Migrating Intercom to Salesforce Service Cloud takes 2–4 weeks. Watch for the 4,000-char CaseComment limit and the 500-part API retrieval cap that silently truncate transcripts.
There is no native migration path from Intercom to Salesforce Service Cloud. Intercom's native Salesforce app supports live sync of ongoing conversations as Tasks, but it is not designed to replay historical support data into Salesforce's Account → Contact → Case hierarchy. The fundamental challenge is that Intercom's flat, conversation-centric data model—where Users, Leads, and conversation_parts exist as loosely related streams—must be restructured into Salesforce's strict relational schema with parent-child relationships across Accounts, Contacts, Cases, and CaseComments. Custom ETL work is required to extract full transcripts via the Intercom REST API (CSV exports omit message content), transform timestamps and custom attributes to Salesforce's strict schema, handle character limits on CaseComment fields, and rebuild Fin AI configurations, bot flows, and Product Tours from scratch.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
TL;DR — Intercom to Salesforce Service Cloud Migration
Migrating from Intercom to Salesforce Service Cloud is a high-complexity project because Intercom's conversation-centric data model does not map cleanly to Salesforce's Account → Contact → Case hierarchy. The realistic timeline is 2–4 weeks including mapping, testing, and cutover. The biggest risk is losing conversation transcripts — Intercom's CSV and standard dataset exports omit message content entirely, and the CaseComment.CommentBody field in Salesforce is capped at 4,000 characters, silently truncating long conversation parts. The Intercom API also caps conversation_parts retrieval at 500 per conversation, so long-running threads need explicit exception handling. Intercom Fin AI configurations, Product Tours, and custom bot flows cannot be migrated — they must be rebuilt in Salesforce. Current Intercom API rate limits are 10,000 calls per minute per app, though legacy documentation references 1,000/min; throttle from live X-RateLimit-* headers. Teams with small, clean workspaces can build a custom ETL script; for larger volumes, attachment-heavy conversations, or zero-downtime requirements, a managed migration service is the safer path.
Conversation parts are capped at 500 per conversation when retrieved via the API
If a conversation has more than 500 parts (common with long-running support threads or bot-heavy workflows), the API silently truncates. You must paginate through conversation_parts separately for these edge cases. Use statistics.count_conversation_parts in the search API to identify oversize threads before cutover. (developers.intercom.com)
Intercom's native Salesforce integration is designed for ongoing sync, not bulk
Intercom's native Salesforce integration is designed for ongoing sync, not bulk historical migration. By default, it maps conversation transcripts to Tasks on the Contact record, not to Cases. While auto case creation exists, it requires explicit configuration, does not back-fill historical conversations, and forces chat transcript into Case.Description — which can fail on field validation and does not support formula fields. (intercom.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 Intercom
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 Salesforce Service Cloud can hold your support model
Walk your current workflow through Salesforce Service Cloud: 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 Intercom → Salesforce Service Cloud 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.
Intercom → Salesforce Service Cloud specifics
- Enterprise case management and SLA enforcement
- Salesforce Service Cloud provides native Entitlements, Milestones, and Omni-Channel routing with skills-based assignment. Intercom's SLA tracking exists but lacks the multi-tier escalation paths and contractual compliance reporting that regulated or enterprise support orgs require.
- Unified CRM and service platform
- When sales already lives in Salesforce, running support in Intercom creates a data silo. Moving to Service Cloud puts Cases, Opportunities, and Account health on one platform — eliminating the sync overhead of maintaining a bidirectional Intercom↔Salesforce integration.
- Reporting depth and compliance
- Salesforce analytics, audit trails, field-level security, HIPAA-eligible configurations, and FedRAMP authorization exceed what Intercom offers for enterprise compliance teams.
- < 5,000 conversations, simple fields
- Custom script is feasible if you have an engineer with Salesforce API experience. Estimated effort: 40–80 engineer-hours.
- 5,000–50,000 conversations
- Custom ETL with dedicated engineering time (2–3 weeks, 120–200 engineer-hours).
