HubSpot stores ticket history as fragmented engagement objects across multiple APIs. Migrating to Front means reconstructing them into threaded conversations under tight rate limits on both sides.
There is no native migration path from HubSpot Service Hub to Front for historical ticket data. HubSpot stores support interactions as fragmented CRM objects—tickets, emails, notes, calls, and attachments—linked via an associations layer, while Front consolidates everything into threaded conversations within shared inboxes. Migrating requires a custom API-led pipeline that extracts tickets and all associated engagements from multiple HubSpot v3 endpoints, reconstructs them chronologically, and writes them into Front via the Import Message endpoint, handling strict rate limits on both sides.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
The standard HubSpot ticket export drops all conversation content
If you export tickets via the UI or the CRM Exports API, you get a spreadsheet of metadata — not the actual support history your team needs in Front.
HubSpot's v3 API does not have a unified engagements endpoint
The legacy v1 endpoint (/engagements/v1/engagements/paged) returned all engagement types in one call. The v3 API splits them into separate object endpoints — emails, notes, calls, meetings, and tasks — with no consolidated alternative. Extraction scripts must query each type independently.
Recommended extraction order
``text tickets -> ticket associations (email, note, call, contact, company) -> activity objects (full properties + bodies) -> HubSpot files / signed URLs -> normalized timeline -> Front messages + comments ``
Threading matters
To group related messages into a single Front conversation, use the conversation_id returned by the first imported message. Getting this wrong creates orphan conversations — one per message instead of one per ticket. If a HubSpot ticket has no customer-facing email thread at all, Front supports comment-only discussion conversations rather than forcing you to invent a fake inbound email. (dev.frontapp.com)
Front custom field updates are replace operations
When you PATCH conversation custom_fields, Front expects the full field set. If you send only the field you want to change, omitted fields are erased. Read, merge, then write. (dev.frontapp.com)
If you're moving in phases, let Front's native HubSpot sync handle reference data —
If you're moving in phases, let Front's native HubSpot sync handle reference data — contacts and companies — while your custom migration handles conversations, comments, and files.
The runbook
Work top to bottom. Tick steps as you go — your progress is saved in this browser.
01 Discovery Establish why you are moving, what "done" means, and who signs off.
Objective A written scope with agreed success criteria, a named owner per workstream, and a budget approved by finance.
Keep these open
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Pull the real numbers out of HubSpot
Export counts for tickets (open and closed separately), contacts, organisations, attachments, macros, triggers, automations, views and SLA policies. Note the oldest ticket date — history depth drives the whole timeline. Estimating from memory is the single most common cause of a blown migration window.
Data Profiler Get real record counts instead of estimating from memory -
Decide what history actually moves
Agree a cut-off with the support lead: all history, last 24 months, or open tickets plus a read-only archive. Every extra year of closed tickets adds API time and cost without adding much agent value. Get this in writing — it is the decision people relitigate mid-cutover.
A "move everything" default is what turns a two-week migration into a two-month one.
COI & ROI Calculator Build the 36-month business case you will need for sign-off -
Confirm Front can hold your support model
Walk your current workflow through Front: multi-brand, business hours, SLA targets, CSAT, side conversations, public vs internal notes, and any channel you depend on (voice, chat, WhatsApp, social). List anything with no native equivalent — those are project risks, not configuration details.
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Build the business case
Model licence delta, migration effort, agent retraining, and the cost of staying put (Cost of Inaction). Executives approve a number, not a plan, and you will be asked for it again at the go/no-go.
Helpdesk Migration Planner Turn ticket volume into a dated HubSpot → Front timeline -
Name owners and set the go/no-go date
One named owner each for data, configuration, integrations, and agent enablement, plus a decision-maker who can call a rollback. Put the go/no-go meeting in calendars now, 48 hours before the freeze.
Don't move on until
- Record counts confirmed for tickets, contacts, organisations and macros
- Success criteria signed off by the support lead
- Freeze window provisionally booked with the business
02 Data Audit Find out what is actually in the data before you try to move it.
Objective A profiled, cleaned export with every quality defect either fixed at source or explicitly accepted.
Keep these open
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Take a full HubSpot export and profile it
Export to CSV or JSON and profile every file: row counts, null rates per column, distinct values, and type consistency. Compare row counts against the API totals from Discovery — a gap here means your export is silently truncated, usually by pagination.
