Freshdesk-to-Zendesk migration is a data-model translation problem with specific API constraints on both sides. This guide covers the complete process: pre-migration checklist, exact field and status mapping, how to translate Freshdesk automations into Zendesk triggers and macros, attachment and inline-image re-hosting, delta sync mechanics for zero-downtime cutover, sandbox testing procedures, rollback plans, a full QA verification checklist, and realistic timelines by migration size. The three migration methods (CSV, SaaS tool, engineer-led) each have hard trade-offs — choose based on your fidelity requirements, not the tool's marketing.
Migrating from Freshdesk to Zendesk is a data-model translation problem, not a drag-and-drop. Freshdesk organizes support around contacts and tickets in a flat hierarchy, while Zendesk uses a layered model of users, organizations, and tickets where every record relates through explicit ID references. The structural mismatch creates three core problems: a single Freshdesk contact with a company must split into a Zendesk user plus organization membership, conversation types (replies, notes, forwards) must flatten into Zendesk's public/private comment model, and status mapping is not 1:1 across the two platforms. Every migration requires the Zendesk Ticket Import API for timestamp preservation, inline image re-hosting to prevent broken URLs, and careful rate limit management across both platforms (200–700 req/min).
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
Do not test migration scripts on a Freshdesk trial account
Trial accounts are hard-capped at 50 requests per minute. A migration script that works fine in dev will hit hundreds of 429 errors at that rate, giving you a false picture of how the production run will behave. Always test against a paid sandbox or request a temporary rate limit increase from Freshdesk support.
Do not rely on one GET /tickets loop for a historical export
Segment by updated_since, and plan a separate conversation pass for long tickets. If you need archived tickets or a broader system snapshot, use the account export job instead of trying to coerce everything through the list endpoint.
Imported tickets do not run triggers, and historical ticket metrics are not backfilled
Zendesk does not compute first reply time or first resolution time for imported tickets. Tag imported tickets (e.g., migrated_from_freshdesk) and exclude them from SLA reports. Plan your workflow cutover and reporting expectations separately from data loading. (support.zendesk.com)
Zendesk tags cannot contain spaces or uppercase letters
Freshdesk allows both. Run a normalization pass on all tags before import: lowercase, replace spaces with underscores, strip special characters.
Do not disable Freshdesk immediately after cutover
Keep it running in read-only mode for at least 72 hours. Straggler emails from cached DNS records, webhook retries from third-party tools, and agent bookmarks pointing to old URLs will all surface during this window.
Select edge cases deliberately
Your sample should include the hardest tickets, not a random slice. If you have a ticket with 200 conversations, a 19 MB attachment, and 8 custom fields, that ticket should be in your sample.
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 Freshdesk
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 Zendesk can hold your support model
Walk your current workflow through Zendesk: 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 Freshdesk → Zendesk 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.
Freshdesk → Zendesk specifics
- Days 1–4
- Data audit. Exported sample of 300 tickets. Built field mapping tables. Identified 3 custom statuses requiring tag-based mapping (Zendesk Professional plan, no custom status support). Discovered 1,200 tickets with inline images requiring re-hosting.
- Days 5–14
- Script development. Built export pipeline with updated_since windowing and conversation fan-out for tickets with 10+ replies. Built import pipeline with attachment re-hosting, tag normalization, and retry logic. Tested against Zendesk trial instance.
- Days 15–17
- Sample migration of 500 tickets in sandbox. Identified 2 issues: dropdown custom field values not transforming correctly, and 4 inline images with unusual URL patterns not caught by the regex. Fixed and re-ran.
- Days 18–20
- Bulk import. Ran overnight during low-support-volume hours. Completed in 14 hours. Support team continued working in Freshdesk during this window.
- Days 21–24
- QA. Ran automated count checks (99.8% ticket parity, 99.6% conversation parity). Manually inspected 100 tickets. Found 3 tickets with broken inline images (edge case: SVG files embedded as data URIs). Accepted as known limitation.
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 Freshdesk 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 Freshdesk 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 Freshdesk 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 -
Contact/company export jobs
return downloadable CSVs. These are async — only one export job can run at a time per account, and download URLs expire after 15 days. Useful for flat bulk pulls of identity data.
