Migrate from Spark CRM to Odoo CRM

Spark contacts map to Odoo res.partner records of type 'contact'. The email field serves as the unique key for upsert operations. Spark contact owner_id is stored as x_spark_owner_id and matched to res.users by email after the user load step completes.

Spark companies map to Odoo res.partner records of type 'company'. Company contacts in Spark (contacts with a company association) are linked via the contact's partner_id Many2one pointing to the company res.partner. Multi-company contact patterns collapse to the primary company link with additional companies surfaced via partner relations.

Spark deals map to Odoo crm.lead records where type='opportunity'. The deal's pipeline determines the target crm.team, and the deal stage maps to a crm.stage within that team. Deal amount, close date, and probability transfer as is. Owner maps via x_spark_owner_id.

Spark leads map to Odoo crm.lead records where type='lead'. Lead status in Spark maps to Odoo's crm.lead stage sequence. Leads without a deal value or close date remain as leads in Odoo until manually converted to opportunity by a sales rep.

Spark pipelines map to Odoo crm.team records. Each Spark pipeline becomes one crm.team. Stages within the pipeline map to crm.stage records scoped to that team. Stage order and probability percentages transfer value-by-value to maintain forecast accuracy. If a pipeline contains custom stage properties such as temperature or rating, those are preserved as custom fields on the corresponding crm.stage record for reporting continuity.

Spark pipeline stages map to Odoo crm.stage records by pipeline. Stage names map value-by-value, preserving sequence order and probability weights. Stage-entered timestamps in Spark are stored as custom datetime fields on crm.lead for historical stage-transition reporting in Odoo. If a stage includes specific action items or checklists, those details are captured in a custom char field linked to the stage record for future reference.

Spark custom fields on any object require Odoo custom fields created via Settings > Technical > Custom Fields. All custom fields use the x_ field name prefix in Odoo. Field type mapping: text to char, number to float or integer, pick-list to selection, date to date, and multi-select to char with comma separation or relational record.

Spark activity history maps to Odoo mail.message records linked to crm.lead via res_model='crm.lead' and res_id pointing to the lead ID. Activity type (call, email, meeting) sets mail.message.message_type and mail.activity.activity_type_id. Original timestamps and author IDs preserved. Scheduled follow-up tasks create mail.activity records.

Spark owner records map to Odoo res.users. Owners are loaded first in the migration sequence so user IDs are available for foreign-key assignment. Unmatched owners (no Odoo user with matching email) are flagged and assigned to a fallback user specified by the customer before the full migration runs.

Spark file attachments on contacts, companies, and deals are downloaded and re-uploaded to Odoo ir.attachment records. Each attachment is linked to the target crm.lead or res.partner via res_model and res_id. Odoo's file storage path preserves the original filename and content type. Inline images in notes are extracted and stored as separate attachments.

Spark CRM workflows, action rules, and field-change triggers have no Odoo equivalent. They do not transfer. FlitStack AI exports workflow definitions as a text reference document so your Odoo administrator can rebuild equivalent logic using Odoo's Automated Actions, Server Actions, or base.automation modules.

Spark tags on leads and deals map to Odoo crm.tag records linked to crm.lead via the many2many tag_ids field. Tags with the same name are deduplicated during migration so duplicate tags do not proliferate in Odoo. If a tag includes a color or description attribute, we store those as separate custom char fields on the crm.tag record for UI display and filtering.