Intercom and Freshdesk share similar core models for contacts, companies, and conversations, but Freshdesk enforces stricter schema references and does not support backdating timestamps. Every custom field, dropdown option, and ticket type must exist before data import. Intercom Conversations become Freshdesk Tickets with message parts mapped to notes or replies based on visibility. Intercom's newer Tickets API represents internal tasks that require separate schema mapping and can be linked back to Conversations via private notes. Intercom-specific features like events, lead scoring, and bot conversations have no direct Freshdesk equivalents and must be archived externally as CSV or JSON.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
Check your Freshdesk plan tier
API access, custom field limits, and automation capabilities vary significantly between Freshdesk plans (Free, Growth, Pro, Enterprise). Verify that your plan supports the number of custom fields, API rate limits, and features your migration requires before you begin.
On backdated timestamps
Freshdesk does not allow backdating created_at on any object — companies, contacts, or tickets. Throughout this guide, wherever a timestamp needs to be preserved, store the original value in a custom field (e.g., original_created_at) or prepend it to a note header. This applies to every mapping table below.
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 Intercom
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 Freshdesk can hold your support model
Walk your current workflow through Freshdesk: 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 Intercom → Freshdesk 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.
Intercom → Freshdesk specifics
- Data to migrate
- Conversations (including messages and attachments), contacts, companies, tags, and custom attributes. These represent the transactional and relational data that define your customer interactions.
- Configuration to rebuild
- Workflows, assignment rules, SLAs, agent groups, roles, and automations. These are platform-specific and need to be recreated in Freshdesk.
- Data to archive
- Intercom events, leads, and in-app engagement metrics. These can be exported to a CSV or stored as a JSON archive for reference, but they do not have 1:1 objects in Freshdesk.
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 Intercom 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 Intercom 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 Intercom 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
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 Intercom → Freshdesk 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 Intercom → Freshdesk 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 Freshdesk 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.
Intercom → Freshdesk specifics
- Custom field completeness
- For each custom field, run a count of non-null values in Freshdesk and compare against Intercom source counts.
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 Freshdesk sandbox that reconciles cleanly and has been reviewed by real agents.
Keep these open
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Stand up a Freshdesk 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 Freshdesk'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.
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 Freshdesk, 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 Intercom 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 Freshdesk'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 Intercom 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 Intercom 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 Intercom and Freshdesk 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 Freshdesk, 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 Intercom 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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Record counts
Compare total companies, contacts, and tickets between Intercom exports and Freshdesk. Every object type should match within your defined migration scope.
Intercom → Freshdesk specifics
- Spot-check sampling
- Pick 20–50 tickets across different categories (multi-company contacts, long threads, tickets with attachments, multilingual articles, CSAT-rated conversations). Open each in Freshdesk and verify field values, message order, and attachment integrity against the Intercom source.
- Tag reconciliation
- Export tag lists from both platforms and diff them. Missing or misspelled tags break automations and views.
- Attachment integrity
- Confirm that attachments open correctly and that no files were silently dropped during upload (common with oversized files or unsupported MIME types).
- Company–contact linkage
- Verify that contacts are associated with the correct companies by checking a sample of domain-based auto-associations.
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.
Company Company
| Intercom field | Freshdesk field | Notes |
|---|---|---|
| id | unique_external_id + custom field intercom_company_id | Required to re-run imports safely. |
| name | name | Use the same company name. |
| domain | domains [] | Enables auto-association for users sharing a domain. |
| company_id (custom) | custom_fields{} | Precreate schema for any Intercom custom attributes. |
| created_at | read-only custom field original_created_at | See backdating note above. |
Contact Contact
Clean mapping, but Leads need special tagging as inactive contacts
| Intercom field | Freshdesk field | Notes |
|---|---|---|
| id | unique_external_id + intercom_contact_id | Keeps imports idempotent. |
| name | name | Combine first and last names if separate. |
| Required for requesters. | ||
| phone | phone | Normalize format to E.164 for consistency. |
| companies [] | company_id | Links to imported company. |
| custom_attributes{} | custom_fields{} | Create schema before import. |
| tags [] | tags [] | One-to-one mapping. |
| created_at | original_created_at | See backdating note above. |
