CRM migration

Migrate from Mautic to Odoo CRM

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

Mautic logo

Mautic

Source

Odoo CRM

Destination

Odoo CRM logo

Compatibility

72%

13 of 18

objects map 1:1 between Mautic and Odoo CRM.

Complexity

BStandard

Timeline

4-8 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Moving from Mautic to Odoo CRM is a migration from a contact-centric marketing automation platform to a modular ERP where the CRM is one component of a suite. Mautic organizes data around Contacts and Companies with marketing workflows, dynamic Segments, and point-based scoring. Odoo CRM requires a Lead-to-Opportunity pipeline model where Contacts attach to Accounts, and it has no native equivalent for campaign automation logic. We resolve the contact-to-Lead split using Mautic's lifecycle stage and point values, map Segments to Odoo's filter groups, and transfer engagement history (calls, emails, meetings, tasks, notes) through Odoo's XML-RPC API with batch chunking. We do not migrate Campaigns, Forms, Landing Pages, or marketing automation as code; we deliver a written inventory of these for the customer's admin to rebuild in Odoo Studio or via the Odoo Apps store.

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

Mautic logo

Mautic

What's pushing teams away

  • Upgrading between major versions (4→5→6) is not a simple in-place update; plugins and custom code frequently break silently with no errors logged.
  • MySQL/MariaDB column-size limits and index-per-table restrictions throttle performance at contact counts above 500K, forcing expensive database workarounds.
  • Self-hosting requires dedicated server management, security patching, and cron job maintenance that marketing teams are not equipped to handle.
  • The UI and documentation lag behind feature development, making routine tasks like bulk contact exports unreliable in newer versions (v6.0.0 CSV exports queue but do not reliably email).
  • Enterprise support tiers at $20K–$30K/year are priced similarly to SaaS alternatives, removing the cost advantage for organizations that need professional SLA coverage.

Choosing

Odoo CRM logo

Odoo CRM

What's pulling them in

  • Teams choose Odoo CRM for its modular architecture — one base install with one-click app additions means they can adopt CRM alone and add accounting, inventory, or sales later as the business grows.
  • Small businesses pick Odoo because the Community edition is free and open-source, with no per-user or contact limits, allowing full evaluation before committing to a paid Enterprise tier.
  • The drag-and-drop Kanban pipeline and AI lead scoring are highlighted across G2 reviews as concrete features that make lead management faster and more visual than spreadsheet-based workflows.
  • Odoo's native integration with email, live chat, SMS, VoIP, and WhatsApp means inbound leads from multiple channels feed into a single pipeline without third-party middleware.
  • Companies in retail, supply chain, and construction value that Odoo's CRM module shares the same PostgreSQL database and UI as its ERP modules, eliminating data silos between sales and operations.

Object mapping

How Mautic objects map to Odoo CRM

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

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

Mautic

Contact

maps to

Odoo CRM

Lead

1:1
Fully supported

Mautic Contacts migrate to Odoo CRM Lead. We use Mautic's lifecycle stage, point value, and lead status properties to determine the initial Odoo Lead stage. The email address serves as the primary key for deduplication. If the Mautic contact has an associated Company with a revenue or industry field, those values map to corresponding Lead fields. We preserve the original Mautic contact ID in a custom field mautic_id__c on the Lead for audit and reconciliation.

Mautic

Contact

maps to

Odoo CRM

Contact (secondary)

lossy
Fully supported

Mautic Contacts that represent existing customers (lifecycle stage = customer or evangelist) can optionally map to Odoo CRM Contact records attached to a Company rather than to Lead. The customer chooses during scoping based on whether they want to maintain a distinction between prospect Leads and active customer Contacts in Odoo. We create a custom field mautic_lifecycle_stage__c on both Lead and Contact to preserve the original classification.

Mautic

Company

maps to

Odoo CRM

Company

1:1
Fully supported

Mautic Company records map directly to Odoo CRM Company. The company domain field maps to the Website field in Odoo, and domain-based deduplication is applied during import. Odoo Company supports address, industry classification, annual revenue, and number of employees fields that map from their Mautic equivalents. We create the Company record first in each batch so that the Contact import can satisfy any contact-to-company association by name or domain lookup.

