LiveAgent-to-Intercom migration requires mapping tickets to conversations, handling a 180 req/min source API limit, and working around Intercom's 250 CDA cap and 500-part conversation limit.
There is no native migration path from LiveAgent to Intercom; LiveAgent's ticket-centric data model does not map 1:1 to Intercom's dual conversation/ticket architecture and contact-timeline-centered design. LiveAgent treats every interaction as a ticket with messages attached, while Intercom separates conversations from tickets and uses a many-to-many contact-to-company relationship versus LiveAgent's one-to-one. Preserving historical context, multi-message threads, attachments, and relational links (Contact → Company → Conversation → Teammate) requires a programmatic, API-led approach with significant custom transformation logic to bridge the structural gap between platforms.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
The lowest-risk migration pattern
load closed history first into a non-live Intercom workspace, run UAT with 2–3 agents, then execute a final delta run for records changed after the cutoff, and switch DNS/routing to Intercom.
Intercom CDAs have strict limitations
text values are capped at 255 characters, dropdown lists are limited to 35 options per attribute, and the soft limit is 250 active CDAs per workspace. Exceeding 250 requires contacting Intercom support — they can raise the limit, but query performance may degrade. If your LiveAgent instance has long text fields or picklists with many values, you will need to transform the data — use text CDAs instead of dropdowns, truncate with a suffix marker (e.g., [truncated]), or move overflow text into conversation notes. CDAs must be created in Intercom before importing data, or values will be silently discarded with no error returned.
Company attributes cannot be enforced as required-on-close in Intercom
That toggle applies only to conversation and ticket attributes, so move close-critical data onto those objects instead of company fields. (intercom.com)
Intercom's 10,000 req/min limit sounds generous, but creating a single conversation with
Intercom's 10,000 req/min limit sounds generous, but creating a single conversation with 20 messages requires ~21 API calls (1 to create + 20 reply calls). A 50K-ticket migration with an average of 5 messages per ticket means ~300K API calls on the Intercom side alone — approximately 30 minutes of pure API time at maximum throughput, but realistically 1–2 hours with retries and backoff.
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 Intercom can hold your support model
Walk your current workflow through Intercom: 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 → Intercom 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 → Intercom specifics
- Conversational support model
- Intercom's messenger-first architecture supports in-app messaging, proactive outreach, and AI-powered resolution via Fin — which can autonomously resolve up to 50% of support volume according to Intercom's published benchmarks. LiveAgent has no native equivalent to embedded in-app messaging or AI resolution agents.
- Product-led growth alignment
- Teams building SaaS or subscription products need Intercom's behavioral event tracking, product tours, and event-driven messaging tied directly to their app. LiveAgent lacks native user-event ingestion for triggering contextual messages.
- Consolidation
- Companies already using Intercom for marketing or sales want support on the same platform. Running LiveAgent alongside Intercom means paying for two platforms, maintaining two integrations, and splitting customer context across systems.
- Automation sophistication
- Intercom's visual workflow builder supports branching logic, conditional paths, API webhooks, and Fin AI agent handoffs. LiveAgent's automation is limited to flat trigger-action rules without visual orchestration or AI components.
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 → Intercom 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 → Intercom 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 Intercom 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 Intercom sandbox that reconciles cleanly and has been reviewed by real agents.
Keep these open
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Stand up a Intercom 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 Intercom'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 Intercom, 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 Intercom'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.
LiveAgent → Intercom specifics
- Critical
- Intercom does not cascade-delete. Deleting a contact does not delete their conversations. You must delete conversations separately.
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 Intercom 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 Intercom, 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.
LiveAgent → Intercom specifics
- Search API
- Use filters to find records by external_id or custom attributes. Limited to 50 results per page. Use for targeted spot checks.
- Scroll API
- Returns all contacts in paginated batches. Use for full count validation. Note: scroll sessions expire after 1 minute of inactivity.
