No native importer exists between Freshdesk and SurveySparrow. Migrate via custom API scripts — extract from Freshdesk v2, transform, load through SurveySparrow v3.
Migrating from Freshdesk to SurveySparrow Ticket Management requires a fully custom API-to-API pipeline, as no native importer, verified third-party connector, or bulk migration tool currently exists for this path. Freshdesk is a full-lifecycle enterprise helpdesk built around tickets as a central relational entity — linked to contacts, companies, groups, SLA policies, products, and hierarchical ticket relationships — while SurveySparrow Ticket Management is a flatter, feedback-first module designed around survey responses and NPS data, lacking native concepts for companies, products, ticket types, and tags. Data must be extracted via Freshdesk REST API v2, structurally transformed to match SurveySparrow's schema, and loaded through SurveySparrow API v3, with the critical caveat that SurveySparrow's Create Ticket API does not accept historical timestamps, making all imported tickets appear as if they were created at migration time. Custom fields, careful field mapping, and bespoke scripting are required at every stage to avoid orphaned records, data truncation, and silent data corruption.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
No native importer exists
Do not attempt to use SurveySparrow's standard CSV import for a full helpdesk migration. The CSV importer only captures the initial ticket body — it cannot thread historical replies, map inline attachments, or preserve private notes. The SurveySparrow app on the Freshworks Marketplace is for triggering surveys from Freshdesk events, not importing ticket history. Plan for a custom API-to-API migration from day one.
Even failed requests count
A 401 from a bad key or a 400 from a malformed body still consumes a call against your rate limit. Validate payloads before sending.
Batch is faster but limited
The batch endpoint is significantly faster for creating tickets without attachments, but you lose the ability to set template_id or upload files. If your migration includes attachments, you must use the single-ticket endpoint and handle rate limiting carefully.
Status and priority integers are not universal
Freshdesk uses 2 for Open and 1 for Low priority. SurveySparrow uses its own integer mapping. Fetch SurveySparrow's status/priority definitions from the Ticket Fields API and build an explicit mapping table before writing any transformation code. Assuming the integers match will silently misclassify every ticket in the migration.
Checkpoint as you go
Write extracted tickets to a local JSON file or database after each page. If the script fails at page 200, you don't want to re-extract pages 1–199. Store the last successfully processed updated_at value — you'll need it for delta sync.
Author attribution
Comments created via API are attributed to the API user making the request. Preserve original authorship by prepending [Originally posted by: Name — Date] to each comment body. Map the Freshdesk private boolean directly to the is_private field to preserve internal notes vs. customer-visible replies.
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 Surveysparrow Ticket Management can hold your support model
Walk your current workflow through Surveysparrow Ticket Management: 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 → Surveysparrow Ticket Management 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.
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Disable outbound webhooks
in SurveySparrow Settings → Integrations before running any bulk import. A migration of 10,000 tickets will fire 10,000 webhook events to every connected downstream system (Slack, email notifications, third-party apps). Re-enable after validation.
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Create users
matching your Freshdesk agents and map their IDs.
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Create contacts
matching Freshdesk contacts/requesters. Use the SurveySparrow Contacts API (POST /v3/contacts). When a contact with the same email already exists in SurveySparrow, the API will return a conflict. Implement a lookup-first pattern: query GET /v3/contacts?email={email} before creating. If a match is found with differing field values (e.g., different name or phone), log the conflict and apply a defined merge policy (Freshdesk values overwrite, or SurveySparrow values win) rather than creating a duplicate.
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
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 → Surveysparrow Ticket Management 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 → Surveysparrow Ticket Management 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 Surveysparrow Ticket Management 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.
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Verify custom field values
didn't get silently dropped: check freshdesk_id, original_created_at, tags, and ticket_type on a sample set.
Freshdesk → Surveysparrow Ticket Management specifics
- Truncates subjects
- to 200 characters and logs each truncation with the original text.
- Strips or converts unsupported attachment types
- Log any skipped attachments and upload them to external storage (S3, GCS) with a link appended to the ticket description.
- Resolves requester IDs
- match Freshdesk requester_id to the SurveySparrow contact_id you created in Step 2, using email as the join key.
- Resolves agent/group IDs
- map Freshdesk responder_id → SurveySparrow assignee_id, and group_id → team_id.
- Packs unmapped fields into custom fields
- freshdesk_id, original_created_at, ticket type, tags, company name.
