:1 between Brokerkit and Pipedrive.

Complexity

BStandard

Timeline

24–72 hours

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Brokerkit organizes data around real estate agents, brokerages, recruitment pipelines, and transaction milestones — tracking where each agent sits in onboarding, active, or retention status. Pipedrive models the same contacts as Persons linked to Organizations, and tracks progress through customizable Deal pipelines with Stages, Activities, and Notes. The migration carries Brokerkit's agent profiles, brokerage associations, transaction records, custom fields, and activity history into Pipedrive's object graph. The main translation work is mapping Brokerkit's recruitment-stage values to Pipedrive's Stage pick-list per pipeline, resolving Brokerkit owner emails to Pipedrive user accounts, and deciding how Brokerkit's transaction pipeline stages map to Pipedrive stage names. FlitStack AI uses scoped read access against Brokerkit's API and Pipedrive's Bulk API to move records in the correct dependency order — Organizations first, then Persons, then Deals, then Activities. Automation workflows (recruitment sequences, drip campaigns) do not migrate and must be rebuilt in Pipedrive's automation builder after migration.

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

Brokerkit logo

Brokerkit

What's pushing teams away

  • The platform lacks deep customization options, leaving brokerages with non-standard recruiting workflows forced to work around the tool's opinionated structure.
  • Canadian market integrations do not exist, and no native equivalents to US tools like RealMetrix means international teams have no path forward within the platform.
  • Reporting and analytics fall short for teams that need pipeline attribution broken down beyond basic source-level tracking.

Choosing

Pipedrive logo

Pipedrive

What's pulling them in

  • Clean drag-and-drop pipeline interface with minimal learning curve, making it approachable for small sales teams without dedicated CRM admins.
  • Visual deal tracking keeps reps focused on next actions — activities, calls, and follow-up tasks surface directly in the pipeline view.
  • Strong integrations via Zapier and native marketplace apps let teams wire Pipedrive into Calendly, ActiveCampaign, and similar sales-stack tools.
  • Mobile apps for iOS and Android keep field reps connected to deals, contacts, and tasks without a desktop session.
  • Reputation and review volume — over 3,000 verified reviews across G2 and Capterra — signal reliability for teams evaluating CRM options.

Object mapping

How Brokerkit objects map to Pipedrive

Each row shows how a Brokerkit 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.

Brokerkit

Agent / Contact

maps to

Pipedrive

Person

1:1
Fully supported

Brokerkit's agent profile maps directly to Pipedrive's Person object. Name, email, phone, address, and job title fields translate field-by-field with no transformation logic required. Brokerkit agent status (Active, Inactive, Prospect) is preserved as a custom pick-list on the Person record in Pipedrive, ensuring that agent lifecycle information remains queryable after migration.

Brokerkit

Brokerage / Team

maps to

Pipedrive

Organization

1:1
Fully supported

Brokerkit's brokerage entity maps to Pipedrive's Organization object. Brokerage name, website, industry, and address fields map directly using the same data types. Multi-office brokerages with parent-child relationships translate via Organization's parent_id field in Pipedrive, preserving the hierarchical structure. The parent Organization must be migrated first to resolve circular reference issues during the data load.

Brokerkit

Agent–Brokerage Association

maps to

Pipedrive

Person–Organization Link

1:1
Fully supported

Brokerkit's agent-to-brokerage many-to-one relationship maps to Pipedrive's Person.organization_id lookup. Each Brokerkit agent has one primary brokerage assignment that becomes the organization_id on the Person record. Secondary brokerage associations that exist in Brokerkit are preserved as custom fields on the Person record, allowing teams to maintain a complete brokerage association history without data loss.

Brokerkit

Transaction / Deal

maps to

Pipedrive

Deal

1:1
Fully supported

Brokerkit's real estate transaction records map to Pipedrive's Deal object. Transaction status, close date, commission amount, and agent assignment all translate to standard Pipedrive Deal fields. Brokerkit's transaction ID is stored as Source_System_ID__c on the Pipedrive Deal for traceability back to the original Brokerkit record, enabling audit trails and cross-system reporting after migration completes.

