Plain's native Zendesk importer handles standard data (users, tickets, messages, tags). Custom fields, organizations, and attachments need API scripting or a managed service.
Migrating from Zendesk to Plain moves support data from a broad, enterprise-grade REST-based helpdesk to an API-first, GraphQL-native platform purpose-built for B2B engineering teams. Plain does ship a native Zendesk importer that handles end users, tickets, messages, and tags automatically, providing a fast path for standard migrations. However, fundamental data model mismatches — most critically the absence of a direct import path for Zendesk Organizations into Plain's Company and Tenant model, and the lack of custom ticket field mapping in the native importer — require additional API scripting or a managed service for anything beyond a basic migration. Attachments, organization-level custom fields, granular status mapping, and historical timestamp preservation all require custom engineering work against Plain's GraphQL API using mutations such as upsertCustomer, importThread, and importThreadMessages.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
Scale threshold
If your Zendesk instance has over 50,000 tickets, multiple brands, or complex custom field dependencies, a DIY script will likely require multiple iterations due to payload limits, unmapped relational constraints, or rate limit exhaustion. Budget for at least two full test runs before the production migration.
For pilot slices, use Zendesk's Search Export endpoint instead of filtering spreadsheets by hand
It supports cursor pagination up to 1,000 records per page and works well with queries like status:open tags:migrate_to_plain created>2026-01-01. (developer.zendesk.com)
Plain assigns Companies automatically based on customer email domain
If your Zendesk Organizations don't align with email domains (e.g., shared support emails, partner accounts, multiple domains per org), you'll need to update Company assignments via the API after import. Free email providers (gmail.com, outlook.com, yahoo.com) will group unrelated customers into the same Company — handle these explicitly.
Determining your Plain rate limit
Make any authenticated API call and inspect the response headers. x-ratelimit-limit returns your workspace's per-minute cap. x-ratelimit-remaining shows how many requests you have left in the current window. Build your backoff logic around these values. (plain.com)
Use source IDs everywhere
Plain's historical import mutations are idempotent on externalId, so you can resume after failures without duplicate threads or messages. Always prefix IDs with the source system (e.g., zd_ticket_12345) to avoid collisions if you migrate from multiple platforms later.
Plain's Customer Cards can fill some gaps
If you need to display Zendesk organization data, billing status, or custom object data in Plain, build a Customer Card that pulls from your own backend or a cached copy of the Zendesk data. Customer Cards are rendered live on each load, so they always show current data from your system of record.
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 Plain can hold your support model
Walk your current workflow through Plain: 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 → Plain 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.
Zendesk → Plain specifics
- API-first architecture
- Plain exposes a fully public GraphQL API where every object is readable and writable. Zendesk's REST API has grown organically but carries legacy constraints and tighter rate limits on lower-tier plans (200 req/min on Team vs. 2,500 on Enterprise Plus).
- Engineering-team collaboration
- Plain integrates natively with Linear, GitHub, and Jira for escalation workflows. Zendesk can do this through Marketplace apps, but the plumbing is heavier.
- Bring Your Own AI agent
- Plain's architecture lets you connect Claude, GPT, Gemini, or custom models directly via Machine Users — no per-resolution fees.
- Cost structure
- Plain includes AI on every plan. Zendesk's per-agent cost scales faster, especially once you add the High Volume API add-on ($35/agent/month on Suite plans) or Advanced AI features.
- Small team, standard data, fast timeline
- Start with Plain's native Zendesk importer. It's included in your plan, it's fast, and it handles core objects.
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
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 → Plain 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 → Plain 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 Plain 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 → Plain specifics
- Mid-size account with custom fields and org data
- API-based migration or managed service, depending on engineering availability.
- Status mapping
- new, open → TODO; pending → SNOOZED; on-hold → TODO or SNOOZED based on your semantics; solved, closed → DONE
- User deduplication
- Zendesk allows multiple users with similar emails; Plain enforces email uniqueness
- Organization → Tenant mapping
- Map Zendesk organization_id to Plain Tenant externalId
- Custom field conversion
- Cast Zendesk field values to match Plain Thread Field types. Plain's schema is strict — passing a string into an enum field fails the entire mutation.
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 Plain sandbox that reconciles cleanly and has been reviewed by real agents.
Keep these open
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Stand up a Plain 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 Plain'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 Plain, 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 Plain'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.