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 Intercom 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 Intercom 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 Intercom 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
Intercom → Salesforce Service Cloud specifics
- Fin AI configuration and training data
- must be rebuilt in Salesforce Einstein or Agentforce.
- Intercom Product Tours and Checklists
- no Service Cloud equivalent; requires a separate tool (WalkMe, Pendo, or similar).
- Intercom Series (automated message sequences)
- rebuild as Salesforce Flows or Marketing Cloud journeys.
- Conversation ratings (CSAT)
- can be migrated as custom fields on the Case, but Salesforce's native CSAT survey mechanism (post-chat surveys, Customer Lifecycle Analytics) is structurally different.
- Bot steps, snooze history, and assignment event sequences
- no native Case fields for these. Decide up front whether they become searchable text in CaseComments, read-only custom fields, or a separate transcript object for audit and reporting.
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 Intercom → Salesforce Service Cloud 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 Intercom → Salesforce Service Cloud 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 Salesforce Service Cloud 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 Salesforce Service Cloud sandbox that reconciles cleanly and has been reviewed by real agents.
Keep these open
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Stand up a Salesforce Service Cloud 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 Salesforce Service Cloud'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 Salesforce Service Cloud, 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 Intercom 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 Salesforce Service Cloud'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 Intercom 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 Intercom 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 Intercom and Salesforce Service Cloud 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 Salesforce Service Cloud, 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 Intercom 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.
Intercom → Salesforce Service Cloud specifics
- Omni-Channel Routing
- Set up routing configurations, service channels, and agent presence statuses. Map Intercom team assignments to Salesforce skill-based routing rules.
- Entitlements & Milestones
- Define SLA policies that replace Intercom's SLA tracking. Create Entitlement Processes with Milestone Types (First Response, Resolution) and corresponding Milestone Actions.
- Escalation Rules
- Rebuild any Intercom escalation workflows as Salesforce Escalation Rules with time-based criteria.
- Quick Text
- Recreate Intercom saved replies as Salesforce Quick Text records for agent efficiency.
- Case Assignment Rules
- Configure rules based on criteria (product, priority, language) to replace Intercom's round-robin or workload-based assignment.
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.
Intercom Salesforce Service Cloud Object Mapping
| Intercom field | Salesforce Service Cloud field | Notes |
|---|---|---|
| User (role=user) | Contact | Match on email. Store Intercom user_id in a custom External_ID__c field. Salesforce requires a Last Name — Intercom often only has a first name or email. |
| Lead (role=lead) | Lead | Convert to Contact post-migration if needed. |
| Company | Account | Match on company_id or domain to prevent duplicates. |
| Conversation | Case | One Conversation = one Case. Map created_at → CreatedDate (requires "Set Audit Fields upon Record Creation" permission). (help.salesforce.com) |
| Conversation Part (comment) | CaseComment or EmailMessage | CaseComment has a 4,000-character limit on CommentBody. Use EmailMessage for HTML-rich or long messages. |
| Conversation Part (note) | CaseComment (IsPublished=false) | Internal notes map to private CaseComments. |
| Conversation Part (assignment, state_change) | Case field update or FeedItem | Assignment events can be logged as Chatter posts or discarded based on reporting needs. |
| Admin / Teammate | User | Salesforce Users must pre-exist; match by email. Inactive Intercom agents must be mapped to an active placeholder User or their history will fail to insert. |
| Team | Queue | Map Intercom Teams to Salesforce Queues for case assignment. |
| Tag | Topic or Custom Field | Salesforce Topics have limits; mapping tags to a multi-select picklist or custom object is often safer. |
| Custom Attribute (Contact) | Custom Field on Contact | Data type mapping required: Intercom allows flexible strings, booleans, numbers — Salesforce picklists reject values that don't match predefined options. |
