CRM migration
Field-level mapping, validation, and rollback between Kartra and Pipedrive. We move data and schema; workflows are rebuilt natively in Pipedrive.
Kartra
Source
Pipedrive
Destination
Compatibility
9 of 11
objects map 1:1 between Kartra and Pipedrive.
Complexity
BStandard
Timeline
3-5 weeks
Overview
The Kartra-to-Pipedrive migration is a structural pivot from an all-in-one marketing platform to a dedicated sales CRM. Kartra organizes data around Contacts with tag-based segmentation, membership access, and purchase transactions; Pipedrive organizes data around a visual Deal pipeline attached to People and Organizations. The central challenge is that Kartra has no bulk data extraction API — all source data comes via manual CSV exports from the Kartra UI, which limits automation and adds a manual step for accounts over 2,500 contacts. We map Kartra's Contacts and Companies to Pipedrive's People and Organizations, Transactions to Deals, and Tags to Pipedrive's native tag system. Membership access, course enrollment, Sequences, and automation logic do not export from Kartra and cannot be migrated — we deliver a written inventory of these gaps for the customer to rebuild in Pipedrive after 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 Kartra 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.
Kartra
Contact (formerly Lead)
Pipedrive
Person
1:1Kartra Contacts map to Pipedrive People. Standard fields (first_name, last_name, email, phone, address) map directly. We preserve the original Kartra contact creation date as a custom field kartra_created_date__c for audit and reporting. Kartra's GDPR Status and GDPR Status Date fields migrate to Pipedrive's opt_in_status and a custom gdpr_consent_date__c field. We export oldest-to-newest to preserve lead creation order and replay it in Pipedrive.
Kartra
Company
Pipedrive
Organization
1:1If Kartra contacts include a Company field, we map to Pipedrive Organization. The Organization is created before Person import so the org_id lookup is satisfied at insert time. Organizations without a company name in Kartra are created as single-person orgs in Pipedrive to avoid orphan records.
Kartra
Transaction
Pipedrive
Deal
1:1Kartra Transactions map to Pipedrive Deals. Transaction fields map as follows: amount becomes Deal value, product_name becomes Deal title (with transaction_id appended for uniqueness), transaction_date becomes expected_close_date, payment_method becomes a custom field, and transaction status (completed, refunded, pending) becomes Deal status. Kartra transactions without a linked contact are flagged for manual review before import.
Kartra
Subscription
Pipedrive
Deal (recurring)
1:1Kartra Subscription records (active, cancelled, paused) map to Pipedrive Deals with a custom subscription_status__c field. Subscription start date and associated product/membership migrate as custom fields. Note: Kartra does not export subscription revenue MRR or ARR as a computed field; we extract what is available in the CSV and flag the gap.
Kartra
Tag
Pipedrive
Tag
1:1Kartra tags stored as comma-separated strings in the CSV are parsed and split into individual Pipedrive tags. We use Pipedrive's tag creation API to upsert tags before attaching them to People and Deals. Tags that represent behavioral events (form completed, email clicked) without a corresponding record in Pipedrive are preserved as tags but noted as informational — Pipedrive does not have an equivalent behavioral event log.
Kartra
List
Pipedrive
Tag or Person Group
lossyKartra list memberships export as comma-separated values per contact. We split list memberships and create corresponding tags in Pipedrive with a list_ prefix for discoverability. The customer chooses at scoping whether to use Pipedrive tags or to pre-create Person Groups in Pipedrive and map list memberships accordingly.
Kartra
Custom Field
Pipedrive
Custom Field
1:1Kartra's five custom field types (input_field, text_area, drop_down, radio_button, checkbox) map to Pipedrive's text, varchar, int, double, date, datetime, enum, set, and bool types. We read Kartra's field schema during discovery to determine types before creating Pipedrive custom fields. Drop-down and radio_button fields in Kartra map to Pipedrive enum fields with the same picklist values preserved.
Kartra
Owner
Pipedrive
User
1:1Kartra owner email references are matched to Pipedrive Users by email during migration. Owners without a matching Pipedrive User are placed in a reconciliation queue for the customer to provision before Person import. This is a common gap when migrating from Kartra because Kartra team members may not have been set up as Pipedrive users at the destination.
Kartra
Calendar / Appointment
Pipedrive
Activity
1:1Kartra Calendar appointments (booking records) map to Pipedrive Activities. We map calendar name, appointment time, and attendee to a Pipedrive Activity with type=Meeting or type=Call. Historical appointment records require a separate Kartra export and are not included in the standard contact CSV; we flag this and include it in the scope if the customer requests it during discovery.