Brokerkit

Recruitment Pipeline

maps to

Pipedrive

Pipeline + Stage

1:1
Fully supported

Brokerkit's recruitment pipeline stages (Applied, Interviewing, Offered, Hired, Active, Retained) map to Pipedrive Pipeline stages. Each Brokerkit recruitment pipeline becomes one Pipedrive Pipeline with ordered stages representing the agent journey. Stage probability values are assigned per stage name during migration configuration, and stage-entered timestamps are preserved as custom datetime fields on the Deal for historical reporting.

Brokerkit

Transaction Pipeline

maps to

Pipedrive

Pipeline + Stage

1:1
Fully supported

Brokerkit's transaction pipeline stages (Pre-Market, Listed, Under Contract, Pending, Closed Won, Closed Lost) map to a separate Pipedrive Pipeline. Each stage's success probability is set during Pipedrive pipeline configuration. Stage-entered timestamps are preserved as custom datetime fields on the Deal.

Brokerkit

Activity / Follow-up

maps to

Pipedrive

Activity

1:1
Fully supported

Brokerkit's recruiting activity log (calls, emails, notes, tasks) maps to Pipedrive Activities. Each activity type maps to Pipedrive's activity_type field (call, email, meeting, task). Original timestamps, owners, and linked agent or deal references are preserved in the Pipedrive activity record, maintaining the full activity history for each agent and transaction throughout the migration.

Brokerkit

Note / Comment

maps to

Pipedrive

Note

1:1
Fully supported

Brokerkit's notes on agents, transactions, and brokerages migrate to Pipedrive Notes. Notes are attached to the corresponding Person, Organization, or Deal record based on the entity they reference in Brokerkit. Rich-text formatting from Brokerkit is preserved as plain text in Pipedrive's Note object, ensuring that note content remains readable even if advanced formatting is simplified during the migration.

Brokerkit

Custom Field (Agent)

maps to

Pipedrive

Person Custom Field

1:1
Fully supported

Brokerkit custom fields on agent profiles that have no direct Pipedrive equivalent (e.g., license number, MLS ID, referral source) are created as Pipedrive custom fields on the Person object using the matching field type (text, numerical, single option, etc.). Pipeline-specific fields are scoped to the relevant Pipedrive pipeline.

Brokerkit

Custom Field (Transaction)

maps to

Pipedrive

Deal Custom Field

1:1
Fully supported

Brokerkit custom fields on transaction records (e.g., property address, listing type, commission split) migrate as Pipedrive custom fields on the Deal object. Date and monetary field types from Brokerkit map directly to Pipedrive's date and monetary custom field types, maintaining the original data precision. Pipeline-specific custom fields are scoped to the relevant Pipedrive pipeline during configuration.

Brokerkit

Tag / Label

maps to

Pipedrive

Label

1:1
Fully supported

Brokerkit tags on agents and transactions map to Pipedrive Labels. Labels exist independently per entity type in Pipedrive (Person Labels, Organization Labels, Deal Labels), so agent tags land in the Person Labels section while transaction tags appear in Deal Labels. Labels are created automatically during migration with the same color-coding applied where Pipedrive's label color field supports it.

Brokerkit

Owner / User

maps to

Pipedrive

User

1:1
Fully supported

Brokerkit users are matched to Pipedrive users by email address to preserve ownership assignments during migration. Unmatched Brokerkit owners are flagged before migration begins — these users are either invited to create Pipedrive accounts or assigned to a fallback Pipedrive user. No record lands in Pipedrive without a valid OwnerId, ensuring that all migrated data maintains proper access controls and accountability.

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.

Brokerkit logo

Brokerkit gotchas

High

CSV exports truncate long text fields

High

No public API means migration tooling is limited

Medium

Plan tier limits restrict what data exists

Medium

Integration connections do not transfer on migration

Pipedrive logo

Pipedrive gotchas

High

Custom field hash keys differ per account

High

Export access gated by visibility groups

Medium

Token-based API rate limits since December 2024

Medium

Sequences and Automations not exposed via REST API

Low

Cost escalates via workflow caps and add-ons

Pair-specific challenges

  • Brokerkit pipeline stages have no direct Pipedrive equivalent — stage value mapping is manual

    Brokerkit's recruitment and transaction pipelines use custom stage names that don't exist in Pipedrive by default. Pipedrive requires you to create a Pipeline first, then add Stages within that pipeline with explicit names, probabilities, and ordering. FlitStack AI cannot auto-create Pipedrive pipelines without a mapping plan — we deliver a Stage Mapping Worksheet that maps each Brokerkit stage name to a target Pipedrive Stage name and probability value. Pipedrive's stage_id on the Deal record then uses that mapping. Without this step, Deals land in Pipedrive with no stage assignment. The mapping worksheet must be approved before the migration validation run commits.

