Freshchat to Unthread is a schema translation project, not a simple export/import. Use API-led ETL or a managed service when history, attachments, and routing matter.
There is no native or push-button migration path from Freshchat to Unthread. Freshchat uses a traditional omnichannel contact/conversation data model with separate agent and contact entities, while Unthread is built around a Slack-native, Customer-as-Channel architecture where all users are Slack workspace members with no agent/contact distinction. Migrating requires API-based extraction from Freshchat's REST API v2, schema transformation to reconcile fundamentally different data models (statuses, custom fields, user types), and programmatic loading into Unthread's API — making this a custom engineering project typically spanning 2–6 weeks depending on data volume and complexity.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
This migration involves a fundamental architecture shift
Freshchat is channel-agnostic with a traditional contact/conversation model. Unthread is Slack-native with a Customer-as-Channel model. Not every Freshchat concept has a 1:1 equivalent. Plan accordingly.
Timestamp warning
If original message timestamps must appear as native Unthread timestamps, prove that in a pilot first. Unthread's public create and update schemas document status, assignee, customer, notes, ticket type, metadata, and attachments, but they do not document backdated createdAt fields. Contact Unthread support to ask whether undocumented parameters exist for setting creation timestamps on imported conversations. In most migrations, the original Freshchat timestamp is preserved in metadata (e.g., metadata.originalCreatedAt) or as an inline prefix in transcript text (e.g., [2024-01-15 14:32 UTC] Original message...). (docs.unthread.io)
Freshchat uses page and items_per_page pagination parameters for some endpoints and
Freshchat uses page and items_per_page pagination parameters for some endpoints and cursor-based next_link for others. Always use the pagination.next_link URL from the response when available — do not construct pagination URLs manually. For conversations, filter by updated_since (ISO 8601 timestamp) to limit extraction to your migration scope window.
Unthread rate limits
Unthread's public API documentation does not publish a numeric rate limit as of early 2025. In practice, sustained throughput of 30–60 requests/minute has been observed as stable for conversation creation. Before running a full migration, contact Unthread support to confirm rate ceilings and request temporary limit increases for bulk imports. (docs.unthread.io)
State management is non-negotiable
Do not attempt a production migration without a local state database (SQLite for small migrations, PostgreSQL for enterprise). If your script crashes halfway through 100,000 records, you need a reliable way to resume without duplicating tickets. Make every step idempotent by checking the crosswalk table before creating any record. Quarantine bad records (log them to a failed_records table) instead of stopping the whole run.
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
-
Pull the real numbers out of Freshchat
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 Unthread can hold your support model
Walk your current workflow through Unthread: 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.
-
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 Freshchat → Unthread 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.
-
Set up Unthread first
Create your Slack workspace connection, Projects, Ticket Types, Tags, and Accounts before importing any data. These scaffolding records must exist before conversations can reference them.
-
Record count comparison
Total contacts, conversations, messages, and attachments in Freshchat vs. created records in Unthread. Every number should match or have a documented reason for the discrepancy (e.g., "47 conversations excluded: 32 spam, 15 empty"). Build a validation report that shows: source count, target count, delta, and explanation for each entity type.
Freshchat → Unthread specifics
- Slack-first workflow
- Teams already working in Slack want ticketing without forcing users into a separate portal. Freshchat requires agents to work in a dedicated dashboard; Unthread keeps everything in Slack.
- Simplicity over feature sprawl
- Unthread's focused architecture reduces admin overhead compared to Freshworks' broader suite (Freshdesk, Freshsales, Freshservice, etc.).
- AI-native resolution
- Unthread's AI agent can auto-resolve tickets directly from Slack using connected knowledge base sources, without separate bot configuration or workflow builder setup.
- Cost and licensing model
- Unthread's published pricing is $50/agent/month (Basic) and $75/agent/month (Pro), with AI included in plans rather than sold as add-ons. For teams with 10+ agents, the per-seat cost difference relative to Freshchat Enterprise ($79/agent/month) narrows, but the elimination of separate AI/bot add-on costs is the meaningful delta.
- Small business (<5K conversations)
- Move only open and recently active conversations. Direct API or a managed vendor.
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
-
Take a full Freshchat 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 Freshchat 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 Freshchat 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.
-
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
Freshchat → Unthread specifics
- Data audit
- Export a baseline count of Freshchat Contacts, Conversations, Messages, Agents, Groups, Tags, and KB articles. Identify stale or duplicate records. Record these counts — you will need them for post-migration validation.
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
-
Generate the first-pass Freshchat → Unthread 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 Freshchat → Unthread 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.