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 Plain 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 Plain, 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.
Don't move on until
- Full reconciliation report attached to the project record
- Reporting baselines match pre-migration figures within agreed tolerance
- Formal acceptance signed and archive retention scheduled
Field mapping reference
The field-by-field mapping for each object. Use this as the starting point for your mapping spec.
Object Equivalent
| Zendesk field | Plain field | Notes |
|---|---|---|
| End-user | Customer | Matched by email (unique in Plain). Store Zendesk user ID in externalId. |
| Organization | Company + Tenant | Company is auto-assigned by email domain. Tenant maps to your product's workspace/org concept. Org custom fields need manual handling. |
| Ticket | Thread | Use importThread for historical data, not createThread. |
| Ticket comment (public) | Thread message (INBOUND/OUTBOUND) | Preserve timestamps and author attribution. |
| Ticket comment (internal) | Note | Internal notes import as Plain notes via the native importer. |
| Ticket tag | Label | 1:1 mapping. Create Labels in Plain before import if using API. |
| Custom ticket field | Thread Field | Must configure Thread Field schema in Plain first. Data types must match exactly — Plain's schema is strict. |
| Custom user field | Customer metadata | No direct equivalent — store in externalId or surface via Customer Cards. |
| Custom org field | Tenant metadata | No direct equivalent. Consider Customer Cards for live data. |
| Macro | Workflow / Rule | Must rebuild manually. No import path. |
| Trigger / Automation | Auto-responder / Rule | Must rebuild manually. |
| SLA Policy | SLA (per-tier) | Rebuild in Plain's tier-based SLA system. |
| Satisfaction rating | — | Not migrated. Export separately (see CSAT Data Handling). |
| Ticket form | — | Plain uses Thread Fields instead of multiple ticket forms. |
| Custom objects (Sunshine) | — | No equivalent. See Sunshine Custom Objects for handling strategies. |
| Help Center article | Help Center article | See Knowledge Base Migration. |
Zendesk Plain
| Zendesk field | Plain field | Notes |
|---|---|---|
| ticket.id | thread.externalId | Prefix with source system, e.g. zd_ticket_12345 |
| ticket.subject | thread.title | Direct map |
| ticket.status (new/open) | status = TODO | Map detail to NEW_REPLY or IN_PROGRESS where supported |
| ticket.status (pending) | status = SNOOZED | Maps to WAITING_FOR_CUSTOMER |
| ticket.status (on-hold) | status = TODO or SNOOZED | Choose based on your internal semantics — these are not the same operationally |
| ticket.status (solved/closed) | status = DONE | DONE_MANUALLY_SET for imported threads |
| ticket.priority | priority | Plain import uses 0=urgent, 1=high, 2=normal, 3=low |
| requester.email | customer.email | Unique in Plain; deduplicate before load |
| requester.id | customer.externalId | Keep original source ID |
| organization.id | company.externalId or tenant.externalId | Decide once and stay consistent |
| ticket.tags | labelTypeIds | Normalize spelling and casing first |
| custom_fields | threadFields | Convert to declared schema and valid enums |
| ticket.created_at | createdAt | ISO 8601; use importThread to preserve original timestamp |
| attachments | attachmentIds | Upload first, then reference in message import |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Tickets / Threads | low | Core ticket-to-thread migration is well-supported by Plain's native Zendesk importer and the <code>importThread</code> GraphQL mutation, though very large accounts (500K+ tickets) may face extended migration windows of several hours. |
| End Users / Customers | low | Zendesk end-user records map cleanly to Plain Customers via the <code>upsertCustomer</code> mutation and are handled automatically by the native importer, making this one of the lowest-risk entities in the migration. |
| Organizations / Companies & Tenants | high | Zendesk Organizations have no direct import path in Plain's native importer and must be manually decomposed into the Company and Tenant model, with organization-level custom fields requiring a completely separate migration strategy. |
| Custom Ticket Fields / Thread Fields | high | Custom field schemas must be manually re-created in Plain before migration, and the native importer does not carry over any custom field data, requiring full API-based scripting to populate Thread Fields from Zendesk source data. |
| Ticket Comments / Thread Messages | medium | Public and internal comments (notes) are imported by the native importer, but historical timestamp preservation and author attribution require API-based migration using <code>importThreadMessages</code>, and the CSV export path omits comments entirely. |