Data Profiler Profile the HubSpot export for nulls, outliers and type drift -
Validate file structure before anyone writes a transform
Check delimiters, quoting, encoding (expect UTF-8, watch for BOMs and Latin-1), duplicate headers, and embedded newlines in ticket bodies. Ticket descriptions with raw newlines and commas break naive CSV parsers and silently shift columns.
A single unescaped quote in one ticket body can shift every subsequent column without any error.
CSV Validator Catch broken headers and ragged rows in the raw export -
Inventory PII and set retention
Scan for emails, phone numbers, payment card fragments, national IDs and anything else regulated in ticket bodies and custom fields — support tickets are where customers paste things they should not. Decide what gets migrated, masked, or dropped, and record the legal basis.
Ticket bodies and attachments routinely contain card and ID data that never appears in a structured field.
PII & Compliance Scanner Find regulated fields before they land in a new system -
Quantify duplicates, orphans and dead references
Count duplicate contacts (same email, different casing), tickets whose requester no longer exists, organisations with no members, and attachments whose parent ticket is gone. Fix these in HubSpot where you can — migrating them just moves the mess.
Data Cleaner Strip empty rows, stray whitespace and dead columns -
Clean and normalise the export
Trim whitespace, drop empty rows and columns, normalise casing on emails and tags, and standardise every timestamp to UTC ISO 8601. Timezone drift is invisible at load time and shows up weeks later as SLA reports nobody can reconcile.
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Produce a masked copy for sandbox work
Generate a realistic but fake version of the export for testing and for any vendor who needs sample data. Loading real customer PII into a sandbox is a breach in most jurisdictions, and sandboxes are rarely covered by your DPA.
PII Masker Generate a safe copy for sandbox and vendor testing -
Extract Messages and Comments
For each conversation, call GET /conversations/{conversation_id}/messages and GET /conversations/{conversation_id}/comments.
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Extract Tags
Tags are returned in the conversation object, but you can also map the global tag list via GET /tags.
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Download Attachments
Parse the attachments array in each message and download the files using the provided URLs.
HubSpot → Front specifics
- List Conversations
- Use GET /conversations or GET /inboxes/{inbox_id}/conversations to paginate through shared inboxes.
Don't move on until
- Export parses cleanly with no ragged rows or encoding errors
- PII inventory complete and retention decisions recorded
- Duplicate and orphan records quantified and triaged
03 Field Mapping Turn two schemas into one signed-off mapping spec.
Objective A reviewed field-level mapping covering every object, with an explicit decision for every field that has no target.
Keep these open
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Generate the first-pass HubSpot → Front field map
Start from an automated match on both schemas, then review every row by hand. Automated matching gets the obvious 70% right and is confidently wrong on the rest — especially anything named "type", "status" or "custom_field_1".
Schema Mapper Opens pre-loaded with the HubSpot → Front field pair -
Map status, priority and channel values, not just field names
Enumerate every value in each picklist on both sides and map them explicitly. Value-level mismatches are the defect class that survives all the way to production because the field itself mapped fine — a ticket that should be "Pending" arriving as "Open" reopens SLA clocks.
Statuses with no target equivalent (on-hold, pending-customer) need a policy decision, not a best guess.
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Decide how custom fields land
Create the target custom fields first, matching type exactly (a dropdown mapped to free text can never be mapped back). Where Front has no equivalent, decide between a new custom field, a tag, or a note appended to the ticket body — and record which.
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Resolve identity and threading
Decide how source IDs are preserved — most platforms will not let you set the primary key, so keep the original ID in a custom field. Without it, reconciliation becomes fuzzy matching and every future support question about an old ticket is unanswerable.
Losing the original ticket ID makes reconciliation and rollback effectively impossible.
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Plan attachments, inline images and threading order
Confirm size limits, allowed MIME types, and whether inline images survive as attachments or need rehosting. Decide the comment ordering and author attribution rules: comments loaded out of order, or all attributed to the API user, destroy the conversation history agents rely on.
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Freeze and sign off the mapping spec
Version the spec, walk the support lead through it row by row, and get explicit sign-off. Any change after this point goes through change control — mid-flight mapping edits are how partial loads happen.