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 Count It
| LiveAgent field | Intercom field | Notes |
|---|---|---|
| Tickets | Total + by status | Include resolved/archived. Note the 10K filter cap — use date windowing if total exceeds this. |
| Contacts | Total + duplicates | Check for contacts with no tickets and contacts sharing the same email across channels. |
| Companies | Total | Verify contact-company links. Orphaned companies will not surface in Intercom UI. |
| Tags | Total | Map to Intercom tags. Identify and consolidate synonymous tags. |
| Custom fields (Contact) | List all with data types | Check for fields exceeding 255 characters or picklists with >35 options. |
| Custom fields (Ticket) | List all with data types | Map to Intercom CDAs. Count total — must stay under 250 active CDAs. |
| Knowledge base articles | Total + categories | Map categories to Intercom collections. Note internal links and embedded images. |
| Attachments | Total count + total size in GB | Estimate re-hosting needs. Budget ~1 second per attachment for download/upload. |
| Agents / Departments | Total active + inactive | Map to Intercom admins/teams. Decide how to handle inactive agents. |
| Call recordings | Total count + total size | These have no Intercom destination — plan external archival. |
Object Object
| LiveAgent field | Intercom field | Notes |
|---|---|---|
| Contact | Contact (role: user) | Match on email. Keep identifier strategy consistent to avoid duplicate matching. |
| Company | Company | Create via API with a stable company_id. Companies become visible only after a contact is attached. (intercom.com) |
| Agent | Admin | Cannot be created via API — must exist in Intercom first. Map inactive agents to a generic "Legacy Agent" admin to preserve attribution without consuming a paid seat. |
| Department | Team | Create manually in Intercom before migration. |
| Ticket | Conversation or Ticket | See design decision above. Use POST /conversations for conversations, POST /tickets for tickets. |
| Ticket message | Conversation Part | Each message becomes a part. Max 500 parts per conversation. |
| Internal note | Conversation Part (note) | Use message_type: "note" for internal notes, message_type: "comment" for public replies. Handle both old and new LiveAgent note-type conventions. (support.liveagent.com) |
| Tag | Tag | Create via API, then attach to conversations/contacts. |
| KB Article | Article | Map categories to Intercom collections. See Knowledge Base Migration section. |
| Custom contact field | Custom Data Attribute | Must be created before importing data. |
| Custom ticket field | Conversation Data Attribute | Limited to supported types. List attributes expect target list item IDs, not labels. (developers.intercom.com) |
| Ticket attachment | Conversation part attachment | Must be re-uploaded; URLs are not transferable. |
LiveAgent Intercom
| LiveAgent field | Intercom field | Notes |
|---|---|---|
| Primary identifier. Lowercase and trim whitespace before import. | ||
| firstname + lastname | name | Concatenate — Intercom uses a single name field |
| phone | phone | Direct mapping |
| company_id | company.company_id | Must link after company creation |
| city | custom_attributes.city | No native city field in Intercom |
| custom fields | custom_attributes.* | Create CDAs first |
| dateCreated | signed_up_at | Convert to Unix epoch |
| contactid | external_id | Preserve for deduplication and audit |
Tickets Conversations
LiveAgent's ticket object must be mapped to either Intercom conversations or tickets, with full multi-message thread reconstruction, chronological ordering, and a 500-part-per-conversation limit.
| LiveAgent field | Intercom field | Notes |
|---|---|---|
| subject | source.subject | Only on first message. Intercom's standard Conversations do not use subject lines — the subject is typically prepended to the first message body. Intercom's newer Tickets object does support formal titles via the title field. |
| status (New/Answered) | state (open) | |
| status (Postponed) | state (snoozed) | |
| status (Resolved/Deleted) | state (closed) | |
| department_id | team_assignee_id | Map department → team via lookup table |
| agent_id | assignee.id | Agent must exist as admin. Use GET /admins to build ID lookup. |
| tags | tags | Attach after conversation creation |
| dateCreated | created_at | Convert to Unix epoch. Use Intercom's historical import endpoint to set this correctly. |
| messages [] | conversation_parts [] | Each message = one part. Preserve chronological order. |
Tickets Intercom Tickets
LiveAgent's ticket object must be mapped to either Intercom conversations or tickets, with full multi-message thread reconstruction, chronological ordering, and a 500-part-per-conversation limit.
