LiveAgent to Freshservice is a platform-class conversion from a customer help desk to an ITIL-based ITSM tool. API-driven migration is the only reliable path for full conversation history.
Migrating from LiveAgent to Freshservice is a fundamental data-model conversion, not a simple data copy — LiveAgent is an omnichannel external customer support platform, while Freshservice is an ITIL-aligned internal IT Service Management (ITSM) system. No native migration path exists between the two platforms, and there is no one-to-one object mapping: LiveAgent Contacts (external customers) must be reframed as Freshservice Requesters (internal employees), LiveAgent Departments (routing groups) map to Freshservice Groups rather than Departments, and LiveAgent Companies have no direct Freshservice equivalent. Conversation history stored as typed messages in LiveAgent must be reconstructed into Freshservice's split reply-and-note conversation model, and attachments require separate download and re-upload rather than URL reference transfer. Custom scripting or a third-party migration service is required to preserve full ticket history, maintain entity relationships, and suppress automation storms during import.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
Architecture mismatch alert
LiveAgent's Contacts are external customers; Freshservice's Requesters are internal employees. LiveAgent's Departments route tickets to agent teams; Freshservice's Departments represent organizational structure. Every record must be conceptually reframed before import.
Timezone gotcha
LiveAgent's API v3 returns dates in your account's configured timezone, not UTC. You must either add a Timezone-Offset header to API calls or convert timestamps in your transformation layer before loading into Freshservice, which expects ISO 8601 format. See the normalize_timestamp() function in the code samples below.
Bulk migration APIs
For partner-grade migrations, Freshservice exposes bulk APIs that support tickets and notes only. These require a migration token, allow 50 tickets or notes per request, run at 10 requests per minute, and require attachments to be publicly accessible by URL (capped at 40 MB total per entity). All other entities use standard public APIs. (support.freshservice.com)
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 Freshservice can hold your support model
Walk your current workflow through Freshservice: 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 → Freshservice 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 → Freshservice specifics
- Internal IT consolidation
- The organization is retiring a customer-support tool repurposed for internal IT ticketing and wants a purpose-built ITSM platform with proper change management and asset tracking.
- ITIL compliance
- LiveAgent has no native support for problems, changes, releases, or a CMDB. Freshservice provides these out of the box.
- Enterprise service management (ESM)
- Freshservice extends service management to HR, Facilities, Legal, and Finance departments — use cases LiveAgent was never designed for.
- Tool consolidation
- Merging disparate customer support and IT teams into a single Freshworks ecosystem.
- AI-powered triage
- Freshservice's Freddy AI provides ticket triage, summarization, and a virtual agent in Slack and Microsoft Teams. LiveAgent's automation is rule-based with no native AI.
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 → Freshservice 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 → Freshservice 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 Freshservice 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 Freshservice sandbox that reconciles cleanly and has been reviewed by real agents.
Keep these open
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Stand up a Freshservice 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 Freshservice'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.
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Create a sandbox
In Freshservice Admin → Sandbox, provision a sandbox instance. Freshservice Pro and Enterprise plans include sandbox access.
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Run the full migration
against the sandbox using the same scripts and mappings.
LiveAgent → Freshservice specifics
- Replicate configuration
- Copy your production custom fields, groups, departments, and categories to the sandbox. Freshservice sandboxes can sync configuration from production.
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 Freshservice, 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 Freshservice'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 Freshservice 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 Freshservice, 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.
Don't move on until
- Full reconciliation report attached to the project record
- Reporting baselines match pre-migration figures within agreed tolerance
- Formal acceptance signed and archive retention scheduled
Field mapping reference
The field-by-field mapping for each object. Use this as the starting point for your mapping spec.
