Zendesk-to-Intercom migration requires translating tickets to conversations, managing dual API rate limits, re-hosting every attachment, and suppressing notifications to avoid spamming customers.
Migrating from Zendesk to Intercom is a data architecture translation, not a lift-and-shift. Zendesk organizes everything around tickets with structured statuses and comment threads. Intercom is contact-centric with conversations, conversation parts, and a dedicated Tickets object — each following a messenger-first model. Conversation parts are capped at 500 per conversation, HTML is not supported in message bodies, and every attachment must be downloaded from Zendesk and re-hosted before import. Intercom's native importer handles up to 10 attachments and 10 inline images per ticket — anything beyond that is silently dropped. All imported tickets transition through open/update/close states, which can trigger customer-facing notifications if workflows are not disabled. A successful migration requires suppressing outbound messaging, managing dual API rate limits, and deciding between message-by-message replay and transcript approaches.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
Key decision before you start
Just because something was a ticket in Zendesk does not mean it has to be a ticket in Intercom. Intercom offers conversations (temporal, chat or email), customer-facing tickets, and back-office tickets. Intercom's native importer maps public Zendesk tickets to Customer tickets and private Zendesk tickets to Back-office tickets. You must decide the target structure during the planning phase, not mid-migration.
Disable outbound messaging in Intercom before importing any records
Intercom says email notifications are usually suspended automatically during migration, but also warns that some ticket emails can still send and recommends disabling Ticket Updates for the whole workspace first. (intercom.com)
Pre-create searchable destination fields for legacy IDs (e.g., legacy_zendesk_ticket_id,
Pre-create searchable destination fields for legacy IDs (e.g., legacy_zendesk_ticket_id, legacy_zendesk_user_id) before your first test import. It makes QA, agent search, and reruns much easier.
The author trap
When you use the API to create comments or replies, Intercom defaults the author to the API token owner. You must explicitly map the admin_id for agent replies and use the contact's Intercom ID for customer messages. If you miss this, your entire support history looks like it was written by one account.
Inline image trap
Zendesk ticket comments frequently contain inline screenshots as <img> tags pointing to Zendesk-hosted URLs. These are separate from the attachments array. If you don't explicitly extract and re-host these images, they will appear as broken links in Intercom after you decommission Zendesk.
Use Intercom's native importer if all of these are true
you are importing all tickets, volume is below 150K, tags do not need to come across, side conversations and call recordings are out of scope, and a point-in-time snapshot is acceptable. (intercom.com)
Both Zendesk and Intercom actively evolve their APIs
Before starting any migration, verify the current API documentation for both platforms to confirm endpoint availability and any recent changes to object models or rate limits.
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 Zendesk
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 Zendesk → 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.
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Migrate via API
The bulk of your historical data will move programmatically. This includes your Organizations (which map to Intercom Companies), End Users (Contacts), Tickets (which Intercom now supports as a dedicated object), and Ticket Fields (Data Attributes).
Zendesk → Intercom specifics
- Week 2: Initial Bulk Run
- All closed Gorgias tickets up to a fixed date are migrated to Intercom. Your team continues working in Gorgias.
- Manual Configuration
- Some objects simply do not have a direct write-path via the API or are efficient enough to handle by hand. Agents fall into this category.
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 Zendesk 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 Zendesk 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 Zendesk 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
Zendesk → Intercom specifics
- Rate limit orchestration
- Our scripts monitor both Zendesk and Intercom rate limit headers in real time, adjusting throughput dynamically rather than relying on fixed delays.
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 Zendesk → 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 Zendesk → 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.
Zendesk → Intercom specifics
- Custom field data
- Check that Data Attributes populated correctly — especially dropdowns, dates, and multi-line text fields that are prone to formatting issues.
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.
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Test Fin AI responses
against migrated Help Center articles to ensure content is being surfaced correctly.
Zendesk → Intercom specifics
- Week 1: Mapping & Sandbox Test
- We extract Gorgias tickets via their REST API, map custom fields, and run a sandbox import.
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 Zendesk 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 Zendesk 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 Zendesk read-only rather than cancelled — cancelling the old contract on day one removes your only fallback.