Don't move on until
- Every source field is mapped, deliberately dropped, or parked in a custom field
- Status, priority and channel value maps agreed with the support lead
- Mapping spec version-controlled and signed off
04 Test Migration Prove the pipeline on a small, representative slice.
Objective A pilot load into a Front sandbox that reconciles cleanly and has been reviewed by real agents.
Keep these open
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Stand up a Front sandbox that matches production config
Create the custom fields, groups, brands, business hours and SLA policies first. A pilot into a default sandbox tests nothing, because the failures you care about are all configuration mismatches.
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Pick a deliberately nasty pilot sample
Take 500-1000 records chosen for difficulty, not convenience: the longest ticket threads, tickets with the most attachments, non-Latin character sets, merged and split tickets, deleted requesters, and every status value. A clean random sample proves only that easy records are easy.
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Run the load with masked data and instrument everything
Log every API request and response with its source record ID. When 40 records fail out of 10,000 you need to know exactly which ones and why, without re-running the whole batch.
PII Masker Never load real customer PII into a sandbox -
Measure real throughput against the rate limit
Record achieved records-per-hour under Front's actual rate limits, including retries and backoff. Extrapolate to the full volume: if the maths says the full load exceeds your freeze window, you fix that now, not on cutover night.
Published rate limits are ceilings, not throughput. Assume real-world rates are meaningfully lower once retries and backoff are counted.
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Reconcile the pilot and triage every failure
Diff source against target on record counts and field-level values. Every discrepancy gets a root cause and a fix — "probably fine" at pilot scale becomes thousands of broken records at full scale.
Migration Validation Tool Diff the pilot batch against source before scaling up -
Put real agents in front of the pilot data
Have two or three agents work sample tickets end to end in the sandbox. They find the things reconciliation cannot see: unreadable threading, missing context, macros that no longer make sense. Fix the mapping, then re-run.
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Test rules and workflows
Imported conversations may or may not trigger Front rules depending on how they were imported. Test before enabling any auto-assignment or auto-tagging rules.
Don't move on until
- Pilot batch reconciles to 100% on record counts
- Agents have reviewed sample tickets and confirmed they are workable
- Measured throughput extrapolates to a viable full-load window
05 Cutover Execute the switch inside a controlled, reversible window.
Objective All in-scope data live in Front, agents working in the new system, and a rollback path that stayed available throughout.
Keep these open
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Pre-load history before the freeze
Load closed tickets and contacts days or weeks ahead while HubSpot stays live. Only open tickets and the final delta need to move inside the freeze — this is the single biggest lever on window length.
Helpdesk Migration Planner Size the freeze window from Front's real API limits -
Publish the runbook with times, owners and abort criteria
A timed sequence: freeze start, final export, delta load, channel switch, smoke test, go/no-go, agent switch. Name who does each step and the explicit condition that triggers a rollback. Decide the abort criteria before the night, when nobody wants to be the one to call it.
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Freeze HubSpot and take the final delta
Stop new ticket creation, let agents finish in-flight replies, then export everything changed since the pre-load. Announce the freeze to the whole business, not just support — someone always tries to raise a ticket during it.
Tickets created during an unenforced freeze land in the old system and are the most common source of permanently lost data.
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Load the delta and open tickets
Run the delta load, then reconcile counts before touching any channel. Do not repoint email until the delta has verified — an inbound ticket arriving mid-load is far harder to untangle than a few extra minutes of freeze.
Migration Validation Tool Confirm the final delta landed before you reopen -
Repoint channels and verify with live traffic
Switch email forwarding and MX or connector settings, update chat widgets and web forms, and re-authorise integrations. Then send real test tickets through every channel and confirm each lands, routes and triggers the right automation.
Email forwarding changes can take up to a full DNS TTL to propagate — check the TTL days in advance and lower it if needed.
Cron Expression Builder Schedule the delta syncs that run through the freeze -
Run the go/no-go and switch the agents
Walk the exit criteria with the decision-maker, call it explicitly, then move agents over with a named person on hand for the first few hours. Keep HubSpot read-only rather than cancelled — cancelling the old contract on day one removes your only fallback.