Object Object
| LiveAgent field | Freshservice field | Notes |
|---|---|---|
| Ticket | Ticket (Incident/Service Request) | Status values differ. LiveAgent uses letter codes (N/T/A/P/R/X). Freshservice uses numeric codes (2=Open, 3=Pending, 4=Resolved, 5=Closed). See LiveAgent API v3 ticket status reference. |
| Contact | Requester | External customers → internal employees. Email is the join key. |
| Company | Department (or discard) | No direct equivalent. See decision framework below. |
| Department | Group | LiveAgent departments route tickets to agent teams. Freshservice Groups serve the same function. |
| Agent | Agent | Map by email. Agent roles may differ between platforms. |
| Tag | Tag | Direct mapping, but verify no naming conflicts. |
| Custom Ticket Field | Custom Ticket Field | Type-by-type mapping required. Not all LiveAgent field types exist in Freshservice. |
| Knowledge Base Article | Solution Article | Category/folder structure must be recreated first. |
| Canned Message / Predefined Answer | Canned Response | No API import path. Must be rebuilt manually. |
| Chat Transcript | Ticket Note (or discard) | Freshservice has no native chat object. Chat history can be appended as ticket notes. |
| Call Recording | Attachment on Ticket | No native call object in Freshservice. Attach as file. |
| SLA Rules | SLA Policy | Cannot be migrated. Rebuild in Freshservice. |
| Automation Rules | Workflow Automator | Cannot be migrated. Rebuild in Freshservice. |
LiveAgent Freshservice
| LiveAgent field | Freshservice field | Notes |
|---|---|---|
| subject | subject | Direct map |
| status (N/T/A/P/R/X) | status (2/3/4/5) | N→2 (Open), T→2, A→3 (Pending), P→3, R→4 (Resolved), X→5 (Closed). See LiveAgent API v3 docs. |
| departmentid | group_id | Lookup against pre-created Groups |
| agentid | responder_id | Lookup against pre-created Agents by email |
| date_created | created_at | Freshservice accepts ISO 8601. Timezone conversion required (see code below). |
| date_resolved | resolved_at | Same timezone handling |
| tags | tags | Array of strings |
| priority | priority (1=Low, 2=Medium, 3=High, 4=Urgent) | Map to numeric values |
| Custom fields | custom_fields | Key-value pairs. Freshservice custom field API names are prefixed with cf_. |
LiveAgent Freshservice
| LiveAgent field | Freshservice field | Notes |
|---|---|---|
| Ticket ID | Legacy ID (custom) | Crosswalk, reruns, audit |
| Ticket Code | Subject prefix | Prepend [LA-{code}] for searchability |
| Subject | Subject | Trim and normalize whitespace. Default to (No Subject) if empty. |
| Status | Status | Value mapping required. See LiveAgent API v3 docs. |
| Priority | Priority | Map to numeric values |
| Department | Group | Lookup by pre-created Group ID |
| Agent | Responder | Match by email with fallback queue |
| Contact Email | Requester Email | Lowercase + dedupe. Must be unique. |
| Contact Name | Requester Name | Split fields |
| Company | Department / custom field | See Companies-to-Departments decision framework |
| Tags | Tags | Array of strings, verify naming conflicts |
| Created Date | Created At | Timezone conversion required via normalize_timestamp() |
| First message body | Description | Preserve HTML safely |
| Later public messages | Conversation reply/note | Keep order by created time |
| Internal notes | Private note | Mark non-public to prevent leakage |
| Attachments | Ticket/note attachments | Stage to public URL if using bulk API. 15 MB per file limit. |
| Custom Field | Custom Field | Freshservice prefixes with cf_ |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Tickets | high | LiveAgent's ticket snapshot exports drop full conversation threads and custom fields, and API retrieval is capped at 10,000 records per filtered request, making complete high-fidelity ticket migration technically complex and prone to silent data loss without custom pipeline logic. |
| Conversation History | high | LiveAgent messages must be individually fetched, typed as replies or private notes, and replayed in chronological order against Freshservice's conversation model — any gap in fetch logic results in permanently incomplete or misordered ticket threads. |
| Attachments | high | Attachments are not transferred by reference; each file must be independently downloaded from LiveAgent and re-uploaded to Freshservice, and URL-based references may expire during the migration window, causing irreversible data loss. |
| Contacts / Requesters | high | LiveAgent Contacts represent external customers while Freshservice Requesters represent internal employees, meaning every contact record requires semantic validation and manual or scripted reframing before import, and tickets imported without valid requester IDs will fail or be assigned to a default user. |
| Companies | medium | LiveAgent Companies have no direct equivalent in Freshservice and must be evaluated per-implementation to determine whether they map to Freshservice Departments, are discarded, or are stored in a custom object, requiring a documented decision framework before migration begins. |
| Departments / Groups | medium | LiveAgent Departments function as ticket-routing groups and map to Freshservice Groups rather than Freshservice Departments, which represent organizational structure — incorrect mapping results in broken ticket assignments and misrouted escalations post-migration. |
| Custom Fields | medium | Custom fields that do not have a matching field type or schema in Freshservice are silently dropped during import rather than triggering errors, requiring pre-migration field audits and manual creation of target fields before any data transfer begins. |
| Tags | low | Tags are transferable via both the LiveAgent API v3 and Freshservice API v2 as plain string arrays and carry no relational dependencies, though tag taxonomy normalization may be needed if naming conventions differ between the two platforms. |
| Knowledge Base Articles | medium | LiveAgent knowledge base articles can be extracted via API but must be remapped to Freshservice's Solution Article schema including category and folder hierarchy, and embedded media or attachments within articles require the same separate download-and-re-upload treatment as ticket attachments. |
| Agent / User Accounts | low | Agent accounts can generally be pre-created in Freshservice via the Requester or Agent API before migration begins, though agent attribute mappings such as roles, groups, and permissions must be manually reconfigured to align with Freshservice's ITIL-based access model. |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
Semantic Data Model Mismatch
LiveAgent's core entities — Contacts, Companies, and Departments — do not map directly to Freshservice's Requesters, organizational Departments, and Groups, requiring conceptual reframing and custom transformation logic for every record type before import.