| Conversation Attribute | Custom Field on Case | Create matching custom fields on the Case object before import. |
| Help Center Article | Knowledge__kav | Requires Knowledge enabled in the org. Rich text and image re-hosting needed. |
| Saved Reply / Macro | Quick Text or Macro | Intercom saved replies map to Salesforce Quick Text objects. Intercom macros with multi-step actions map to Salesforce Macros (Enterprise+ only). No automated migration path — these must be recreated manually or scripted via Metadata API. |
| Attachment | ContentVersion + ContentDocumentLink | Download from Intercom CDN, upload to Salesforce Files, link to parent Case. |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Contacts (Users) | medium | Intercom Users often lack a last name (required by Salesforce) and may have incomplete profiles, requiring data enrichment and deduplication by email before import. |
| Accounts (Companies) | medium | Intercom Companies are loosely attached to Users without strict hierarchy, so matching to Salesforce Accounts by company_id or domain requires careful deduplication to prevent duplicates. |
| Cases (Conversations) | high | Mapping Intercom's flat conversation stream to Salesforce's structured Case lifecycle requires preserving original timestamps via audit field permissions, and the API caps conversation_parts retrieval at 500 per conversation. |
| Conversation Transcripts | high | Full message content is unavailable from CSV or S3 exports and must be extracted via individual API calls, with CaseComment's 4,000-character limit silently truncating long conversation parts. |
| Attachments | high | Attachments must be individually downloaded from Intercom's CDN, uploaded as Salesforce ContentVersion records, and linked to parent Cases via ContentDocumentLink, adding significant processing time and storage considerations. |
| Custom Attributes / Fields | medium | Intercom's flexible string/boolean/number attributes must be mapped to Salesforce's strict field types and picklist values, with any non-matching data causing insert failures. |
| Tags | low | Tags can be mapped to Salesforce Topics or multi-select picklists, though Topics have platform limits that may require using a custom object for high-cardinality tag sets. |
| Knowledge Base Articles | medium | Help Center Articles must be migrated to Knowledge__kav with Salesforce Knowledge enabled, requiring rich text transformation and re-hosting of embedded images to Salesforce-accessible URLs. |
| Leads | low | Intercom Leads map directly to Salesforce Leads with relatively straightforward field mapping, though post-migration conversion to Contacts may be needed. |
| Macros and Saved Replies | medium | Intercom saved replies and multi-step macros have no automated migration path to Salesforce Quick Text or Macros and must be manually recreated or scripted via Metadata API. |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
Conversation Transcript Export Gap
Intercom's CSV and S3 dataset exports omit actual message content entirely, requiring per-conversation REST API calls to retrieve full transcripts—meaning 100,000 conversations need over 100,000 individual API requests.
Hierarchical Data Model Mismatch
Intercom's flat identity model with loosely attached Companies must be restructured into Salesforce's strict Account → Contact → Case hierarchy where every Case requires a Contact and every Contact should belong to an Account.
CaseComment Character Truncation
Salesforce's CaseComment.CommentBody field is capped at 4,000 characters and silently truncates longer content, risking data loss for lengthy Intercom conversation parts without explicit handling or use of EmailMessage objects.
Non-Migratable AI and Automation
Intercom Fin AI configurations, Product Tours, Checklists, custom bot flows, and Series automation sequences have no equivalent in Salesforce Service Cloud and must be entirely rebuilt using Einstein, Agentforce, or Flows.
Strict Schema and Picklist Validation
Intercom allows flexible custom attributes as free-form strings, booleans, and numbers, while Salesforce picklists reject any values not matching predefined options, requiring thorough data auditing and cleansing before load.
Audit Field and Timestamp Preservation
Preserving original created dates requires the 'Set Audit Fields upon Record Creation' permission (Enterprise+ only, enabled by Salesforce Support), and all Intercom Unix epoch timestamps must be explicitly converted to ISO 8601 format.
What breaks
Known failure modes. Have a recovery plan for each before you cut over.
Deleted/inactive users in Intercom
Intercom allows conversations to remain assigned to deleted teammates. Salesforce rejects any record assigned to an invalid or inactive OwnerId. Map all deleted Intercom users to an active "System Migration" user in Salesforce, or reactivate them temporarily during the load.
