CRM migration
Field-level mapping, validation, and rollback between Spark CRM and HubSpot. We move data and schema; workflows are rebuilt natively in HubSpot.
Spark CRM
Source
HubSpot
Destination
Compatibility
12 of 12
objects map 1:1 between Spark CRM and HubSpot.
Complexity
BStandard
Timeline
24–72 hours
Overview
Spark CRM targets small teams that need a lightweight contact and deal manager with email integration. HubSpot's data model uses contacts and companies as first-class objects with a lifecycle_stage property on contacts, multiple deal pipelines with stage pick-lists, and an associations graph for linking contacts to companies and deals. FlitStack AI extracts Spark CRM data via API, maps standard fields directly (firstname → firstname, email → email), resolves Spark owner records to HubSpot users by email match, and handles Spark's custom field expansions (CustomFieldsRaw / CustomFieldsExpanded) by creating HubSpot custom properties with the appropriate data type. Deals migrate as HubSpot deals with pipeline and stage mapped; Spark multi-contact deal associations become HubSpot deal-contact associations. Workflows, sequences, and automation logic do not transfer — FlitStack exports those definitions as a rebuild reference for your HubSpot admin. The migration runs in read-only access to Spark CRM, so your team keeps working throughout, with a delta-pickup window capturing any in-flight changes at 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 Spark CRM object lands in HubSpot, including any object-level transformations, lookup resolution, or schema-design dependencies.
Typical mapping — final map is confirmed during the sample migration step.
Spark CRM
Contact
HubSpot
Contact
1:1Spark CRM contacts map directly to HubSpot contacts. Each contact's first name, last name, email, phone, job title, and address fields migrate as HubSpot standard properties. The primary company association from Spark CRM becomes the HubSpot contact's Company property. Contacts without a company in Spark CRM land as unassociated HubSpot contacts, with no default account assigned.
Spark CRM
Company
HubSpot
Company
1:1Spark CRM companies map to HubSpot companies on a one-to-one basis. The standard fields—company name, domain, industry, number of employees, annual revenue, phone, address, city, state, zip, and country—migrate as HubSpot company properties. Parent‑child hierarchies defined in Spark CRM are recreated in HubSpot using the parent company association. Any custom properties on the company object are created as HubSpot custom properties before data loads.
Spark CRM
Deal
HubSpot
Deal
1:1Spark CRM deals map to HubSpot deals with deal name, amount, close date, and owner preserved. Spark's deal stage migrates as the HubSpot deal stage within the configured pipeline. Spark's single-pipeline model becomes one HubSpot pipeline; teams can add more pipelines post-migration.
Spark CRM
User / Owner
HubSpot
User
1:1Spark CRM owners are resolved to HubSpot users by matching the email address stored in the owner record to the HubSpot user email. Any owner whose email does not correspond to an existing HubSpot user is flagged in the pre‑migration report; your team can then either create a HubSpot user for that person or reassign their records to a designated fallback HubSpot user before the migration run begins.
Spark CRM
Activity: Call
HubSpot
Call engagement
1:1Spark CRM logged calls migrate as HubSpot call engagements, preserving call outcome, direction, duration, phone number, and body text. The original call timestamp and the owner assigned in Spark CRM carry over to the HubSpot engagement record. Once in HubSpot, call engagements display in the contact’s timeline, the associated deal’s activity feed, and are searchable via the HubSpot calls API.
Spark CRM
Activity: Email
HubSpot
Email engagement
1:1Spark CRM logged emails are imported as HubSpot email engagements, transferring the subject line, body (including HTML formatting), participants (to, cc, bcc), and the original sent timestamp. Attachments are downloaded from Spark CRM and re‑uploaded to HubSpot Files, then linked to the engagement. Emails are associated with the appropriate contact and company records by matching email addresses, and they also appear in any related deal’s activity feed.
Spark CRM
Activity: Meeting
HubSpot
Meeting engagement
1:1Spark CRM meeting records are imported as HubSpot meeting engagements, preserving the meeting title, description, start and end times (including time zone), location, and the list of attendees. Any meeting attachments stored in Spark CRM are downloaded and re‑uploaded to HubSpot Files, then linked to the engagement. In HubSpot, the meeting is associated with the relevant contact and company records, and it also appears in the linked deal’s activity feed.
Spark CRM
Note
HubSpot
Note engagement
1:1Spark CRM notes are imported as HubSpot note engagements, preserving body text and any HTML or rich‑text formatting. Original creation timestamp and owner transfer to the HubSpot note. File attachments are downloaded and re‑uploaded to HubSpot Files, then linked to the note. Notes are associated with the matching contact, company, or deal by Spark CRM record ID, keeping context in HubSpot.
Spark CRM
Custom field expansion (CustomFieldsRaw / CustomFieldsExpanded)
HubSpot
HubSpot custom property
1:1Spark CRM's custom field API uses a key-value pair structure grouped by field category. Each unique key becomes a HubSpot custom property on the appropriate object (contact or company), with the data type inferred from the value format. Multi-value selections in Spark CRM become HubSpot multi-checkbox or multi-select properties with value-by-value mapping.