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 Surveysparrow Ticket Management sandbox that reconciles cleanly and has been reviewed by real agents.
Keep these open
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Stand up a Surveysparrow Ticket Management 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 Surveysparrow Ticket Management'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 Surveysparrow Ticket Management, 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 Surveysparrow Ticket Management'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.
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 Surveysparrow Ticket Management 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 Surveysparrow Ticket Management, 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.
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Check attachment presence
on tickets that had them in Freshdesk. Verify file type handling — confirm unsupported types were either converted or linked.
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Verify no webhook storms occurred
Check your downstream systems (Slack, email) for unexpected notification volume during the import window.
Freshdesk → Surveysparrow Ticket Management specifics
- Count match
- Query GET /api/v2/tickets?per_page=1 (read X-Total-Count header) vs total tickets in SurveySparrow. Include archived tickets in the Freshdesk count.
- Conversation count match
- For a sample of 50–100 tickets, compare Freshdesk conversation count vs SurveySparrow comment count.
- Spot-check 20–50 tickets
- across different statuses, priorities, agents, and date ranges. Prioritize tickets that had attachments, inline images, private notes, and custom fields.
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.
Freshdesk SurveySparrow
| Freshdesk field | Surveysparrow Ticket Management field | Notes |
|---|---|---|
| id | Custom field: freshdesk_id | Essential for idempotency checks and audit trail |
| subject | subject | Truncate to 200 chars; log any truncations |
| description / description_text | description | HTML or plain text — test both with your template config |
| status (integer) | status (integer) | Integers differ between platforms — build explicit lookup table |
| priority (integer) | priority (integer) | Integers may differ — verify against SurveySparrow Ticket Fields API |
| requester_id | requester_id or email | Must pre-create contacts in SurveySparrow first |
| responder_id | assignee_id | Map Freshdesk agent → SurveySparrow user ID |
| group_id | team_id | Map Freshdesk group → SurveySparrow team |
| type | Custom field | SurveySparrow has no native ticket type |
| source | source | Map integer values |
| tags | Custom field (multiselect or text) | No native tag field on SurveySparrow tickets |
| company_id | Custom field | No native company concept on SurveySparrow tickets |
| product_id | Custom field | No multi-product support |
| custom_fields.* | custom_fields.* | Pre-create matching fields; map internal names |
| created_at | Custom field: original_created_at | Store as ISO 8601 string |
| updated_at | Custom field: original_updated_at | Store as ISO 8601 string |
| due_by | Custom field or SLA config | No direct equivalent |
| cc_emails | Custom field (text) | Store as comma-separated string; SurveySparrow handles collaboration differently |
| conversations | Ticket Comments API | Each conversation becomes a separate comment |
| attachments | attachments on single create | File type + size restrictions apply |
Volume Estimated Duration
| Freshdesk field | Surveysparrow Ticket Management field | Notes |
|---|---|---|
| < 1,000 tickets | 1–2 days | Script development + single run |
| 1,000–10,000 tickets | 3–5 days | Chunked extraction, batch loading |
| 10,000–50,000 tickets | 1–2 weeks | Rate limit pacing dominates; time-windowed extraction required |
| 50,000–100,000 tickets | 2–4 weeks | Consider Account Export for initial pull + API for conversations |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Tickets | medium | Core ticket fields map reasonably well between platforms, but subject truncation at 200 characters, loss of ticket type, and incorrect system timestamps introduce structural data quality issues for every migrated record. |
| Conversations (Replies & Notes) | high | Freshdesk conversations are stored as separate API objects and must be fetched individually per ticket then re-posted via SurveySparrow's Ticket Comments API, dramatically increasing API call volume and creating orphaned comment risk if ticket creation fails or IDs are mismatched. |
| Contacts | medium | Freshdesk contacts include relational company linkages that SurveySparrow does not natively support, resulting in a flat contact model on import with company context either lost or demoted to a custom field. |
| Companies | high | SurveySparrow Ticket Management has no native company entity, meaning all Freshdesk company data must be discarded, mapped to custom fields, or handled via external reference, with no guarantee of relational integrity post-migration. |
