Migrate from Spark CRM to HighLevel

Spark contacts map 1:1 to HighLevel contacts. Name, email, phone, address, job title, and company link all carry over directly. Spark's contact owner resolves by email match to a HighLevel user. Unmatched owners flag before migration so you can invite them or assign a fallback owner.

Spark companies map to HighLevel companies. Company name, domain/website, address, industry, and employee count migrate as direct field mappings. Industry pick-list values map value-by-value where Spark and HighLevel share a value; non-matching values land in a custom field for manual review.

Spark deals migrate as HighLevel opportunities. Deal name, amount, close date, and owner all map directly. The Spark pipeline name becomes the HighLevel pipeline name, and each Spark deal stage maps to a corresponding HighLevel opportunity stage by position and name. Stage entry timestamps from Spark migrate as custom datetime fields for reporting continuity.

Spark pipelines map to HighLevel pipelines. Each Spark pipeline becomes a separate HighLevel pipeline. If your Spark account uses only one pipeline, a single HighLevel pipeline is created. HighLevel allows multiple pipelines with distinct stage sets—Spark's pipeline-to-pipeline isolation is preserved, but no structural transformation is required.

Spark email threads attached to contacts migrate as HighLevel email activity entries. Each sent or received message appears as a separate activity record linked to the contact, preserving the original timestamp and sender. HighLevel logs these under the contact's activity feed; they are searchable but do not create a threaded inbox view.

Spark tasks map to HighLevel tasks. Task subject, due date, completion status, and assigned user carry over. Open Spark tasks migrate as open HighLevel tasks; completed tasks preserve their completion date. Owner assignment resolves by email match to HighLevel users.

Spark notes attached to contacts, companies, or deals migrate as HighLevel notes on the corresponding record. Note body text, author, and create date are preserved. HighLevel notes display in the record's timeline alongside email activities and tasks.

Spark tags are migrated as HighLevel tags by default, which appear on contact records and can be used for segmentation and workflow triggers. Tags that represent structured data (e.g., a numeric score or a status value) can alternatively map to a HighLevel custom field if you specify the mapping before migration runs.

Spark team members resolve by email to HighLevel users. If a HighLevel user with the matching email does not exist, the record owner defaults to the migration-admin user and a flag is set on the record for manual reassignment. FlitStack delivers a pre-migration owner audit so your team can pre-invite unmatched Spark users before data lands.

Spark custom objects that store structured business data map to HighLevel custom objects. HighLevel requires custom objects to be defined in the UI before import; FlitStack delivers a schema plan specifying the object name, field list, and field types needed so your HighLevel admin creates the object before the migration run. N:N relationships in Spark map to HighLevel custom object associations.

Spark file attachments on contacts, companies, or deals are downloaded and re-uploaded to HighLevel's file storage. Each file re-attaches to its original record. Files larger than HighLevel's upload limit are flagged before migration so you can decide whether to split the file or exclude it.

Spark calendar events linked to contacts migrate as HighLevel appointments. Event title, start/end time, invitees, location, time zone, and any meeting notes carry over. If the Spark event has no linked contact, it migrates to the organizer's HighLevel calendar without a CRM record association, preserving the original timestamp and attendees.