Kartra
Affiliate
Pipedrive
Custom Field or Organization
lossyKartra affiliate relationships tracked in the API events system map to Pipedrive as custom fields on Person (affiliate_id__c, affiliate_status__c) or as a Partner Organization type if the customer uses Pipedrive's partner management setup. We determine the strategy during scoping based on the customer's affiliate volume and whether they actively manage affiliate relationships in the CRM.
Kartra
GDPR Status
Pipedrive
Opt-in Status
1:1Kartra's GDPR Status field per contact migrates to Pipedrive's opt_in_status flag. GDPR Status Date migrates to a custom consent_date__c field. We preserve original values but recommend the customer verify consent records against their actual legal obligations in the destination jurisdiction, as Pipedrive may interpret consent states differently than Kartra's internal flags.
| Kartra | Pipedrive | Compatibility | |
|---|---|---|---|
| Contact (formerly Lead) | Person1:1 | Fully supported | |
| Company | Organization1:1 | Fully supported | |
| Transaction | Deal1:1 | Fully supported | |
| Subscription | Deal (recurring)1:1 | Fully supported | |
| Tag | Tag1:1 | Fully supported | |
| List | Tag or Person Grouplossy | Fully supported | |
| Custom Field | Custom Field1:1 | Fully supported | |
| Owner | User1:1 | Fully supported | |
| Calendar / Appointment | Activity1:1 | Fully supported | |
| Affiliate | Custom Field or Organizationlossy | Fully supported | |
| GDPR Status | Opt-in Status1:1 | 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.
Kartra gotchas
Behavioral history is absent from Kartra exports unless tags were pre-set up
Contact-based pricing requires pre-migration record audit
No bulk or programmatic API for extraction
Sequences, automation logic, and workflows cannot be exported
GDPR status fields export but require manual review at destination
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
Discovery and CSV extraction planning
We audit the Kartra account to identify all exportable objects: Contacts, Companies (if populated), Transactions, Subscriptions, Tags, Lists, Custom Fields, Calendar appointments, and Affiliates. We also probe the tag taxonomy for any behavioral tags (form completed, webinar registered, membership accessed) that would preserve engagement history. We assess the total contact volume and plan the CSV chunking strategy for accounts over 2,500 contacts. The discovery output is a written migration scope and a Kartra export checklist for the customer to execute in the Kartra UI.
Data extraction and validation
The customer exports all CSV files from the Kartra UI using the export checklist we provide. We receive the CSV files and validate field completeness, row counts, and date ranges. We flag any missing objects or fields that differ from the discovery scope and request supplemental exports. We parse tag and list membership strings into normalized structures and validate that custom field values match the expected format for each Kartra field type. This step is the primary source of timeline risk for accounts with large contact volumes.
Pipedrive schema preparation
We create Pipedrive custom fields to receive Kartra's custom field data, matching each field type from the Kartra schema. We configure Pipedrive tags for tag and list migration, and set up Pipedrive's pipeline stages to mirror the Kartra deal stages or to follow the customer's preferred deal workflow. We create Pipedrive Users for any Kartra owners referenced in the data, or flag missing users for the customer to provision before import. The schema is validated in Pipedrive's test environment before production migration begins.
Record import in dependency order
We run the migration in dependency order: Pipedrive Users (validated before import), Organizations (from Kartra Company data), People (Contacts with org_id resolved), Deals (Transactions and Subscriptions with linked Person and Organization), and Tags (attached to People and Deals after record creation). Each phase emits a row-count reconciliation report. We use Pipedrive's REST API with rate-limit handling and exponential backoff for all inserts. Custom field values, GDPR flags, and tag memberships are attached in the same API call where possible to minimize round-trips.
Cutover and gap documentation
We freeze Kartra writes during cutover and run a final delta migration of any records created or modified after the initial export. We enable Pipedrive as the system of record and validate a random sample of records against the Kartra source for field-level accuracy. We deliver the Sequences and Automation Inventory document to the customer, documenting every Kartra Sequence with its trigger, conditions, actions, and recommended Pipedrive workflow equivalent. We support a three-day hypercare window for reconciliation issues raised by the customer's team.
Automation rebuild handoff
We deliver a written map of every Kartra Sequence and automation with its configuration details, so the customer's Pipedrive admin can rebuild sequences in Pipedrive's workflow builder. We do not rebuild sequences as part of the migration scope. We do not migrate membership or course enrollment data; if the customer requires this data in Pipedrive, it must be manually reconstructed using the Kartra behavioral tags we identified (if any) or via a separate manual export from Kartra. Post-migration admin support is outside standard scope.
Platform deep dives
Kartra
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 Kartra 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
Kartra: Hardcoded ceiling of 20 inbound API calls per second per Kartra App..
Data volume sensitivity
Kartra 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
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FAQ
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