  • Custom field API keys in Pipedrive are 40-character hashes, not field names

    Pipedrive's API represents custom fields with auto-generated 40-character hash keys (e.g., df8b3c1a2e7f4d9b0c3e5f2a1d8b7c9e3f4a2d6b) rather than readable field names. When writing migration scripts against Pipedrive's API v2, you must first create the custom field via the Pipedrive UI or API to retrieve its hash key, then use that hash as the field identifier in subsequent record creates. Brokerkit custom fields therefore require a two-step setup: pre-create them in Pipedrive to capture hash keys, then reference those keys during the data load. FlitStack AI handles this by creating fields in Pipedrive first and storing the returned keys for the migration run.

  • Brokerkit's agent-to-brokerage model is many-to-one; Pipedrive Persons have a single primary Organization

    Brokerkit allows an agent to be associated with multiple brokerages simultaneously — a common pattern for agents holding licenses with several firms. Pipedrive's Person object has one primary organization_id lookup, with additional organization associations not natively supported. FlitStack AI migrates the most-recently-active brokerage as the primary organization_id and surfaces secondary brokerage associations as a custom multi-select text field (Secondary_Brokerages__c) on the Person record. Your Pipedrive admin can use this field to build filtering views or link records manually.

  • Pipedrive's token-based API rate limits require batch throttling

    Pipedrive introduced token-based API rate limits in December 2024 with per-token request quotas that vary by Pipedrive plan. Bulk data migration from Brokerkit — especially with 25,000+ Person records and historical Activities — can trigger rate limit 429 responses if not throttled. FlitStack AI implements exponential backoff with batch sizing of 50 records per API call and respects Pipedrive's Retry-After headers. Migration run times for large datasets account for rate-limit throttling delays, which can add 2–4 hours to the expected clock time for datasets exceeding 50,000 records.

  • Brokerkit automation sequences (recruitment drips, follow-up campaigns) do not migrate

    Brokerkit sequences — automated multi-step email and task campaigns triggered by recruitment stage transitions — are automation logic stored in Brokerkit's workflow engine. Pipedrive's automation builder (available on Advanced plan and above) supports condition-based triggers and actions but does not import Brokerkit sequence definitions. FlitStack AI does not migrate automation logic. We export your Brokerkit sequence configurations as a reference document (JSON export of trigger conditions, step actions, and delays) that your Pipedrive admin can use to rebuild equivalent automations in Pipedrive's automation editor.

Migration approach

Six steps for a successful Brokerkit to Pipedrive data migration

  1. Audit Brokerkit data and build the mapping plan

    FlitStack AI extracts a full data inventory from Brokerkit — agent profiles, brokerage records, transactions, activities, notes, and all custom fields. We cross-reference this against Pipedrive's standard field inventory to identify which fields map directly, which require custom field creation, and which Brokerkit fields have no Pipedrive equivalent. We deliver a Data Mapping Workbook that lists every field, its mapping type, and any transformation required. You approve the mapping plan before any data moves.

  2. Create Pipedrive schema: pipelines, stages, and custom fields

    Before migrating records, FlitStack AI creates the Pipedrive pipelines and stages needed to receive Brokerkit data. This includes setting up recruitment and transaction Pipedrive Pipelines, defining Stage names and probabilities, and pre-creating custom fields to capture Pipedrive's hash-key field identifiers. Pipedrive users are also verified against Brokerkit owner emails so the owner resolution mapping is ready before records land. This schema setup step ensures that every field and relationship has a target before any data movement begins, preventing the need for retroactive schema changes mid-migration.

