Migrating LiveAgent to Unthread requires API-to-API extraction — no native import path. Plan for 180 RPM rate limits, contact-to-account flattening, and HTML-to-Markdown conversion.
There is no native migration path between LiveAgent and Unthread — no built-in import wizard, no direct export bridge, and no first-party integration for data transfer. The fundamental data model clash centers on LiveAgent's ticket-and-contact architecture versus Unthread's Slack-native, conversation-and-account model, where LiveAgent Contacts (individual people) have no direct equivalent in Unthread's object schema. Every migration requires extracting data via LiveAgent's REST API or database dump, transforming it to fit Unthread's object model, and loading it through Unthread's API — making this a custom schema translation project requiring API/ETL engineering or a managed migration service.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
Critical decision
When importing historical tickets, use type: "triage" to create internal-only records and avoid flooding Slack channels with old conversations. For tickets that should appear in Slack channels, use type: "slack" with the appropriate channelId.
Store source IDs in metadata
Map ticket.id and ticket.code from LiveAgent into the metadata field on Unthread conversations. This creates a traceable link back to the source record for validation and debugging.
Attachment edge case
LiveAgent attachment URLs require authentication. You cannot pass the LiveAgent URL to Unthread directly. You must download the binary file during the ETL process and re-upload it to Unthread's storage.
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 LiveAgent
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.
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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 LiveAgent → 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.
LiveAgent → Unthread specifics
- Slack-first operations
- The support team already lives in Slack. LiveAgent's Slack integration sends notifications, but it doesn't make Slack the primary support interface. Unthread does.
- Simplified tooling
- LiveAgent's feature surface (call center, social media, contact forms, gamification) is overkill for teams that only need Slack-based ticketing with SLAs, routing, and AI deflection.
- AI-native automation
- Unthread offers AI-driven triage and automated knowledge base article generation from resolved tickets.
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 LiveAgent 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 LiveAgent 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 LiveAgent 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 LiveAgent → 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 LiveAgent → 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.
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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 Unthread 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 Unthread sandbox that reconciles cleanly and has been reviewed by real agents.
Keep these open
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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.
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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 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.
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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 Unthread, 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 LiveAgent 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.
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Freeze LiveAgent 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 LiveAgent 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 LiveAgent 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.
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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 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 LiveAgent 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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Rebuild automations
LiveAgent rules (time rules, SLA rules, ticket routing) must be recreated as Unthread Automations using the trigger/step model. Treat this as a separate workstream.
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Configure SLAs
Set up SLA policies in Unthread's workflow management for each Customer/Account.
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Monitor for gaps
Run daily count comparisons for the first two weeks. Watch for conversations missing tags, unlinked accounts, duplicate email threads, or failed attachment uploads. Use Unthread webhooks to monitor conversation creation events and confirm routing rules are firing correctly.
LiveAgent → Unthread specifics
- Recreate canned responses
- LiveAgent's canned messages and predefined answers become Unthread Templates & Canned Responses.
- Knowledge Base sync
- Connect documentation sources in Unthread's Knowledge Base settings for AI-powered responses.
- Reconfigure email
- Set up email forwarding, domain verification, portal authentication, and project permissions.
- Train agents
- Unthread operates from Slack — agents need to learn the thread-based workflow, /unthread commands, /unthread send for email replies, and the web inbox. Moving from a traditional portal to Slack requires behavioral changes. Budget 2–3 training sessions.
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 Equivalent
| LiveAgent field | Unthread field | Notes |
|---|---|---|
| Ticket | Conversation | Core mapping. Statuses differ (see mapping table below). |
| Contact | Account or Customer (partial) | LiveAgent contacts are people; Unthread Customers are Slack channels. Accounts are the closest org-level equivalent. |
| Company | Account | Unthread Accounts hold org-level data: name, domains, Slack channels, support assignees. |
| Department | Project | Unthread Projects scope conversations, users, and settings. |
| Agent | User | Unthread Users are synced from Slack workspace membership. |
| Tag | Tag | Direct mapping. |
| Custom Ticket Fields | Ticket Type Fields | LiveAgent allows unlimited custom fields globally; Unthread scopes custom fields to Ticket Types. |
| Custom Contact Fields | Account Custom Fields (partial) | Limited mapping. Unthread Accounts support customFields but the schema is less flexible. |
| Knowledge Base Article | Knowledge Base Article | Direct API-to-API mapping available. |