Mautic

Deal

maps to

Odoo CRM

Opportunity

1:1
Fully supported

Mautic Deals migrate to Odoo CRM Opportunity. The deal stage maps to an Odoo Stage within the configured pipeline. The associated contact and company resolve to the migrated Lead/Contact and Company records. Deal amount, expected close date, and probability migrate to Opportunity amount, date_closed, and probability fields. We configure the Odoo CRM pipeline stages before migration so that stage names and probabilities align with the customer's existing Mautic deal workflow.

Mautic

Deal Stage

maps to

Odoo CRM

Opportunity Stage

lossy
Fully supported

Mautic pipeline stages map to Odoo CRM Stage configurations within the Opportunity pipeline. Each Mautic pipeline becomes a separate Odoo team or sales channel with its own stage sequence. Stage probabilities migrate from Mautic to Odoo with rounding to Odoo's percentage format. Stage color coding and sequence order transfer to Odoo's Kanban view configuration.

Mautic

Segment

maps to

Odoo CRM

Filter Group

lossy
Fully supported

Mautic Segments (dynamic contact lists filtered by field values, tags, or behavioral criteria) are not replicated as static lists in Odoo. We export the segment filter definition and recreate it in Odoo as saved filter groups on the Lead and Contact list views. The segment membership itself is recalculated at the destination based on the same criteria. We deliver a filter specification document listing each segment's conditions, operators, and field references for manual Odoo filter recreation.

Mautic

Campaign

maps to

Odoo CRM

CRM Team + Activity Plan (documentation)

1:1
Fully supported

Mautic Campaigns are marketing automation workflows with triggers, conditions, actions, and delays. Odoo CRM has no native campaign automation equivalent. We export campaign definitions, step sequences, and contact membership counts. The customer receives a written campaign specification document describing each campaign's trigger logic, step actions, timing, and associated assets. Odoo CRM sales teams are expected to replicate campaign logic manually or via Odoo Studio automations post-migration.

Mautic

Form

maps to

Odoo CRM

Form Builder configuration (documentation)

1:1
Fully supported

Mautic Forms collect contact data and trigger campaign actions on submission. We export form field configurations, field types, validation rules, and submission mappings. Odoo Website and Contact modules have a form builder but no native campaign-triggered follow-up logic. We deliver a form field mapping document and recommend rebuilding forms in Odoo Website or a compatible form app. Webhook-based post-submission actions do not migrate and must be reconstructed in Odoo Studio or via a third-party automation app.

Mautic

Stage

maps to

Odoo CRM

Lead/Contact Stage

1:1
Fully supported

Mautic Stages define contact lifecycle positions (Lead, MQL, SQL, Customer). We map stage names directly to Odoo CRM Lead stages and, where applicable, to Contact tags. If the customer uses Mautic stages as a lead scoring mechanism, we combine stage information with point values to assign initial Odoo Lead status and create a custom field for the original stage name.

Mautic

Points

maps to

Odoo CRM

Lead Score custom field or Tag

lossy
Fully supported

Mautic's point system scores contacts based on actions. Point values migrate as a custom integer field mautic_points__c on Lead and Contact. If the customer uses point thresholds for routing or prioritization, we recommend converting those thresholds into Odoo Lead stage assignments or automated stage-update actions built in Odoo Studio. Point-based scoring logic does not have a native Odoo equivalent and requires manual reconstruction.

Mautic

Tag

maps to

Odoo CRM

Tag

1:1
Fully supported

Mautic Tags are flat string labels applied to contacts and other objects. All tags export and reapply during migration as Odoo CRM tags on the corresponding Lead or Contact record. Tag-based segmentation is preserved through the segment-to-filter translation described above. Tag counts per contact are maintained as the number of applied tags in Odoo.

Mautic

Category

maps to

Odoo CRM

Tag or Team

lossy
Fully supported

Mautic Categories group assets, campaigns, emails, and contacts into hierarchical folders. We export the category hierarchy and reassign related objects to Odoo tags or CRM teams depending on whether the category represents a functional grouping (marketing vs sales) or a content classification. The customer chooses the category-to-tag or category-to-team mapping during scoping.

Mautic

Asset

maps to

Odoo CRM

Document

1:1
Fully supported

Mautic Assets are downloadable files (PDFs, guides, media) with metadata. We export asset metadata (name, URL path, MIME type, download count) and replicate the file storage structure in Odoo Documents or as attachments on the related Lead, Contact, or Company record. Large binary files migrate via the Odoo XML-RPC file upload API. Asset download counts and related campaign associations are preserved in custom fields or notes.