Conversation Ticket
Requires field pre-creation, chronological ordering, and HTML cleanup
| Intercom field | Freshdesk field | Notes |
|---|---|---|
| id | unique_external_id + custom field intercom_conversation_id | Critical for deduplication and delta sync. |
| title or subject | subject | Intercom may not have subjects for messenger threads; derive from first message. |
| created_at | stored in original_created_at | See backdating note above. |
| state (open, closed, snoozed) | status | Map to Freshdesk statuses: Open, Pending, Resolved, Closed. |
| priority | priority | Intercom doesn't always expose priority; set default "Medium." |
| assignee.id | responder_id | Recreate agents and map accordingly. |
| tags [] | tags [] | Direct import. |
| custom_attributes{} | custom_fields{} | Schema must pre-exist. |
| source | source (integer enum) | Freshdesk uses an integer enum: 1=email, 2=portal, 3=phone, 7=chat, etc. Map Intercom source strings to the corresponding integer value. |
Part Conversation
| Intercom field | Freshdesk field | Notes |
|---|---|---|
| author | requester or agent on note | Ensure user exists. |
| body (HTML) | body_html | Clean inline styles and images. |
| attachments [] | uploaded file on note | Re-upload; maintain original filenames. Freshdesk enforces a 20 MB per-file limit — check for oversized Intercom attachments before import. |
| created_at | note header or original_created_at field | See backdating note above. |
Cus mer Satisfaction
| Intercom field | Freshdesk field | Notes |
|---|---|---|
| rating | rating value | Map "positive/neutral/negative" to "good/bad." Intercom's "neutral" has no direct equivalent — decide whether to drop it or map to "bad" based on your reporting needs. |
| feedback_text | satisfaction comment | Store as rating comment. |
| submitted_at | note text | Include "Original CSAT at [datetime] by [user]." |
Article Solution Article
Image URLs must be rewritten after upload to Freshdesk
| Intercom field | Freshdesk field | Notes |
|---|---|---|
| id | unique_external_id | Use for re-runs. |
| title | title | |
| body (HTML) | description | Retain formatting; rewrite image URLs after upload. |
| author_id | author | Must exist as agent. |
| tags [] | labels [] | 1:1 mapping. |
| attachments [] | attachments [] | Re-upload files. |
| translations [] | translations [] | Add per language. |
Ticket Ticket
Requires field pre-creation, chronological ordering, and HTML cleanup
| Intercom field | Freshdesk field | Notes |
|---|---|---|
| id | unique_external_id + custom field intercom_ticket_id | Required to support idempotent imports and delta re-runs. |
| title | subject | If missing, derive from category or ticket_type_id. |
| description | description_html | Clean HTML before import; replace embedded image URLs. |
| category | ticket_type or a custom dropdown field | Freshdesk uses "Ticket Type." Create custom values if needed. |
| ticket_type_id | custom_fields.ticket_type_ref | Optional – store reference for reporting. |
| state (open, snoozed, closed) | status | Map to Open, Pending, Resolved, Closed. |
| priority | priority | Direct mapping. Default "Medium" if null. |
| contact_ids [] | requester_id | Ensure contact exists; create if missing. |
| teammate_ids [] | responder_id or group association | Re-map agent IDs to existing Freshdesk agents. |
| tags [] | tags [] | One-to-one tag import. |
| created_at | original_created_at (custom field) | See backdating note above. |
| updated_at | updated_at | Use for sync and delta comparison. |
| custom_attributes{} | custom_fields{} | Pre-create schema for all Intercom ticket attributes. |
Freshdesk Conversation Notes and caveats
| Intercom field | Freshdesk field | Notes |
|---|---|---|
| Public reply by agent | Author → agent. | Admin reply |
| Public reply by requester | Author → contact. | Contact reply |
| Private note | Create note type conversation. | Internal note |
| Attached files on note or reply | Upload separately using multipart API; maintain filenames. Freshdesk enforces a 20 MB per-file limit. | Attachments |
| Not backdatable in Freshdesk | See backdating note above. | Created time |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Companies | low | Direct one-to-one mapping with domain-based auto-association |
| Contacts | low | Clean mapping, but Leads need special tagging as inactive contacts |
| Conversations → Tickets | medium | Requires field pre-creation, chronological ordering, and HTML cleanup |
| Message History | high | Cannot backdate, HTML sanitization required, attachments must be re-uploaded |
| CSAT Ratings | medium | Rating scale must be remapped and timestamps stored as notes |
| Help Center Articles | medium | Image URLs must be rewritten after upload to Freshdesk |
| Intercom Tickets | medium | Separate object requiring distinct schema mapping and ID tracking |
| Ticket-Conversation Links | high | No native linking mechanism, requires private note workarounds |
| Events/Lead Scoring | high | No Freshdesk equivalent, must archive externally as JSON or CSV |
| Workflows/SLAs | medium | Must be manually rebuilt as Freshdesk automations and assignment rules |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
Timestamp Preservation
Freshdesk cannot backdate ticket or comment creation times. Original dates must be stored in custom fields or prepended as note headers.
HTML Body Cleanup
Intercom messages contain inline styles and base64 images that must be sanitized before import to avoid broken formatting and bloat.
Ticket-Conversation Linking
Intercom links Tickets to Conversations, but Freshdesk requires private note workarounds or custom fields to preserve these relationships.
Schema Pre-Creation
All custom fields, dropdown options, and ticket types must exist in Freshdesk before any data import begins.
Lead Data Gap
Intercom Leads have no direct Freshdesk equivalent and must be imported as tagged inactive contacts to preserve the distinction.
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.