| Custom Fields | medium | Both platforms support a `custom_fields` object on tickets, but field names must match exactly in SurveySparrow and all target custom fields must be pre-created before migration, with any name mismatch causing silent data loss or 422 errors. |
| Attachments | high | SurveySparrow enforces a 15 MB file size limit and restricts accepted file types to pdf, png, jpeg, mp3, csv, and wav, meaning unsupported Freshdesk attachment formats will be blocked entirely and oversized files must be split or excluded before migration. |
| Tags | high | Freshdesk treats tags as a first-class array on tickets, but SurveySparrow has no native tag field, requiring tags to be either concatenated into a custom field string or abandoned, with no native filtering or reporting capability preserved post-migration. |
| Ticket Hierarchy (Parent/Child) | medium | SurveySparrow supports parent/child ticket ID references, but Freshdesk's additional tracker ticket concept has no equivalent, and hierarchy relationships can only be re-established after all parent tickets are successfully created and their new SurveySparrow IDs are known. |
| Historical Timestamps | high | SurveySparrow's Create Ticket API ignores `created_at` and `updated_at` values, so all migrated tickets carry the migration execution date as their system timestamp, making native date-based sorting, filtering, and reporting unreliable unless custom fields are used as a substitute. |
| Archived Tickets | medium | Freshdesk automatically archives tickets inactive for more than 120 days and excludes them from the standard List Tickets endpoint, requiring a separate archive endpoint query to avoid silently omitting potentially years of historical ticket data from the migration. |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
No Native Migration Path
No native importer, verified third-party connector, or marketplace tool supports bulk historical migration from Freshdesk to SurveySparrow Ticket Management, requiring a fully custom API-to-API pipeline from day one.
Historical Timestamp Preservation
SurveySparrow's Create Ticket API does not accept `created_at` or `updated_at` parameters, so all imported tickets receive the migration date as their creation timestamp, requiring custom fields to preserve original Freshdesk timestamps for accurate reporting.
Threaded Conversation Reconstruction
Freshdesk stores conversations as separate objects fetched via a dedicated endpoint per ticket, while SurveySparrow uses a distinct Ticket Comments API, requiring a multi-step create-then-comment workflow that multiplies total API calls and rate limit exposure.
Structural Data Model Mismatch
Freshdesk entities including companies, products, ticket types, tags, SLA policies, and parent-child-tracker ticket hierarchies have no direct equivalents in SurveySparrow's flatter schema, forcing lossy translation or custom field workarounds for every affected entity.
Freshdesk Pagination and Archive Limits
The Freshdesk List Tickets endpoint is hard-capped at 300 pages (~30,000 tickets), and archived tickets require a separate endpoint, meaning accounts with large or aged datasets must implement time-windowed extraction strategies to avoid silently incomplete exports.
Attachment Compatibility and Size Constraints
SurveySparrow restricts attachments to specific file types (pdf, png, jpeg, mp3, csv, wav) with a 15 MB per-file limit and does not support attachments via the batch creation endpoint, requiring per-ticket multipart uploads and pre-migration validation of all Freshdesk attachment types and sizes.
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
Is there a native migration tool from Freshdesk to SurveySparrow?
No. The SurveySparrow integration on the Freshworks Marketplace only triggers surveys from Freshdesk ticket events. It does not import historical ticket data. Every migration requires a custom API-to-API approach using Freshdesk's REST API v2 for extraction and SurveySparrow's v3 API for loading.
Can SurveySparrow preserve original Freshdesk ticket timestamps?
Not directly. SurveySparrow's Create Ticket API does not accept created_at or updated_at parameters. Imported tickets will carry the import date as their creation timestamp. To preserve original dates, store them in custom fields like original_created_at on the SurveySparrow ticket.
What Freshdesk data is lost when migrating to SurveySparrow?
SurveySparrow Ticket Management has no native equivalent for Freshdesk ticket types, tags, companies, products, or multi-product routing. These values must be stored in custom fields or dropped. Attachment support is limited to pdf, png, jpeg, mp3, csv, and wav files with a 15 MB max. Unsupported file types need alternative handling.
Does SurveySparrow's batch ticket API support attachments?
No. The POST /v3/tickets/batch endpoint accepts JSON and does not support file uploads. Tickets with attachments must be created one at a time using the single-ticket POST /v3/tickets endpoint with multipart/form-data.
How long does a Freshdesk to SurveySparrow migration take?
For under 1,000 tickets, expect 1–2 days including script development. For 10,000–50,000 tickets, plan for 1–2 weeks due to rate limit pacing on both platforms. The extraction side is typically the bottleneck since Freshdesk conversations require one API call per ticket.