Mautic

Custom Object

maps to

Odoo CRM

Custom Record Type (Studio)

1:1
Fully supported

Mautic Custom Objects extend the data model beyond standard contacts and companies. We export custom object definitions and data, then recreate equivalent record types in Odoo using Odoo Studio, including all custom fields, field types, and lookup relationships to standard objects (Lead, Contact, Company, Opportunity). Relationship data between custom objects in Mautic is accessed via the junction tables in MySQL/MariaDB because the Mautic Relationships API is non-functional, and the relationship records are mapped to Odoo's many2many or one2many fields through the XML-RPC API.

Mautic

Engagement: Email

maps to

Odoo CRM

Message

1:1
Fully supported

Mautic email engagements (sent, opened, clicked, bounced) migrate to Odoo CRM Message records attached to the target Lead or Contact. The WhoId links the message to the Lead; Subject, Body, and Date transfer to corresponding Message fields. We preserve the engagement type (sent, opened, clicked) as a custom field because Odoo Message does not natively track open and click events. Activity timeline ordering is preserved by setting Message Date to the original Mautic timestamp.

Mautic

Engagement: Call

maps to

Odoo CRM

Phone Call Log

1:1
Fully supported

Mautic call engagements map to Odoo CRM call logs attached to the target Lead or Contact. Call duration, disposition, and recording URL (if stored in Mautic) transfer to custom fields on the activity record. The WhoId on the activity points to the migrated Lead. Call timestamp migrates as the activity date, preserving the chronological activity timeline.

Mautic

Engagement: Meeting

maps to

Odoo CRM

Calendar Event

1:1
Fully supported

Mautic meeting engagements map to Odoo Calendar Event records. Start time, end time, location, and attendee information transfer to the corresponding Event fields. Attendee mapping links to EventPartner records pointing to the migrated Lead or Contact. Meeting subject and body migrate as the event description.

Mautic

Engagement: Note / Task

maps to

Odoo CRM

Note / Task

1:1
Fully supported

Mautic Notes migrate to Odoo CRM Notes attached to the relevant Lead, Contact, Company, or Opportunity. Note body transfers as plain text. Mautic Task engagements (internal tasks with owners and due dates) migrate to Odoo CRM Tasks linked to the owner by email resolution. Task status and priority migrate to the corresponding Odoo fields.

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.

Mautic logo

Mautic gotchas

High

Mautic v6 CSV export silently fails to deliver files

High

Mautic 4 to 5 upgrade breaks plugins without warning

Medium

MySQL/MariaDB index limits throttle large contact databases

Medium

Custom Object Relationships API is non-functional

Medium

Mautic 5 to 6 migration logs no errors on failure

Odoo CRM logo

Odoo CRM gotchas

High

Odoo.sh version gating blocks assisted migrations from trial

High

Enterprise modules fail to install on Community after database restore

Medium

Custom module view inheritance breaks between Odoo major versions

Medium

Custom fields risk losing their application context on Community

Low

API access for Community is gated behind the Custom Plan

Pair-specific challenges

  • Mautic v6 CSV export silently fails with no error output

    Mautic 6.0.0 CSV exports queue the file for processing but never deliver it via email and write no errors to Apache logs or Mautic's internal log. Organizations relying on the built-in export for data extraction discover the failure only when expected files do not arrive. We handle this by bypassing the built-in export entirely: we pull contact, company, and custom object data directly from the MySQL/MariaDB database using authenticated read access, or we call the REST API in batched requests with pagination. This ensures a reliable extraction regardless of the export queue failure.

  • Contact-to-Lead split requires an upfront design decision

    Mautic uses a single contact-centric model where every record is a Contact regardless of qualification level. Odoo CRM separates unqualified prospects into Leads and qualified buyers into Contacts attached to Companies. There is no automated answer to this split. We define the split rule during scoping based on Mautic lifecycle stage, point values, and associated campaign membership, then apply it as a transform during migration. Contacts that map to Lead land in the Odoo pipeline; those that map to Contact get attached to the corresponding Company. Skipping this step produces orphaned records in Odoo with no pipeline assignment.