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Clean the Zendesk instance
If you used a sandbox or trial, discard it and provision a new one. If you imported into production Zendesk, delete the imported tickets in batches or tag them for exclusion from views and reporting.
Freshdesk → Zendesk specifics
- Account export jobs
- produce a broader JSON snapshot that can include tickets, archived tickets, contacts, companies, groups, canned responses, surveys, and more. Use this when you need archived tickets or a configuration snapshot alongside the live API extraction.
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 Freshdesk → Zendesk 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 Freshdesk → Zendesk 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 Zendesk 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 Zendesk sandbox that reconciles cleanly and has been reviewed by real agents.
Keep these open
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Stand up a Zendesk 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 Zendesk'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.
Freshdesk → Zendesk specifics
- Any critical automation fires incorrectly in sandbox testing
- Do not go live with untested trigger logic.
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 Zendesk, 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 Freshdesk 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 Zendesk'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 Freshdesk 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 Freshdesk read-only rather than cancelled — cancelling the old contract on day one removes your only fallback.
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Disable Zendesk triggers and automations
to prevent any new tickets from being actioned in the Zendesk instance.
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Fix the issue and re-run the sample migration
before attempting the full migration again.
Freshdesk → Zendesk specifics
- 48 hours before cutover
- Reduce DNS TTL for your support portal domain and any MX records to 300 seconds. This ensures DNS changes propagate quickly on cutover day.
- Cutover day, T-2 hours
- Run the final delta sync from Freshdesk to Zendesk.
- T-1 hour
- Announce to agents that Freshdesk is entering read-only mode. Agents should finish active conversations and not pick up new tickets.
- T-0 (cutover moment)
- Update MX records to point to Zendesk. Update email forwarding rules to route incoming support email to Zendesk. Disable the Freshdesk customer portal (or redirect its DNS to Zendesk's Help Center URL).
- T+15 minutes
- Run a final micro-delta sync to capture any tickets that arrived between the last delta run and the MX record switch. The email queue may still contain messages routed to Freshdesk during DNS propagation.
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 Freshdesk and Zendesk 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 Zendesk, 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 Freshdesk 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.
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.
Object Object
| Freshdesk field | Zendesk field | Notes |
|---|---|---|
| Contact | User | Email is the unique key. Import users before tickets. Handle other_emails as additional identities if reply-by-email continuity matters. |
| Company | Organization | Map company_id → organization_id. Domain mapping optional. |
| Agent | User (role: agent) | Agents must exist in Zendesk before ticket assignment. |
| Group | Group | Recreate groups manually or via API before import. |
| Ticket | Ticket (via Import API) | Use /api/v2/imports/tickets to preserve timestamps. |
| Conversation (reply) | Comment (public: true) | Map body or body_text to comment html_body. Prefer html_body when formatting matters. |
| Conversation (note) | Comment (public: false) | Private notes → private comments. |
| Conversation (forward) | Comment (public: false) | No native equivalent. Append as private note with forward context. |
| view_all_tickets | User restriction + org sharing | Not 1:1. Test portal visibility after import. |
| product_id | Brand, form, tag, or custom field | This is a target design choice, not a platform default. |
| Solution Article | Help Center Article | Separate migration via Help Center API. |
Freshdesk Zendesk
| Freshdesk field | Zendesk field | Notes |