Zendesk → Intercom specifics
- Week 3: Delta Sync & Cutover
- We migrate everything that changed since the bulk run, redirect your support channels to Intercom, and go live.
- Initial bulk run
- All closed tickets up to a fixed "delta date" are migrated to a launch-ready but non-live Intercom workspace. Your team continues working in Zendesk with zero interruption.
- Delta sync
- On cutover day, we migrate everything that changed since the delta date — newly closed tickets plus all open/pending tickets.
- Attachment pipeline
- We download every attachment and inline image from Zendesk, re-host it, and link it correctly in Intercom — including files beyond the 10-per-message limit.
- Legacy ID preservation
- We store the original Zendesk ticket number as a custom attribute in Intercom so agents can search historical references without losing context.
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 Zendesk 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 Zendesk read-only for an agreed period (30-90 days is typical), take a final archive export, and only then cancel. Diarise the decommission date so it does not quietly renew.
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Record counts
Compare the total number of Organizations, Users, Tickets, and Articles in Zendesk against what landed in Intercom. Any discrepancy means something was dropped or duplicated.
Zendesk → Intercom specifics
- Ticket counts match
- Compare total tickets exported from Zendesk against total conversations/tickets in Intercom. But count parity alone is a weak success metric — you can recreate the right number of tickets and still lose operational history.
- Spot-check 50+ records
- across different ticket types, statuses, and date ranges. Look for: correct author attribution, correct timestamps, intact attachments, correct tag application, and correct team/teammate assignment.
- Search for edge cases
- Tickets with 100+ comments, tickets with 10+ attachments, tickets from deleted Zendesk users, tickets with side conversations, tickets with only private notes, multiselect fields that were flattened to text.
- Re-enable outbound messaging
- only after you've confirmed the import is clean. Turn on workflows, campaigns, and notifications one at a time.
- Comment ordering
- Spot-check a sample of migrated tickets to confirm comments appear in the correct chronological order and are attributed to the right authors.
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.
Zendesk Intercom Data Mapping Guide
| Zendesk field | Intercom field | Notes |
|---|---|---|
| Organizations | Companies | Must migrate first. Company associations anchor contact records. |
| End Users | Contacts (Users/Leads) | Must exist before tickets. Map external_id to preserve legacy IDs. |
| Agents | Admins/Teammates | Cannot create admins programmatically with permissions intact. |
| Groups | Teams | Routing logic differs; recreate by hand. |
| Tickets | Conversations or Tickets | Choose target structure per ticket type. |
| Ticket Fields | Data Attributes / Ticket Type Attributes | Must create attributes in Intercom before importing tickets. |
| Ticket Comments | Conversation Parts / Ticket Replies | Public comments → replies; private comments → notes. |
| Tags | Tags | Native importer skips tags entirely. API supports adding tags post-create. |
| Triggers & Automations | Workflows | No API migration path. See Automations, Macros, and Workflows. |
| Macros | Saved Replies / Macros | Rebuild in Intercom UI. |
| Help Center Articles | Articles | Intercom can import or sync a Zendesk Help Center. |
| Side Conversations | Private Notes (lossy) | No native equivalent. Native importer drops them entirely. |
| Satisfaction Ratings | Conversation Ratings | Historical CSAT data does not map cleanly. |
Object Object
| Zendesk field | Intercom field | Notes |
|---|---|---|
| Organizations | Companies | Migrate first to establish company associations |
| End Users | Contacts (Users/Leads) | Map organization_id to the corresponding Company |
| Agents | Admins | Cannot reliably create with permissions via API |
| Groups | Teams | Recreate to ensure routing logic is correct |
| Ticket Fields | Data Attributes / Ticket Type Attributes | Must exist before ticket import |
| Tickets | Tickets | Map requester_id → contact_id, assignee_id → Admin ID |
| Ticket Comments | Conversation Parts (replies) | Must replay comments in order; watch author attribution |
| Attachments | Attachments (multipart upload) | Download from Zendesk, re-upload to Intercom |
| Categories / Sections | Collections | Recreate hierarchy, then migrate articles |
| Articles | Articles | Preserve HTML body carefully |
| Tags | Tags | Apply to Contacts and Tickets after import |