  • Custom Object Relationships API is non-functional

    Mautic's Custom Objects support relationships between object types, but the REST API endpoint for creating relationship records has been documented as broken since 2022 community reports. Organizations with relationship data between custom object types cannot migrate those relationships through the API. We handle this by accessing the relationships data directly through the MySQL/MariaDB junction tables, mapping the junction table records (object_id_a, object_id_b, relationship_type) to Odoo's many2many or one2many fields via the XML-RPC API.

  • Odoo CRM has no native campaign automation equivalent

    Mautic's campaign builder (triggers, conditions, delays, A/B tests, lead scoring actions) has no direct Odoo CRM equivalent. Odoo CRM manages pipeline stages and opportunities but does not run automated marketing sequences. We do not migrate campaign logic as executable automation. We deliver a written campaign specification document listing each campaign's trigger conditions, step sequence, timing, associated forms, and assets. The customer's admin rebuilds campaign logic manually in Odoo Studio, via a third-party automation app from the Odoo Apps store, or accepts that pipeline follow-up automation will be managed manually or through Odoo's opportunity-based action buttons.

  • Odoo XML-RPC API requires different batch handling than REST

    Odoo exposes data through an XML-RPC API with session-based authentication, different from the REST endpoints that most CRM migration tools target. Batch operations in Odoo's XML-RPC API have size limits per request, and rate limiting is enforced per database session rather than per API key. We handle this by using Odoo's XML-RPC batch create and write methods with configurable chunk sizes, session rotation to avoid lock contention, and retry logic with exponential backoff on timeout errors. Direct database writes to Odoo's PostgreSQL schema are not used as a primary path because Odoo relies on the ORM layer for computed fields, ondelete cascade rules, and audit logging.

Migration approach

Six steps for a successful Mautic to Odoo CRM data migration

  1. Discovery and source audit

    We audit the source Mautic instance across version (4, 5, or 6), hosting model (self-hosted or Acquia Cloud), database engine (MySQL or MariaDB), and all active object types. We profile the contact schema including standard fields, custom contact fields, and any custom object definitions. We document all active segments with their filter definitions, active campaigns with their step logic, engagement history volume by type (email, call, meeting, note, task), and any custom field type mismatches. We pair this with an Odoo edition review: Odoo Community (free, self-hosted) covers most migrations; Odoo Online ($24/app/user/month) covers cloud-hosted destinations. The discovery output is a written migration scope and Odoo edition recommendation.

  2. Contact-to-Lead split design and schema configuration

    We define the split rule mapping Mautic lifecycle stages and point values to Odoo Lead stages, Contact records, or a hybrid model based on the customer's sales process. We configure the Odoo CRM pipeline stages, team assignments, tag taxonomy, and any custom Lead or Contact fields before migration begins. If custom objects exist, we create the equivalent record types in Odoo Studio including all fields and relationship definitions. Schema configuration is validated in an Odoo staging database before production migration.

  3. Direct database extraction bypassing Mautic v6 CSV export

    We extract all object data directly from the Mautic MySQL/MariaDB database rather than relying on the built-in CSV export. We connect with read-only authenticated access, extract contacts, companies, deals, segments, custom objects, and junction table relationship records in batched queries, and validate record counts against API-based counts. For Mautic v6, this is the only reliable extraction path. We generate a data quality report identifying duplicate emails, orphaned companies, blank required fields, and records with no associated owner before transformation begins.

  4. Transformation and split application

    We apply the contact-to-Lead split as a transform step using the scoping-defined lifecycle stage and point threshold rules. Company records are normalized for domain-based deduplication. Segment filter definitions are translated into Odoo saved filter specifications. Engagement history records are transformed to Odoo Message, Calendar Event, and Task format with the original timestamps preserved for chronological ordering. We produce a transformation report showing record counts per object before and after the split, and flag any records that cannot be assigned a split outcome for customer review.

  5. Sandbox migration and owner reconciliation

    We run a full migration into an Odoo staging database using production-like data volumes. The customer reconciles record counts (Leads in, Contacts in, Companies in, Opportunities in, Activities in), spot-checks 25-50 random records against the Mautic source, and validates that the contact-to-Lead split produced the expected distribution. We also reconcile Mautic owners by email against Odoo Users, flagging any owner without a matching Odoo User for the customer's admin to provision before production migration. Any mapping corrections happen at this stage.