| Canned Messages / Predefined Answers | Templates & Canned Responses | Manual recreation typically needed. |
| SLA Rules | SLA configuration | Rebuilt in Unthread, not migrated as data. |
| Automation Rules | Automations | Rebuilt, not migrated. Unthread automations use a different trigger/step model. |
LiveAgent Unthread
| LiveAgent field | Unthread field | Notes |
|---|---|---|
| ticket.id | conversation.metadata.sourceId | Store as metadata for traceability |
| ticket.code | conversation.metadata.sourceCode | Store as metadata |
| ticket.subject | conversation.title | Direct; default to "(no subject)" if null |
| ticket.status | conversation.status | Map: N/T/C/W→open, A→in_progress, P→on_hold, R/X/B→closed |
| ticket.date_created | conversation.metadata.sourceCreatedAt | Cannot backdate; store in metadata |
| ticket.department_id | conversation.projectId | Map departments to Projects |
| ticket.owner_contactid | conversation.customerId | Map via Account/Customer lookup |
| ticket.agent_id | conversation.assignedToUserId | Map LiveAgent agents to Unthread Users (matched by email) |
| ticket.tags | conversation.tags | Map tag names → Unthread tag IDs |
| ticket.custom_fields | conversation.ticketTypeFields | Map per Ticket Type schema |
| contact.email | account.emailsAndDomains | Direct |
| contact.name | account.name | Direct (or concatenate first+last) |
| company.name | account.name | Direct |
| message.body | message.body.value | HTML → Slack mrkdwn conversion (see degradation notes in Step 3) |
| kb_article.title | article.title | Direct |
| kb_article.content | article.content | HTML → Markdown |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Tickets (Conversations) | medium | Core ticket metadata maps to Unthread Conversations, but status values differ and the 10,000-record API cap requires date-range windowing for larger datasets. |
| Contacts | high | Unthread has no direct contact object; individual contact records must be flattened into Accounts or encoded as metadata, resulting in potential data loss for person-level fields. |
| Companies (Accounts) | low | LiveAgent Companies map directly to Unthread Accounts, with Accounts supporting org-level data including name, domains, and Slack channels. |
| Custom Fields | high | LiveAgent's globally scoped custom fields must be restructured to fit Unthread's Ticket Type-scoped field model, and contact custom fields have only partial mapping to Account custom fields. |
| Tags | low | Tags have a direct one-to-one mapping between LiveAgent and Unthread with API support on both sides. |
| Departments (Projects) | medium | LiveAgent Departments map to Unthread Projects, but project-level scoping of conversations, users, and settings requires careful configuration beyond simple data transfer. |
| Knowledge Base Articles | low | Direct API-to-API mapping is available for knowledge base articles, making this one of the more straightforward entities to migrate. |
| Attachments | high | Attachments are excluded from CSV exports, require manual download from LiveAgent, and older data moved to S3 may complicate extraction timing. |
| Automation Rules | high | Automations cannot be migrated as data and must be entirely rebuilt in Unthread's different trigger/step model, requiring significant manual effort. |
| Canned Messages (Templates) | medium | LiveAgent predefined answers and canned messages typically require manual recreation in Unthread's templates and canned responses system. |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
Contact-to-Account Schema Mismatch
LiveAgent Contacts are individual people with emails and phone numbers, but Unthread has no direct contact object — its Customer represents a Slack channel and its Account represents an organization, requiring flattening or metadata mapping.
API Rate Limit Constraints
LiveAgent's API enforces a 180-requests-per-minute rate limit and caps the /tickets endpoint at 10,000 records per filter, requiring date-range windowing and extended extraction times for larger datasets.
Custom Fields Scope Differences
LiveAgent allows unlimited global custom ticket fields, while Unthread scopes custom fields to specific Ticket Types, requiring a restructuring of the custom field schema during migration.
CSV Export Data Incompleteness
LiveAgent's CSV export captures ticket metadata but omits full message bodies, attachments, and custom fields, making it insufficient for any migration requiring message-level fidelity.
Automation and SLA Rebuilds
LiveAgent's automation rules and SLA configurations cannot be migrated as data and must be manually rebuilt in Unthread, which uses a fundamentally different trigger/step automation model.
Attachment and Storage Handling
LiveAgent moves data older than 7 days to AWS S3 storage, and attachments must be manually downloaded and re-uploaded since there is no direct attachment transfer between the two platforms.
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
Can I import data directly into Unthread from LiveAgent?
No. There is no native migration path, CSV import, or built-in wizard in Unthread for importing LiveAgent data. You must extract via LiveAgent's REST API (v1 or v3) and load via Unthread's REST API, or use a managed migration service.
What is LiveAgent's API rate limit for data extraction?
LiveAgent's API rate limit is 180 requests per minute per API key. The v3 /tickets endpoint also caps at 10,000 records per filter set, so you need date-range windowing for larger datasets.
How do LiveAgent contacts map to Unthread?
Unthread has no standalone contact object. LiveAgent contacts are individual people with emails and phone numbers. In Unthread, you map companies to Accounts (which hold emailsAndDomains and Slack channels) and flatten individual contact records into Account metadata.
Can I backdate conversations in Unthread during migration?
No. Unthread's createdAt timestamp is set when the conversation is created via API. You cannot inject a historical date. Store the original LiveAgent creation date in the conversation's metadata field for reference.
What data does not map cleanly from LiveAgent to Unthread?
Custom fields require remodeling into Ticket Type Fields. Voice/call data, social channel history (Facebook, WhatsApp, Twitter), and internal notes all need special handling. Unthread also caps attachments at 10 files per message and 20MB per file, so large attachment sets must be split across multiple API calls.