Don't move on until
- Full historical load complete and counts matched
- Inbound channels repointed and verified with live test tickets
- Rollback decision point passed explicitly, not by default
06 Validation Prove the migration is complete, then close it out.
Objective Documented evidence that data, workflow and reporting all survived, and a signed acceptance.
Keep these open
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Run the full reconciliation
Compare source and target on every object: total counts, counts by status, counts by group, attachment counts, and field-level spot checks on a random sample. Produce one report you can hand to an auditor.
Migration Validation Tool Reconcile HubSpot and Front record-for-record -
Verify field completeness, not just record counts
Re-profile the loaded data and compare null rates per field against the source profile. Matching record counts with a field that silently arrived empty is the failure mode counts alone will never catch.
Data Profiler Prove field completeness held up through the load -
Rebuild reporting and compare against baselines
Recreate your core dashboards — volume, first response time, resolution time, CSAT — and compare to pre-migration figures for the same period. Explain every variance; a changed SLA calculation is a real finding, not a rounding error.
SLA and first-response metrics are usually recalculated from the loaded timestamps, so they will differ if any timestamp mapping was approximate.
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Test the workflow layer end to end
Fire every trigger, automation, SLA escalation, macro and notification with a live ticket. Workflow does not migrate — it gets rebuilt — so it is untested until someone has actually watched it run.
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Confirm compliance and produce the audit trail
Re-scan the loaded data for regulated fields, confirm retention and deletion policies are configured in Front, and file the evidence with your PII decisions from the audit phase.
PII & Compliance Scanner Produce the compliance evidence your auditor will ask for -
Sign off, then decommission on a schedule
Get written acceptance against the Discovery success criteria. Keep HubSpot read-only for an agreed period (30-90 days is typical), take a final archive export, and only then cancel. Diarise the decommission date so it does not quietly renew.
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Check contact matching
Ensure conversations are linked to the correct Front contacts — especially where HubSpot had multiple email addresses per contact.
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Verify tag and status mapping
Confirm that pipeline stages, priorities, and custom property values translated correctly to Front tags and ticket statuses.
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Confirm attachment integrity
Open a sample of attachments to verify they're downloadable and not corrupted. Check inline images specifically.
HubSpot → Front specifics
- Spot-check 50 conversations
- across different pipelines. Verify message ordering, sender attribution, note content, and attachment accessibility.
- Search by source IDs
- If you stored HubSpot ticket IDs in Front custom fields, run searches to verify the lookup works. This is your audit trail for post-migration troubleshooting.
Don't move on until
- Full reconciliation report attached to the project record
- Reporting baselines match pre-migration figures within agreed tolerance
- Formal acceptance signed and archive retention scheduled
Field mapping reference
The field-by-field mapping for each object. Use this as the starting point for your mapping spec.
Ticket Conversation Mapping
Ticket-level properties such as subject, status, pipeline, priority, and owner are straightforward to extract and map to Front conversation fields.
| HubSpot field | Front field | Notes |
|---|---|---|
| Ticket ID (hs_object_id) | Conversation reference / custom field | Use as external ID for tracking. Store in custom field for search and audit. |
| Subject (subject) | Conversation subject | Maps directly. |
| Pipeline + Stage | Inbox + Tag / Ticket status | Map each pipeline to a Front inbox. Stages become tags or ticket statuses (requires ticketing enabled). |
| Priority (hs_ticket_priority) | Tag | Front uses tags for priority; no native priority field on conversations. |
| Status (Open/Closed) | Conversation status | open → Open, closed → Archived. |
| Owner (hubspot_owner_id) | Assignee (teammate_id) | Map HubSpot owner emails to Front teammate IDs. HubSpot's owners API returns owner ID and email for a deterministic lookup table. |
| Contact (associated_contact) | Conversation sender/recipient | Match by email address. Front auto-creates contacts. |
| Company (associated_company) | Contact's company / Account | Front links contacts to accounts. |
| Create date (createdate) | created_at on imported message | Set using the created_at field in the import payload. |
| Custom properties | Conversation custom fields or tags | Front supports custom fields on conversations (Enterprise). Map selectively. |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Tickets (metadata) | low | Ticket-level properties such as subject, status, pipeline, priority, and owner are straightforward to extract and map to Front conversation fields. |