|---|---|---|
| id | external_id | Store Freshdesk ID as external_id for cross-referencing. |
| subject | subject | Direct map. |
| description | First comment body | Freshdesk description = first conversation entry. |
| status (2=Open, 3=Pending, 4=Resolved, 5=Closed) | status (new, open, pending, hold, solved, closed) | Requires explicit mapping table. See below. |
| priority (1=Low, 2=Medium, 3=High, 4=Urgent) | priority (low, normal, high, urgent) | 1:1 if you map Medium → Normal. |
| source (1=Email, 2=Portal, 3=Phone…) | via.channel | Zendesk tracks channel differently; set as tag if needed. |
| requester_id | requester_id | Must reference an existing Zendesk user ID. |
| responder_id | assignee_id | Agent assignment. |
| group_id | group_id | Must reference an existing Zendesk group ID. |
| company_id | organization_id | Mapped through the user's organization membership. |
| tags | tags | Direct map. Validate tag format (Zendesk: lowercase, no spaces). |
| custom_fields | custom_fields | Create matching fields in Zendesk first. Map by field ID. |
| created_at | created_at | Preserved via Import API. |
| updated_at | updated_at | Preserved via Import API. |
Status Value
| Freshdesk field | Zendesk field | Notes |
|---|---|---|
| Open | 2 | |
| Pending | 3 | |
| Resolved | 4 | |
| Closed | 5 | |
| Custom statuses | 6+ | Zendesk supports custom statuses on Enterprise+. Otherwise, map to closest standard status + a tag. |
Company Organization
| Freshdesk field | Zendesk field | Notes |
|---|---|---|
| id | external_id and custom field fd_company_id | Keep the Freshdesk ID for reference and deduplication. |
| name | name | Use consistent naming for search and automation rules. |
| domains [] | domain_names [] | Ensures auto-assignment of tickets to organizations. |
| custom_fields{} | custom fields | Create schema in advance with the same value types. |
| tags [] | tags | Tags import directly as strings. |
Contact User
Email uniqueness and other_emails require separate identity handling.
| Freshdesk field | Zendesk field | Notes |
|---|---|---|
| id | external_id and custom field fd_contact_id | Keeps imports idempotent — meaning re-running the import against the same external_id updates the existing record instead of creating a duplicate. |
| name | name | |
| Required for requesters. | ||
| phone, mobile | phone | Combine both numbers if needed. |
| company_id | organization_id | Must reference an existing organization. If the organization does not exist yet, the import will fail or create an orphaned user. Create organizations first. |
| custom_fields{} | user_fields{} | Schema must exist first. |
| tags [] | tags [] | One-to-one mapping. |
Tickets and their entire conversation his ry
Requires Ticket Import API to preserve timestamps; standard API stamps current date.
| Freshdesk field | Zendesk field | Notes |
|---|---|---|
| id | external_id and custom field fd_ticket_id | Required to rerun safely and update existing tickets. |
| subject | subject | Keep it short; Zendesk truncates at 255 chars. |
| description (HTML) | initial comment | Preserve formatting; clean up HTML tags before import. Tags Zendesk rejects include non-standard elements and inline event handlers (e.g., onclick, onerror). Strip those before import or the API will return a 422. |
| requester_id | requester_id | User must already exist. |
| responder_id | assignee_id | If missing, assign to a default group and update later. |
| group_id | group_id | Recreate groups first. |
| status | status | Use crosswalk table. |
| priority | priority | Direct map (Low, Normal, High, Urgent). |
| source (email/chat/api) | via.channel | Used in Zendesk analytics. |
| tags [] | tags [] | Direct map. |
| custom_fields{} | custom_fields{} | Schema must match. |
| created_at, updated_at | stored in custom fields original_created_at, original_updated_at | The standard Zendesk Tickets API does not allow backdating. However, the Zendesk Ticket Import API (POST /api/v2/imports/tickets) does accept a created_at value and is the correct endpoint to use when timestamp preservation matters. Use the import endpoint wherever possible; fall back to custom fields for anything it does not support. |
| due_by | due_at | Recreate SLA-based due times if required. |
Tickets and their entire conversation his ry
Requires Ticket Import API to preserve timestamps; standard API stamps current date.