  3. Migrate Organizations and Persons first, then Deals

    Pipedrive requires Organizations to exist before Persons can be linked via organization_id, and Persons to exist before Deals can reference person_id. FlitStack AI sequences the migration in dependency order: first Organizations (brokerages), then Persons (agents), then Deals (transactions). Activities and Notes attach after their parent records exist. This sequencing prevents orphaned records and broken relationship links that occur when deals are migrated before the people associated with them.

  4. Run a sample migration with field-level diff and reconciliation report

    FlitStack AI migrates a representative sample — typically 200–500 records spanning agents, brokerages, transactions, and activities — before the full run. We generate a field-level diff comparing source values in Brokerkit against destination values in Pipedrive. The reconciliation report surfaces any fields where values differ, custom fields that failed to write, and Deals that landed without a stage assignment. You review the report and approve the full migration before it commits.

  5. Execute full migration with delta-pickup and rollback window

    The full migration runs against Pipedrive's API in throttled batches. A delta-pickup window of 24–48 hours after the primary run captures any records modified in Brokerkit during cutover. FlitStack AI generates a complete audit log of every record created or updated. If reconciliation reveals a data integrity issue, one-click rollback reverts all migrated records from Pipedrive. After rollback window closes, the Pipedrive instance is your live system with Brokerkit in read-only mode for reference.

Platform deep dives

Context on both ends of the pair

Brokerkit logo

Brokerkit

Source

Strengths

  • Tiered plans scale from solo broker to 10-seat brokerage with predictable per-user pricing.
  • Built-in SMS and email follow-up sequences without requiring a separate engagement platform.
  • Multi-admin account support on Core and Expansion tiers enables office manager delegation.
  • Strong customer support reputation with responsive ticket resolution and webinar-based onboarding resources.

Weaknesses

  • No public API documentation means migration relies on CSV exports, which can truncate long text fields.
  • Canadian market has no integrations or localization, making the platform US-only for practical purposes.
  • Limited customization compared to general-purpose CRMs like HubSpot or Follow Up Boss.
Pipedrive logo

Pipedrive

Destination

Strengths

  • Intuitive drag-and-drop pipeline that sales reps actually use without resistance or training overhead.
  • Per-seat unlimited-deals model on all tiers — reps cannot be blocked from logging activity.
  • Active marketplace with 400+ integrations and a documented REST API with OpenAPI 3 specs.
  • Mobile apps with offline access, call logging, and calendar sync keep field teams operational.
  • Strong focus on sales activity tracking — next-action reminders and follow-up scheduling are first-class features.

Weaknesses

  • No custom objects — teams needing non-standard data structures must work around the four standard entity types.
  • Workflow automation limits by tier (30, 60, 90 active workflows) force upgrades as processes grow.
  • No free permanent plan — teams evaluating fit must commit to a trial without a freemium option.
  • Limited advanced reporting and custom dashboard capabilities compared to HubSpot or Salesforce.
  • Export permissions are gated by visibility groups, meaning data scoping must account for who can see what before migration.

Complexity grading

How hard is this migration?

Standard CRM migration. 3 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 Brokerkit and Pipedrive.

  • Object compatibility

    B

    3 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

    Brokerkit: Not publicly documented — confirm with Brokerkit support during scoping..

  • Data volume sensitivity

    B

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

Estimator

Estimate your Brokerkit to Pipedrive 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 Brokerkit to Pipedrive data migrations

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

Can't find your answer?

Walk through your Brokerkit to Pipedrive migration with a real engineer — 30 minutes, free, written quote within 24 hours.

Book a free 30 minute consultation

Most Brokerkit-to-Pipedrive migrations complete in 24–72 hours of clock time for under 25,000 records. Larger datasets with 100,000+ records or multi-pipeline setups (recruitment plus transaction pipelines per brokerage) extend to 5–10 days. The longest planning step is stage mapping — defining how each Brokerkit pipeline stage name translates to a Pipedrive Stage within a named Pipeline. That planning typically takes 1–3 business days and must be completed before migration validation runs.

Adjacent paths

Related migrations to explore

Ready when you are

Move from Brokerkit.
Land in Pipedrive, intact.

Tell us record counts and timeline. We'll come back with a written quote inside 1 business day — no commitment, no sales pitch.

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