-
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 Unthread has no equivalent, decide between a new custom field, a tag, or a note appended to the ticket body — and record which.
-
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.
-
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.
-
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 Unthread sandbox that reconciles cleanly and has been reviewed by real agents.
Keep these open
-
Stand up a Unthread 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.
-
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.
-
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 Unthread'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.
-
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.
Freshchat → Unthread specifics
- Field-level spot checks
- Sample 5–10% of records (minimum 50 records) and verify:
- Operator trust (UAT)
- Have 2–3 support agents review a subset of migrated conversations in the Unthread Slack inbox. Provide them with the same conversations in Freshchat for side-by-side comparison. If agents do not trust the migrated data, the migration has not succeeded regardless of the record counts.
- KB article review
- Open imported articles in Unthread and check formatting (Markdown rendering), links (no broken URLs), embedded images, and user group assignments.
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 Unthread, agents working in the new system, and a rollback path that stayed available throughout.
Keep these open
-
Pre-load history before the freeze
Load closed tickets and contacts days or weeks ahead while Freshchat 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 Unthread'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.
-
Freeze Freshchat 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.
-
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 Freshchat read-only rather than cancelled — cancelling the old contract on day one removes your only fallback.
Freshchat → Unthread specifics
- Rollback readiness
- If the migration fails validation, have a deletion script ready that iterates through your crosswalk table and deletes all imported records via DELETE /conversations/:id. Test this script in a sandbox before production migration.
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
-
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 Freshchat and Unthread 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.
-
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.
-
Confirm compliance and produce the audit trail
Re-scan the loaded data for regulated fields, confirm retention and deletion policies are configured in Unthread, 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 Freshchat 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.
-
Rebuild automations
Recreate Freshchat assignment rules and bot flows using Unthread's automation engine (event-triggered, scheduled, or webhook-based). Document the mapping: for each Freshchat rule, record what it did, then build the Unthread equivalent. Our guide on migrating automations, macros, and workflows covers this in detail.
-
Configure SLAs and escalations
Set up Support Steps on Customers with assignment, escalation, and reminder rules. Map Freshchat's SLA tiers (response time, resolution time, business hours) to Unthread's SLA configuration.
-
Set up knowledge base sync
Connect Unthread to your documentation sources (Confluence, Notion, Google Docs, etc.) so the AI agent has up-to-date context for auto-resolution.
Freshchat → Unthread specifics
- Train your team
- Unthread's workflow lives inside Slack. Agents accustomed to Freshchat's web dashboard need hands-on onboarding for Slack-native ticket management. Budget 2–3 hours of guided training per agent. Key differences to cover: how to claim tickets, how to add internal notes, how to change status, and how to use the Unthread web dashboard for reporting.
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.
Freshchat Unthread
| Freshchat field | Unthread field | Notes |
|---|---|---|
| contact.email | user.email / Customer emailDomains | External contacts map to Customer email domains. Primary identity key for deduplication. |
| contact.first_name + last_name | user.name / Customer name | Concatenate with space delimiter. Handle null last_name gracefully. |
| contact.phone | User customAttributes | No native phone field on Unthread User. Store as custom attribute or in notes. |
| conversation.conversation_id | Conversation metadata or notes | Unthread generates its own UUIDs. Store legacy ID in metadata for traceability. |
| conversation.status | conversation.status | Map: new → open, assigned → in_progress, resolved → closed, reopened → open. Note: Unthread also supports on_hold, which has no Freshchat equivalent. |
| conversation.assigned_agent_id | conversation.assignedToUserId | Must resolve Freshchat agent ID → Unthread user ID via crosswalk table. Only map if target assignees exist in the Slack workspace. |
| conversation.label | tag.name | Create tags first via POST /tags, then link via POST /tags/:tagId/conversations/create-links. |
| conversation.custom_fields | conversation.ticketTypeFields | Requires Ticket Type setup with matching field IDs. Map cf_* keys to Ticket Type Field UUIDs. |
| conversation.priority | conversation.priority | Freshchat uses 1–4 (1=urgent). Verify Unthread's priority values match or remap. |
| message.message_type (normal/private) | message.isPrivateNote | Map private → isPrivateNote: true. |
| message.message_parts | message.body / message.markdown | Convert HTML to Markdown. Flatten bot quick replies and carousels into readable text with [Quick Reply: option_text] notation. |