Spark CRM
Deal-to-contact association (multi-contact deals)
HubSpot
Deal-contact association
1:1Spark CRM allows a deal to associate with multiple contacts. In HubSpot, each deal has a primary contact with additional contacts added via deal-contact associations. We migrate all Spark deal-contact links; the primary contact is identified by the most-recent association timestamp or your specified rule.
Spark CRM
Attachment / File
HubSpot
HubSpot Files
1:1Spark CRM file attachments are downloaded and re-uploaded to HubSpot Files. Files are associated with the relevant contact, company, or deal record. Large files are subject to HubSpot's file size limits. Original Spark file URLs embedded in notes are flagged for manual review post-migration.
Spark CRM
Spark CRM pipeline and stage
HubSpot
HubSpot deal pipeline and stage
1:1Spark CRM's single pipeline and its stage set map to one HubSpot pipeline with corresponding stages. Each stage name becomes a HubSpot deal stage value in the target pipeline. If Spark stages include custom statuses not present in HubSpot's defaults, those stages are created as custom stage values within the pipeline.
| Spark CRM | HubSpot | Compatibility | |
|---|---|---|---|
| Contact | Contact1:1 | Fully supported | |
| Company | Company1:1 | Fully supported | |
| Deal | Deal1:1 | Fully supported | |
| User / Owner | User1:1 | Fully supported | |
| Activity: Call | Call engagement1:1 | Fully supported | |
| Activity: Email | Email engagement1:1 | Fully supported | |
| Activity: Meeting | Meeting engagement1:1 | Fully supported | |
| Note | Note engagement1:1 | Fully supported | |
| Custom field expansion (CustomFieldsRaw / CustomFieldsExpanded) | HubSpot custom property1:1 | Fully supported | |
| Deal-to-contact association (multi-contact deals) | Deal-contact association1:1 | Fully supported | |
| Attachment / File | HubSpot Files1:1 | Fully supported | |
| Spark CRM pipeline and stage | HubSpot deal pipeline and stage1:1 | 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.
Spark CRM gotchas
Multiple unrelated 'Spark CRM' products exist
Platform fee on top of monthly subscription affects long-term TCO
Payment-orchestration data is tightly coupled to Spark's runtime
Limited public review footprint for due diligence
HubSpot gotchas
Marketing Contacts billing model is migration-critical
Feature tier gating is not visible until onboarding
Mandatory onboarding fees inflate year-one cost
HubSpot CSV importer cannot migrate engagements or attachments
Custom objects require Enterprise and a pre-existing schema
Pair-specific challenges
Migration approach
Audit Spark CRM data and document the source schema
FlitStack AI runs a full data audit against your Spark CRM account, profiling all contact, company, deal, and activity records. We capture record counts, identify duplicate and incomplete records, document custom field names and data types from the CustomFieldsRaw expansion, map the Spark pipeline and stage structure, and document the association types in use. This audit produces a data quality report and a schema inventory that becomes the basis for the field mapping plan before any records move.
Build the Spark CRM to HubSpot field mapping plan
FlitStack maps each Spark CRM contact property, company property, deal field, and custom field to its HubSpot equivalent. Standard fields map directly. CustomFieldsRaw key-value pairs become HubSpot custom properties created with the appropriate data type. Pick-list fields receive value-by-value mapping for each option. Owner email addresses are matched against existing HubSpot users; unmatched owners are flagged for your team to resolve. The mapping plan is reviewed with your team before the test migration runs.
Run a sample migration with field-level diff
A representative slice of records — typically 100 to 500 across contacts, companies, deals, and a sample of activities — migrates to HubSpot in a test environment. FlitStack generates a field-level comparison report showing source values, mapped values, and any discrepancies. You verify lifecycle stage mapping, deal stage routing, owner resolution, and deal-contact association completeness. The sample run validates the mapping logic and surfaces any Spark fields that were missed before the full migration commits.
Execute the full migration with delta-pickup cutover
The full data set migrates in dependency order — companies first, then contacts, then deals — with Spark CRM owner IDs resolved to HubSpot user records. Spark CRM remains fully operational during the migration; your team continues working without interruption. A delta-pickup window (typically 24 to 48 hours) captures any records created or modified in Spark CRM during the cutover period. FlitStack generates an audit log covering every record migrated, the mapping applied, and the target HubSpot record ID assigned. One-click rollback is available if reconciliation finds unexpected discrepancies.
Post-migration validation and reconciliation report
After the migration commits, FlitStack runs a reconciliation report comparing Spark CRM record counts and field values against HubSpot records. We verify deal-to-contact associations, confirm pipeline and stage assignments, check that custom property values populated correctly, and flag any records that were held during migration due to quality issues. A Spark CRM workflow export is delivered as a documented rebuild reference for your HubSpot admin to recreate automation in HubSpot's workflow builder.
Platform deep dives
Spark CRM
Source
Strengths
Weaknesses
HubSpot
Destination
Strengths
Weaknesses
Complexity grading
Standard CRM migration. 2 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 Spark CRM and HubSpot.
Object compatibility
2 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
Spark CRM: Not publicly documented on sparkcrm.io.
Data volume sensitivity
Spark CRM 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
Pick a category, then your source and destination platforms.
Category
FAQ
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