| LiveAgent field | Intercom field | Notes |
|---|---|---|
| subject | title | Direct mapping — Tickets support formal titles |
| status | ticket_state | Map to: submitted, in_progress, waiting_on_customer, resolved |
| department_id | team_assignee_id | Same as conversations |
| agent_id | assignee.id | Same as conversations |
| ticket type | ticket_type_id | Must pre-create ticket types in Intercom admin UI |
| custom ticket fields | ticket_attributes | Create as ticket-level CDAs |
KB Concept Help Center Concept
| LiveAgent field | Intercom field | Notes |
|---|---|---|
| Category | Collection | 1:1 mapping. Intercom collections can be nested one level deep. |
| Subcategory | Section within Collection | If LiveAgent has deeper nesting, flatten to two levels. |
| Article | Article | Map to a collection. |
| Article status (published) | Article state (published) | Direct mapping. |
| Internal articles | Article state (draft) | Keep as draft; do not publish internal docs to the Help Center. |
Dataset Size Tickets
| LiveAgent field | Intercom field | Notes |
|---|---|---|
| Small | <5K | Single-pass, no date windowing needed |
| Medium | 5K–50K | Requires date-windowed batching |
| Large | 50K–200K | Consider database dump |
| Enterprise | 200K+ | Database dump strongly recommended |
LiveAgent Intercom
| LiveAgent field | Intercom field | Notes |
|---|---|---|
| contactid | external_id | Cast to string |
| Lowercase, trim whitespace | ||
| firstname + lastname | name | Concatenate with space; default to "Unknown" if both empty |
| phone | phone | Direct copy |
| company.name | company.name | Direct copy |
| company.id | company.company_id | Cast to string; use as stable identifier |
| ticket.subject | conversation.source.subject | Direct copy (first message only); prepend to body for Conversations |
| ticket.status | conversation.state | Map: N/T/A/C/B→open, P→snoozed, R/X→closed |
| ticket.dateCreated | conversation.created_at | Convert to Unix timestamp (seconds) |
| ticket.departmentId | conversation.team_assignee_id | Map via lookup table |
| ticket.agentId | conversation.assignee.id | Map LiveAgent agent → Intercom admin via lookup table |
| ticket.tags [] | conversation.tags [] | Match by name, create if missing |
| message.body | conversation_part.body | HTML preserved where supported; strip unsupported tags |
| message.type (internal) | conversation_part.message_type | Map to "note" |
| message.type (public) | conversation_part.message_type | Map to "comment" |
| contact.custom_field_* | contact.custom_attributes.* | Create CDA first; truncate text >255 chars |
| ticket.custom_field_* | conversation.custom_attributes.* | Create CDA first; map list values to Intercom list item IDs |
| message.attachment | conversation_part attachment URL | Download, re-upload, reference new URL |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Contacts | low | Contacts are relatively straightforward to migrate via API or CSV, though care must be taken with consistent user_id usage to avoid duplicates in Intercom's 20 MB CSV import limit. |
| Companies | medium | Intercom does not support CSV import for companies and uses a many-to-many contact relationship model versus LiveAgent's 1:1, requiring API-based import with relationship remapping. |
| Tickets / Conversations | high | LiveAgent's ticket object must be mapped to either Intercom conversations or tickets, with full multi-message thread reconstruction, chronological ordering, and a 500-part-per-conversation limit. |
| Custom Fields | high | Intercom enforces strict CDA constraints (250 active limit, 255-char text cap, 35-option dropdown cap) that may require significant restructuring of LiveAgent's custom contact and ticket fields. |
| Attachments | high | Attachments and inline images are not included in LiveAgent CSV exports and must be individually extracted via API, re-hosted externally, and re-linked within Intercom conversation parts. |
| Tags | low | Tags can be extracted from LiveAgent and applied to Intercom contacts and conversations via API with straightforward string mapping. |
| Knowledge Base Articles | medium | LiveAgent KB articles and categories must be restructured into Intercom's Help Center articles and collections, with potential formatting differences and media re-hosting required. |
| Call Recordings | high | Intercom has no native call recording object, so LiveAgent's VoIP call recordings have no direct migration target and must be stored externally with manual linking or abandoned. |
| Automation Rules | medium | LiveAgent's flat trigger-action rules cannot be automatically converted to Intercom's visual branching workflows and must be manually rebuilt with potentially different logic structures. |
| Agent / Team Assignments | low | LiveAgent departments map conceptually to Intercom teams, but agent IDs differ across platforms and must be manually mapped to preserve correct assignment attribution on historical records. |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
Ticket-to-Conversation Model Mismatch
LiveAgent's single ticket object must be split into Intercom's two distinct object types — conversations and tickets — requiring custom logic to determine which target object each record maps to.