| Freshdesk field | Zendesk field | Notes |
|---|---|---|
| body | body_html | Keep HTML safe and properly escaped. |
| incoming true | public true | Marks customer reply. |
| private true | public false | Internal note. |
| attachments [] | attachments [] | Re-upload files; store URLs temporarily if you hit limits. |
CSAT CSAT
| Freshdesk field | Zendesk field | Notes |
|---|---|---|
| Rating value | score (good or bad) | Map numerical or emoji ratings into "good" or "bad". |
| Feedback comment | comment | Attach text feedback. |
| Timestamp | note text or custom field | Include "Original CSAT at [datetime] by [user]". |
Solutions Help Center
| Freshdesk field | Zendesk field | Notes |
|---|---|---|
| Category | Category | Create first. |
| Folder | Section | Map parent-child properly. |
| Article | Article | Keep HTML, rewrite asset URLs to match new host. |
| Attachments | Article attachments | Upload and relink inside HTML. |
| Tags | Labels | 1:1 mapping. |
| Translations | Translations | Match locale codes. Zendesk uses IETF BCP 47 tags (e.g., en-US, fr, de, es-419). Freshdesk uses its own locale identifiers; verify each locale against Zendesk's supported locales list before import. |
| Redirects | Redirect rules | Recreate via API if you had SEO redirects. |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Contacts / Users | medium | Email uniqueness and other_emails require separate identity handling. |
| Companies / Organizations | medium | Domain mapping and view_all_tickets visibility have no direct equivalent. |
| Tickets | medium | Requires Ticket Import API to preserve timestamps; standard API stamps current date. |
| Conversations / Comments | high | Forward threads have no native equivalent and must be appended as private notes. |
| Inline Images | high | Freshdesk URLs expire; must be re-hosted before import or images break permanently. |
| Attachments | medium | Three API calls per file (download, upload, reference); large files may be silently skipped. |
| Custom Fields | high | Dropdown values need tag-format normalization; missed transforms silently drop values. |
| Tags | medium | Must normalize to lowercase with no spaces; Freshdesk allows both. |
| Satisfaction Ratings | high | No automatic mapping; must be stored as tags or custom field values. |
| Time Entries | high | No direct Zendesk equivalent; requires manual mapping or archival. |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
Contact-to-User Split
A single Freshdesk contact with a company association must become a Zendesk user plus a separate organization membership.
Inline Image Re-hosting
Freshdesk image URLs expire. Every inline image must be downloaded, re-uploaded to Zendesk, and the HTML src rewritten.
Status Mapping Gap
Freshdesk uses 4 default statuses plus custom; Zendesk uses 6. Custom statuses require Enterprise or tag-based workarounds.
Custom Field Translation
Freshdesk cf_* field names must map to Zendesk numeric field IDs, and dropdown display values must be normalized to tag format.
Shared Rate Limit Budget
Both platforms enforce account-wide rate limits (200–700 req/min) shared across all integrations, scripts, and webhooks.
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
How long does a Freshdesk to Zendesk migration take?
Timelines depend on data volume and complexity. A small migration (under 10K tickets) typically takes 2–3 weeks. A mid-size migration (10K–100K tickets) takes 4–6 weeks. Large migrations (100K+ tickets) can take 6–10 weeks. The bulk import runtime itself is a fraction of the total — most time goes to data audit, script development, QA, and automation rebuild.
Can I migrate from Freshdesk to Zendesk without downtime?
Yes, with a delta sync strategy. Run the bulk import while your team continues working in Freshdesk, then run incremental delta syncs to capture changes. On cutover day, run a final delta sync, switch MX records, and redirect your portal DNS. The typical downtime window is under 1 hour if DNS TTL was pre-reduced.
What data gets lost in a Freshdesk to Zendesk migration?
The most common losses are inline images (Freshdesk URLs expire post-migration), large attachments silently skipped by SaaS tools, forward conversation context, satisfaction ratings, time tracking entries, and automation/workflow logic. All of these are preventable with the right migration approach, but none transfer automatically.
Do Freshdesk automations transfer to Zendesk?
No. Freshdesk automations, dispatch rules, scenario automations, and canned responses must be manually rebuilt as Zendesk triggers, automations, and macros. The concepts are similar but not 1:1 — for example, Freshdesk dispatch rules fire once on creation, while Zendesk triggers fire on every matching update unless scoped with a 'Ticket: Is Created' condition.
What is the rollback plan if the migration fails?
Zendesk does not support bulk deletion of imported tickets. The primary rollback strategy is reverting operations to Freshdesk: switch MX records back, re-enable the Freshdesk portal, and notify agents. Keep Freshdesk running in read-only mode for at least 72 hours after cutover to catch straggler emails and DNS propagation issues.