Conversation Thread Reconstruction
LiveAgent stores ticket history as typed messages in a single thread, while Freshservice separates conversations into discrete replies and private notes, meaning every message must be fetched, typed, ordered, and replayed individually to preserve thread integrity.
Attachment Orphaning Risk
Attachments in LiveAgent are referenced by URLs that may expire or require authentication, necessitating a separate download-and-re-upload pipeline rather than a simple reference transfer to avoid broken or missing files in Freshservice.
API Rate Limit Constraints
LiveAgent enforces a cap of 180 requests per minute and limits ticket retrieval to 10,000 records per filtered request, while Freshservice throttles at 100–500 requests per minute depending on plan tier, requiring throttle-aware batching and retry logic throughout the migration pipeline.
Automation Storm Suppression
Unless Freshservice workflows, business rules, and notification triggers are explicitly deactivated prior to import and the bypass_mandatory parameter is used, every ticket created during migration will fire live Slack, Teams, and email alerts to internal employees at scale.
No Bulk Migration via Public API
Freshservice's own documentation explicitly states that its public APIs are designed for integrations rather than large-volume data migrations, and requires partners to use separate migration-request and bulk-migration processes for enterprise-scale transfers.
What breaks
Known failure modes. Have a recovery plan for each before you cut over.
Broken relationships:
Tickets imported without valid requester IDs fail or get assigned to a default user
Lost conversation history:
If you don't fetch and replay every message in order, the thread is incomplete
Attachment orphaning:
Attachments referenced by URL in LiveAgent may expire or require separate download and re-upload
Rate limit cascades:
Both platforms throttle aggressively — LiveAgent at 180 requests/minute, Freshservice at 100–500/minute depending on plan
Silent data loss:
Fields that don't map cleanly get dropped without errors
Mass notification storms:
If you do not explicitly suppress automations during import (via the bypass_mandatory parameter and manual deactivation of workflows), Freshservice will fire Slack notifications, Teams messages, email alerts, and business rules on every ticket created — potentially sending thousands of false notifications to employees
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
Can I migrate LiveAgent data to Freshservice using CSV export?
Only partially. LiveAgent's panel CSV export provides a ticket snapshot but drops full conversation threads, attachments, custom fields, and relational data. Freshservice's CSV imports target specific entities (requesters, departments, assets) and do not provide an end-to-end ticket-history import path. For anything requiring full history, use the API-based approach.
What are the API rate limits for LiveAgent and Freshservice during migration?
LiveAgent's cloud API v3 allows 180 requests per minute per API key. Freshservice's API v2 limits vary by plan: Starter 100/min, Growth 200/min, Pro 400/min, Enterprise 500/min. Freshservice limits are account-wide (shared across all users, apps, and integrations). Both platforms return 429 errors when limits are exceeded.
How do LiveAgent Contacts and Companies map to Freshservice?
LiveAgent Contacts are external customers; Freshservice Requesters are internal employees. They map by email address, but the semantic meaning differs. LiveAgent Companies have no direct Freshservice equivalent — they may map to Departments (if they represent internal orgs), be stored as custom fields on requesters, or be discarded. LiveAgent Departments (routing groups) map to Freshservice Groups, not Freshservice Departments.
Can I migrate LiveAgent automations and SLA policies to Freshservice?
No. LiveAgent's automation rules, SLA policies, canned messages, and predefined answers cannot be migrated programmatically. They must be manually rebuilt in Freshservice's Workflow Automator and SLA configuration. This manual work is often 20–30% of the total migration effort.
What breaks most often in a LiveAgent to Freshservice migration?
The most common failures are: wrong message classification (public vs. private notes), duplicate requesters rejected by Freshservice, broken parent-child relationships from out-of-order record creation, attachment handling errors (size limits, URL expiration), and Freshservice automations firing during import and sending thousands of false notifications.