LiveAgent API Rate Limits
LiveAgent's cloud API is capped at 180 requests per minute with a 10,000-ticket filter limit, meaning extraction of 100K+ tickets can take multiple days of continuous API calls.
Custom Field Transformation Constraints
Intercom's Custom Data Attributes enforce a 250 active attribute limit, 255-character text cap, and 35-option dropdown cap, requiring careful mapping and potential restructuring of LiveAgent's custom fields.
Multi-Message Thread Reconstruction
Rebuilding LiveAgent ticket threads as Intercom conversation parts in correct chronological order with proper agent attribution is complex, especially given Intercom's 500 conversation parts limit.
Attachment and Inline Image Handling
LiveAgent's CSV exports do not include full message threads with attachments, so attachments and inline images must be individually downloaded via the API, re-hosted, and re-linked in Intercom conversations.
Contact-Company Relationship Differences
LiveAgent uses a 1:1 contact-to-company relationship while Intercom supports many-to-many associations, requiring relationship logic transformation and careful deduplication during import.
What breaks
Known failure modes. Have a recovery plan for each before you cut over.
Embedded images:
Images hosted on LiveAgent's CDN must be downloaded and re-uploaded. Use Intercom's article API to upload images, or host them on your own CDN and reference via URL.
Internal links:
Links between KB articles that reference LiveAgent URLs must be rewritten to point to the new Intercom Help Center URLs. Build a URL mapping table (old article URL → new article URL) and do a find-replace across all article bodies.
SEO redirects:
If your LiveAgent KB was public-facing, set up 301 redirects from old article URLs to new Intercom Help Center URLs. This preserves search engine ranking and prevents broken links from external sites.
Intercom article body format:
Intercom's article API accepts HTML, but only a subset of tags. Strip unsupported tags (e.g., <script>, <iframe>, custom data-* attributes) before import.
Article author:
Intercom requires an author_id (an admin ID) for each article. Map LiveAgent article authors to Intercom admins, or default to a single admin for all migrated articles.
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
Can I migrate LiveAgent tickets to Intercom with CSV?
Not cleanly. Intercom's CSV importer handles people records only — not company data, conversation threads, or attachments. Full ticket history requires the LiveAgent API for extraction and the Intercom API for import. CSV is only viable for small contact-only migrations where you can start fresh with conversations.
What are the API rate limits for LiveAgent and Intercom?
LiveAgent's cloud API is limited to 180 requests per minute per API key, with a 10,000-record cap per filtered ticket query. Intercom allows 10,000 API calls per minute per app and 25,000 per workspace, distributed in 10-second windows. LiveAgent's lower limit is typically the bottleneck during extraction.
Should LiveAgent tickets become Intercom conversations or tickets?
Customer-facing threads (email, chat) usually map to Intercom conversations. Back-office or tracked work items map better to Intercom tickets, which require pre-created ticket types. This decision must be made before the first load because it affects the entire target schema.
How long does a LiveAgent to Intercom migration take?
Timeline depends on data volume. A small migration (under 5K tickets) can be done in 1–2 days. Mid-size migrations (5K–100K tickets) typically take 3–7 days including testing. Enterprise migrations with 100K+ tickets may take 1–2 weeks due to LiveAgent's API rate limits on extraction.
What LiveAgent data is lost when migrating to Intercom?
Call recordings, voicemail files, SLA history metrics, chat session metadata (typing indicators, visitor page URLs), automation rules, agent gamification data, and forum/suggestion artifacts do not have equivalents in Intercom. These should be archived externally before migration.