Duplicate contacts
Intercom allows multiple records with the same email (one as User, one as Lead). Salesforce enforces unique email on Contact. De-duplicate before import.
Multi-company contacts
Intercom Users can belong to multiple Companies. Salesforce Contact has a single AccountId. Choose a primary Account and store others in a junction object or multi-select field.
Archived contacts
Intercom archives inactive contacts. You must unarchive them via the API (POST /contacts/{id}/unarchive) before you can retrieve their full data — there is no UI option for bulk unarchiving.
Conversations with > 500 parts
The API caps conversation_parts at 500 per retrieval. Long-running threads may have more, requiring paginated extraction and an explicit exception plan. (developers.intercom.com)
HTML sanitization
Intercom conversation parts contain HTML (<p>, <a>, <img> tags). CaseComment stores plain text only — you must strip HTML. If you use EmailMessage, HTML is preserved, but Salesforce rich text fields enforce a strict tag whitelist. Unsupported tags (complex nested tables, custom div classes, <script>, <style>) will cause the API to reject the entire record with INVALID_MARKUP. Sanitize during the transformation phase.
Timezone handling
All Intercom timestamps are Unix epoch (UTC). Salesforce CreatedDate requires ISO 8601. Example conversion: 1735689600 → 2025-01-01T00:00:00.000Z.
CreatedDate override
By default, creating a Case in Salesforce stamps CreatedDate as the moment the API call runs. To preserve original Intercom timestamps, enable "Set Audit Fields upon Record Creation" before your first pilot load. This requires contacting Salesforce Support or using the Metadata API to enable the CreateAuditFields permission. Without this, a ticket from 2022 will appear as if it was created today. (help.salesforce.com)
Conversation ratings
Intercom CSAT ratings can be migrated as custom fields on the Case (e.g., Intercom_Rating__c picklist with values 1–5 and Intercom_Rating_Remark__c long text) but do not map to Salesforce's native CSAT survey mechanism.
Record locking during parallel loads
If multiple Bulk API jobs update records sharing the same parent Account, you will encounter UNABLE_TO_LOCK_ROW errors. Sort your CSV payloads by AccountId and reduce job parallelism to avoid this.
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
Can Intercom conversation history be preserved in Salesforce Service Cloud?
Yes. Every Intercom conversation part — customer messages, agent replies, internal notes, and bot interactions — can be migrated to Salesforce as CaseComments or EmailMessages on the corresponding Case. The key constraint is the 4,000-character limit on CaseComment.CommentBody; use EmailMessage objects to preserve full HTML content and avoid truncation. Also plan explicit exceptions for threads longer than 500 conversation parts, since the Intercom API caps retrieval at 500.
How much does an Intercom to Salesforce Service Cloud migration cost?
Cost depends on volume and complexity. A managed migration for 10,000–50,000 conversations typically costs $5,000–$15,000. Enterprise migrations (100,000+ conversations with attachments and zero-downtime requirements) range from $15,000–$40,000. DIY costs 120–200 engineer-hours plus the opportunity cost of pulling developers off product work.
What data cannot be migrated from Intercom to Salesforce Service Cloud?
Intercom Fin AI training and configuration, Product Tours, Checklists, Series (automated sequences), custom bot flows, and Messenger styling cannot be migrated. These must be rebuilt natively in Salesforce using Einstein, Agentforce, or Flows. Conversation ratings can be migrated as custom fields but don't map to Salesforce's native CSAT mechanism.
Does the native Intercom Salesforce integration handle historical migration?
No. Intercom's native Salesforce app is designed for ongoing sync of new conversations, not bulk historical migration. It creates Cases or Tasks from active conversations going forward and does not back-fill historical conversation data into Salesforce.
Can I migrate Intercom to Salesforce Service Cloud without downtime?
Yes, with a delta sync strategy. Run the full historical migration while agents continue working in Intercom. Before cutover, run a final delta sync to capture conversations created or updated during the migration window. This ensures zero missed tickets and no agent downtime.