| message.created_time | message.ts | See timestamp warning below. |
| message.actor_id + actor_type | Message sender identification | Resolve actor_type: "agent" via agent crosswalk, actor_type: "user" via contact crosswalk. |
| channel_id / topic | projectId + channelId or emailInboxId | Depends on whether target intake is Slack or email. Map Freshchat channels to Unthread Projects. |
| account.name | account.name | Direct mapping. |
| account.domains | account.emailsAndDomains | Freshchat may store domains differently; normalize to array format. |
| FAQ article title/body | KB article title/content | Use POST /knowledge-base/articles. Convert HTML content to Markdown. |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Conversations | high | Conversations require per-conversation message fetching via API with no bulk export, status value translation, and unconfirmed support for backdated timestamps in Unthread. |
| Messages & Threads | high | Individual message-level fidelity including sender attribution, timestamps, and threading must be preserved through API extraction since CSV exports flatten transcripts into single text blocks. |
| Contacts / Users | medium | Freshchat contacts must be mapped to either Unthread Slack-synced users or external contacts on Customer records, requiring identity matching logic across fundamentally different user models. |
| Agents | medium | Freshchat agents exist as separate API entities that must be matched to Slack workspace users in Unthread, with team structures and assignment rules requiring manual rebuild. |
| Accounts / Companies | low | Both platforms support account-level groupings, and Unthread's Accounts API accepts email domains and Slack channel IDs, making company data relatively straightforward to map. |
| Custom Fields | medium | Freshchat's cf_*-prefixed conversation and contact properties must be mapped to Unthread's Ticket Type Fields, which support only a limited set of field types (short-answer, single-select, multi-select, checkbox, user-select). |
| Tags & Labels | low | Tags and labels are simple string-based entities on both platforms and can be migrated with minimal transformation via API. |
| Knowledge Base Articles | low | Articles can be extracted and recreated via API, though Unthread's KB supports user group scoping which may require additional configuration post-migration. |
| File Attachments | medium | Attachments must be downloaded from Freshchat and re-uploaded to Unthread within its 20MB per-file limit, adding significant transfer time and storage handling for large datasets. |
| Automations & Bot Flows | high | Freshchat's assignment rules, IntelliAssign logic, and Freddy bot flows have no migration path and must be entirely rebuilt using Unthread's event-triggered, webhook, and scheduled automation framework. |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
No Native Import Path
Unthread offers no documented historical import from external platforms; its backfill is limited to 6 months of Slack channel history, requiring all Freshchat data to be migrated via API replay or a custom ETL pipeline.
Agent-Contact Model Mismatch
Freshchat separates agents and contacts into distinct API entities, while Unthread unifies all users as Slack workspace members with no agent/contact distinction, requiring identity reconciliation logic during migration.
Conversation Status Mapping
Freshchat uses status values of new, assigned, resolved, and reopened, which must be explicitly mapped to Unthread's open, in_progress, on_hold, and closed statuses with custom transformation rules.
Restrictive Export Rate Limits
Freshchat's API limits requests to approximately 100 per minute and constrains chat transcript report exports to 24-hour windows with a 15-month lookback, requiring hundreds of sequential API calls for full historical extraction.
Channel Coverage Gaps
Freshchat supports WhatsApp, Facebook Messenger, and Instagram channels that have no Unthread equivalent, meaning conversation data from these channels must be archived or lossy-transformed.
Backdated Timestamp Uncertainty
Unthread's public API documentation does not confirm support for setting backdated message timestamps, risking loss of original chronological ordering for imported historical conversations.
What breaks
Known failure modes. Have a recovery plan for each before you cut over.
Timestamp fidelity
Conversations created via the Unthread API carry their creation timestamp, not the original Freshchat timestamp. Use excludeAnalytics: true to prevent historical data from distorting Unthread's reporting. Preserve original timestamps in metadata (metadata.freshchat_created_at) or as inline prefixes in transcript text. If your use case requires exact timestamp preservation (e.g., legal or compliance reasons), escalate to Unthread support before starting the migration.
Attachment handling
Freshchat attachment URLs are signed and may expire after 24–72 hours. Download all files locally during extraction (Step 1), not during loading. Re-upload through Unthread's multipart upload endpoints. Unthread enforces a 20MB max file size and a 10-file limit per Slack message. Split attachments across multiple messages if needed. Track attachment download failures separately — these are the most common silent data loss. (developers.freshchat.com)
Chat transcripts as single blocks
Freshchat CSV exports flatten entire chat transcripts into one description field with HTML formatting. You must parse these into individual messages (regex on timestamp patterns like [HH:MM] or <div class="message">) before importing, or accept losing per-message granularity.