| Email Engagements | high | Emails are stored as separate objects requiring individual API fetches, and HTML bodies, directions, and threading must be reconstructed accurately to avoid data loss or misattribution. |
| Internal Notes | medium | HubSpot notes must be mapped to Front comments and ordered chronologically within the conversation, with risk of placement errors if timestamps are missing or inconsistent. |
| Call Logs | high | Call records include duration, direction, and body text that have no direct equivalent in Front's message model, requiring lossy conversion into comment or custom message representations. |
| Attachments | high | Attachments must be downloaded separately via HubSpot's Files API and re-uploaded to Front with a 25 MB per-message cap, risking silent data loss for oversized files. |
| Contacts | low | Front's native HubSpot integration supports one-way contact sync, making basic contact data the least risky entity to migrate. |
| Companies | low | Company records are supported by Front's built-in HubSpot integration for one-way sync and do not require custom migration work. |
| Custom Fields | medium | HubSpot custom ticket properties must be manually mapped to Front tags or conversation fields, with no automated schema translation available. |
| Conversation Threading | high | Incorrect use of conversation_id during import creates orphan messages—one conversation per message instead of one per ticket—causing fragmented and unusable history in Front. |
| Meetings & Tasks | medium | Meetings and tasks are engagement types with no direct Front equivalent, requiring conversion to comments or custom messages with potential loss of structured metadata. |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
Fragmented Data Model Reconstruction
A single HubSpot ticket can span emails, notes, calls, meetings, and attachments across five or more separate API object types, all of which must be fetched individually and reassembled into one coherent Front conversation.
N+1 API Query Problem
HubSpot's v3 API lacks a unified engagements endpoint, forcing extraction scripts to query tickets, then associations, then each engagement object separately—resulting in hundreds of thousands of API calls for moderately sized portals.
Tight Front Rate Limits
Front enforces per-company rate limits as low as 50–200 requests per minute depending on plan tier, with the import message endpoint further capped at 5 requests per resource per second, making large-scale imports extremely slow.
Conversation Threading Accuracy
Multi-message HubSpot tickets must be threaded correctly by capturing the conversation_id from the first imported message and appending subsequent messages to it, or the migration produces orphan conversations instead of unified threads.
Standard Exports Drop Content
HubSpot's UI and CRM Exports API only produce flat CSVs of ticket-level properties and associated record IDs—no email bodies, internal notes, call logs, or attachments—making them unusable for historical migration.
Attachment Size Constraints
Front's import endpoint caps attachments at 25 MB per message, requiring an alternate storage or linking strategy for any HubSpot files that exceed this threshold.
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
Can I export HubSpot ticket conversations to a CSV?
No. HubSpot's standard ticket export only includes ticket-level properties (status, pipeline, priority, owner). The actual conversation content — emails, notes, calls — are separate engagement objects that require the Engagements API to extract. You cannot get email bodies or notes from a CSV export. (knowledge.hubspot.com)
Does Front have a native HubSpot importer?
No. Front's published HubSpot integration covers CRM actions plus one-way contact and company sync, not historical ticket migration. Front's only built-in importers are for Freshdesk and Zendesk, and even those are limited (capped at 9,000 tickets, not actively maintained). HubSpot migrations must go through Front's Core API using the imported_messages endpoint.
What are Front's API rate limits for data migration?
Front defaults to 50 requests per minute on Starter, 100 on Professional, and 200 on Enterprise — enforced per company. The import message endpoint has an additional Tier 2 burst limit of 5 requests per resource per second. You can purchase add-ons for 300 additional calls per minute. Build retries and exponential backoff into the loader from the start. (dev.frontapp.com)
How should HubSpot notes and calls map into Front?
Notes become Front comments — the cleanest way to preserve private context without pretending it was part of the customer thread. Calls also become timestamped comments, because Front's import endpoint supports email, SMS, Intercom, and custom message types but not a first-class historical call type. Include call metadata like duration, direction, and recording URLs in the comment body.
What data gets lost when migrating from HubSpot to Front?
Common silent data loss includes: inline images referencing HubSpot's file manager (URLs may expire post-migration), private file attachments missing the files.ui_hidden.read scope, closed-ticket timestamps (Front archives reflect migration date, not original close date), and HubSpot-specific field types like calculated fields and score fields that have no Front equivalent.