  6. Production migration in dependency order

    We run production migration in record dependency order: Companies first, then Leads and Contacts with CompanyId resolved, followed by Opportunities with Lead/Contact and Company lookups resolved, then engagement history via Odoo XML-RPC batch methods. Custom objects import last because they often have lookups to standard objects. We use session rotation to handle XML-RPC rate limits and chunk activity records into batches of 100-500 per request depending on record size. Each phase emits a row-count reconciliation report before the next phase begins.

  7. Cutover, validation, and campaign handoff

    We freeze writes to Mautic during the cutover window, run a final delta migration of any records modified during migration, then switch the customer's CRM system of record to Odoo. We deliver the campaign specification document, segment filter definitions, and lead scoring threshold recommendations to the customer's admin team. We support a one-week hypercare window for reconciliation issues raised by the sales team. We do not rebuild Mautic campaigns as Odoo Studio automations inside the migration scope; that work is documented for the customer's admin or an Odoo implementation partner.

Platform deep dives

Context on both ends of the pair

Mautic logo

Mautic

Source

Strengths

  • Zero per-contact licensing cost with the self-hosted open-source core product.
  • Full source code access enables unlimited customization without vendor dependency.
  • Complete data ownership and infrastructure control for compliance-sensitive organizations.
  • Multi-channel support including email, SMS, mobile push, and web notifications in one platform.
  • Active community and partner ecosystem with implementation support available.

Weaknesses

  • Self-hosted deployment requires ongoing server administration, security updates, and infrastructure costs.
  • MySQL/MariaDB column-size and index-per-table limits constrain large-scale contact databases.
  • Documentation and feature parity across versions is inconsistent, especially for new major releases.
  • CSV export reliability degrades in Mautic v6, and queued export jobs can fail silently without logging errors.
  • Upgrade paths between major versions frequently break third-party plugins and custom code.
Odoo CRM logo

Odoo CRM

Destination

Strengths

  • Modular open-source architecture lets teams start with CRM and add ERP apps as needs grow, all sharing one PostgreSQL database.
  • Free Community edition with no contact limits and full source code access means zero licensing cost for evaluation and small deployments.
  • Drag-and-drop Kanban pipeline with AI lead scoring gives a visual, prioritized view of the sales funnel without requiring custom configuration.
  • Native integrations with email, live chat, SMS, VoIP, WhatsApp, and social media feed all inbound leads into a single unified inbox.
  • Active Odoo Community Association (OCA) maintains dozens of community-maintained modules on GitHub for extended functionality.

Weaknesses

  • Gmail and email integration reliability is a recurring complaint — threads drop and conversations scatter across inboxes, disrupting sales team workflows.
  • Enterprise edition pricing stacks quickly: multiple apps at per-user rates ($25–$50/user/month) plus Odoo.sh hosting costs more than many SMBs anticipate.
  • Setup and configuration complexity increases significantly once custom fields, automation rules, and multiple installed modules are in play.
  • Odoo.sh trial databases run on a version (e.g., 18.3) that is not directly migratable to Odoo.sh, blocking the assisted migration path Odoo advertises.
  • Version upgrades between major Odoo releases (e.g., 17→18) frequently break custom module view definitions and XPath expressions, requiring manual remediation.

Complexity grading

How hard is this migration?

Standard CRM migration. 1 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 Mautic and Odoo CRM.

  • Object compatibility

    B

    1 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

    Mautic: Not publicly documented — enforced at the server level, not within Mautic software.

  • Data volume sensitivity

    B

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

Estimator

Estimate your Mautic to Odoo CRM 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 Mautic to Odoo CRM data migrations

Answers to the questions buyers ask most during Mautic to Odoo CRM migration scoping. Not seeing yours? Book a call.

Can't find your answer?

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Most migrations land between four and eight weeks for accounts under 50,000 Contacts with no custom objects and basic segmentation. Migrations with custom objects, large engagement histories (over 200,000 activity records), or multi-company Odoo setups move to eight to fourteen weeks because of direct database extraction, junction table mapping, and Odoo Studio custom object configuration. Discovery and scoping adds one to two weeks to either estimate regardless of data volume.

Adjacent paths

Related migrations to explore

Ready when you are

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