Slack ID resolution
If you migrate a Freshchat user without a matching Slack ID, Unthread treats them as an email-based user. If they later join your Slack Connect channel, you risk creating duplicate profiles. Plan your identity resolution strategy before you start loading data: build a lookup table of email → Slack user ID from your Slack workspace before migration.
Multi-channel data loss
Freshchat conversations from WhatsApp, Instagram, or Messenger have no native Unthread equivalent. Import these as triage-type conversations with the original channel noted in metadata (metadata.original_channel: "whatsapp"). Alternatively, archive them as read-only JSON exports outside Unthread.
Customer model mismatch
Freshchat contacts are standalone records with email and phone. Unthread Customers are tied to Slack channels via slackChannelIds or email domains via emailsAndDomains. If you do not have shared Slack channels for every Freshchat contact, create triage-type or email-type conversations and associate customers via email domain matching.
Bot payloads
Freshchat quick replies, carousels, and attachment input constructs do not have a clean 1:1 Unthread equivalent. Flatten them into readable transcript text with bracket notation: [Quick Reply: option_text], [Carousel: card_title]. This preserves the information without breaking Unthread's message parser. (developers.freshchat.com)
Duplicate identities
One customer may exist as multiple Freshchat users with shared email domains or missing emails. Neither platform provides built-in deduplication during import. Build email-based matching logic into your transformation layer: normalize emails to lowercase, strip plus-addressing (e.g., user+tag@domain.com → user@domain.com), and merge contacts sharing the same normalized email.
Assignment and routing mismatch
Freshchat's group/agent model and complex routing rules (including IntelliAssign's skill-based and load-balanced routing) do not drop cleanly into Unthread's workspace model. Document your current routing logic before migration, then rebuild using Unthread's automation engine with event-triggered rules.
Freshchat report constraints
Native raw-report export is not a complete historical extraction strategy: start dates cannot be earlier than 15 months from current, end dates cannot exceed one month after start, and the Chat-Transcript report is limited to 24-hour windows. Use the API for extraction instead. (developers.freshworks.com)
Unthread rate limits
Unthread's public API docs do not publish a numeric rate limit. Empirically, 30–60 requests/minute for conversation creation has been stable. For enterprise backfills (50K+ records), throttle conservatively, implement exponential backoff on any non-2xx response, and confirm ceilings with Unthread support before running the full job. (docs.unthread.io)
Bulk deletion for rollback
Unthread's API documents individual DELETE /conversations/:id but does not document a bulk deletion endpoint. If you need to roll back a failed import, script individual deletions using your crosswalk table. At 30–60 requests/minute, deleting 50K records takes 14–28 hours. Factor this into your rollback plan.
Multi-workspace and multi-brand
If you run multiple Freshchat accounts (e.g., per brand or per region), each maps to a separate Unthread workspace or separate Projects within one workspace. Unthread's Project model supports this, but each Project needs its own Slack channel. Plan your Slack channel structure before migration.
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
Can I export Freshchat conversations to CSV for Unthread import?
Freshchat can export contacts as CSV/XLSX, but conversation exports flatten chat transcripts into single text blocks — individual messages are lost. Unthread has no CSV import for conversations. For full message-level fidelity, extract via Freshchat's REST API and import into Unthread's POST /conversations and POST /conversations/:id/messages endpoints.
Can I migrate Freshchat conversations into Unthread with original timestamps?
Not as native historical timestamps through Unthread's public API. The create and update schemas do not document backdated createdAt fields. Most teams preserve original Freshchat timestamps in metadata, notes, or inline transcript text instead. Use excludeAnalytics: true to prevent migrated data from distorting Unthread's reporting.
What Freshchat data cannot be migrated to Unthread?
Freshchat channels like WhatsApp, Instagram, and Facebook Messenger have no native Unthread equivalent. Historical SLA metrics, analytics dashboards, IntelliAssign configurations, bot flow logic, and CSAT ratings must be rebuilt manually. Bot quick replies and carousels need to be flattened into plain text. CRM-adjacent data from Freshsales should stay in the CRM or be migrated separately.
How do I handle Freshchat attachments when moving to Unthread?
Freshchat attachment URLs may expire. Download files locally during extraction and re-upload them through Unthread's multipart upload endpoints. Unthread enforces a 20MB max file size and a 10-file limit per Slack message. Split larger attachment sets across multiple messages.
How long does a Freshchat to Unthread migration take?
For small accounts (under 5,000 conversations), expect 3–5 days of engineering effort for scripting, transformation, and validation. Larger accounts with 50,000+ conversations and complex custom fields may take 2–4 weeks for a DIY migration, or days with a managed migration service like ClonePartner.