| User Segments | Segments | Filtering logic rarely translates directly |
| Triggers / Automations | Workflows / Rules | Must be rebuilt from scratch |
| Ticket Statuses | Ticket States | Zendesk and Intercom use different status models — map these explicitly before import |
| Macros | — | No API write path in Intercom |
| Views | — | Rebuild manually in Intercom |
| SLA Policies | — | Recreate in Intercom's SLA settings |
| Satisfaction Ratings | — | No import path; historical CSAT data stays in Zendesk |
| Audit Logs | — | Zendesk audit trail does not transfer |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Side Conversations | high | No native Intercom equivalent. Native importer drops them entirely. Must be migrated as private notes. |
| Inline Images | high | Must be downloaded and re-hosted. Native importer handles only 10 per ticket; excess is silently dropped. |
| Attachments (>10 per ticket) | high | Native importer caps at 10 attachments per ticket. Overflow must be split across reply parts. |
| Multiselect Fields | medium | Native importer flattens to text, breaking filtering and reporting capabilities. |
| Ticket Tags | medium | Native importer skips tags entirely. Must be recreated via API post-import. |
| Call Recordings | high | Not migrated by the native importer. Require separate extraction and hosting. |
| Ticket Statuses | medium | Custom Zendesk statuses map to nearest standard Intercom state, not custom-to-custom. |
| HTML in Comments | medium | HTML is not supported in Intercom conversation message bodies. Must be stripped or converted to plain text. |
| Deleted/Suspended Users | medium | Not migrated by native importer. Comments from these users are mapped to a default contact. |
| Satisfaction Ratings | medium | Historical CSAT data does not map cleanly to Intercom conversation ratings. |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
Notification Suppression
All imported closed tickets go through open/update/close transitions that trigger notifications if Intercom workflows are active. Outbound messaging must be fully disabled before import.
Attachment Re-hosting
Zendesk attachment URLs break when the account is deactivated. Every file and inline image must be downloaded and re-hosted before referencing in Intercom.
500-Part Conversation Cap
Intercom limits conversation parts to 500. Zendesk tickets with more than 500 comments require truncation or a transcript-style approach.
Author Attribution
Intercom defaults comment authorship to the API token owner. Every comment must explicitly map admin_id for agents and contact ID for customers.
API Call Multiplication
Message-by-message migration inflates API calls by 10–100x. A 15-comment ticket requires 17+ API calls, making rate limit management critical.
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
How long does a Zendesk to Intercom migration take?
It depends on volume and method. Intercom's built-in tool handles under 150K tickets in days. A DIY script takes 2–6 weeks of engineering time. A managed migration service like ClonePartner typically completes the data transfer in days, including delta sync for zero-downtime cutover.
Can I migrate Zendesk tickets to Intercom without sending emails to customers?
Yes, but you must disable all outbound messaging, campaigns, workflows, and email notifications in Intercom before importing. All imported closed tickets go through open → update → close state transitions, which trigger notifications if workflows are active. Add 'Created via API' exceptions to any workflows you can't disable.
What is the Zendesk API rate limit for exporting tickets?
Zendesk's Incremental Export API allows 10 requests per minute on standard plans, with each page returning up to 1,000 tickets. The High Volume API add-on (available on Suite Growth and above, minimum 10 agent seats) increases this to 30 requests per minute.
Do Zendesk attachments transfer to Intercom automatically?
No. Zendesk attachment URLs point to Zendesk's CDN and will break when you deactivate your account. You must download each file, re-host it, and reference the new URL in Intercom. The native importer handles up to 10 attachments and 10 inline images per ticket; anything beyond that is silently dropped.
Should I migrate Zendesk tickets as Intercom conversations or Intercom tickets?
It depends on the ticket type. Customer support interactions map best to Intercom conversations or customer-facing tickets. Structured requests like bug reports map to Intercom tickets (customer-facing or back-office). Intercom's native importer maps public Zendesk tickets to Customer tickets and private tickets to Back-office tickets. Decide the target structure during planning, not mid-migration.