| Attachments | high | Attachments are excluded from Zendesk's bulk CSV export and must be individually fetched via the Zendesk REST API and re-uploaded through Plain's separate attachment upload flow, making this the most engineering-intensive entity to migrate correctly. |
| Tags / Labels | low | Zendesk ticket tags are automatically imported as Plain Labels by the native importer, representing one of the most straightforward entity translations in the migration. |
| Internal Notes | medium | Internal notes on Zendesk tickets are imported by the native importer, but ensuring correct attribution and timestamp fidelity for historical internal notes requires API-based migration rather than relying solely on the built-in tool. |
| Macros / Automations / Triggers | high | Zendesk Macros, Triggers, and Automations have no automated migration path and must be manually reconstructed as Plain Workflows, Rules, and Auto-responders, requiring a full audit of existing automation logic before cutover. |
| Knowledge Base / Help Center | medium | Zendesk Guide content must be migrated separately to Plain's Help Center with no native import tool available, requiring manual export and reformatting of article content, though the absence of relational dependencies keeps risk lower than organization or custom field migration. |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
Organization to Tenant Mapping
Zendesk Organizations have no direct 1:1 equivalent in Plain; they must be decomposed into Plain's two-layer model of Companies (auto-assigned by email domain) and Tenants (representing product workspace or billing boundaries), requiring manual mapping logic before any migration code can run.
Custom Field Schema Translation
Zendesk custom ticket, user, and organization fields do not carry over through Plain's native importer and must be manually re-created as Thread Field schemas in Plain before API-based load scripts can populate them.
Status and Priority Model Mismatch
Zendesk's six-state ticket lifecycle (New, Open, Pending, On-hold, Solved, Closed) must be collapsed into Plain's three-state model (Todo, Done, Snoozed), requiring a deliberate mapping strategy that will inevitably lose granularity for pending and on-hold states.
Attachment Re-upload Complexity
Zendesk's CSV bulk export omits ticket comments and attachments entirely, meaning attachments must be fetched individually via the Zendesk REST API and re-uploaded through Plain's separate attachment upload flow, adding significant engineering complexity and latency to the migration.
API Rate Limit Constraints
Zendesk enforces strict rate limits as low as 200 requests per minute on Team-tier plans, and these limits apply simultaneously with Plain's own API constraints, requiring careful batching, cursor-based pagination, and retry logic to avoid data loss or migration stalls on large accounts.
Delta Sync During Cutover
The native Zendesk importer only syncs new records created after the initial import and does not propagate subsequent changes to existing tickets (status updates, reassignments, priority changes), meaning teams must plan a coordinated cutover window or build a custom delta sync mechanism to avoid data divergence.
What breaks
Known failure modes. Have a recovery plan for each before you cut over.
Duplicate customers
Zendesk allows multiple user records with overlapping emails (especially suspended/deleted users). Plain enforces email uniqueness. Deduplicate before loading — use the most recently active record.
Missing requesters
Some Zendesk tickets have deleted or anonymous requesters. Create a fallback customer in Plain (e.g., "Unknown Customer") to maintain thread integrity.
Multi-organization users
Zendesk supports users belonging to multiple organizations. Plain assigns one Company per customer. Decide which org wins, or use Tenants as the secondary grouping.
Relationship ordering
If you import a thread with a tenantId, the customer must already be a member of that tenant. Load memberships first or fail fast. (plain.com)
Side conversations
Zendesk Side Conversations (child tickets, Slack messages, emails) have no direct Plain equivalent. Import them as notes or separate threads.
Suspended tickets
Tickets caught by Zendesk's spam filter. Decide whether to migrate or discard them.
Ticket followers and CCs
Zendesk tickets can have CCs and followers. Plain threads support multiple participants but the mapping isn't 1:1. Plan how CC'd users appear.
Partial failures
importThreadMessages can return per-message errors and a top-level bulk_partial_failure. Log at message granularity, not just ticket level. (plain.com)
Status nuance
Zendesk pending and on-hold are not the same thing operationally. Pending stops the SLA clock and signals "waiting for the customer." On-hold stops the SLA clock but signals "waiting for an internal/third-party resolution." Don't map both blindly to one Plain state without understanding your team's workflow. (support.zendesk.com)
Free email domains
Customers using gmail.com, outlook.com, yahoo.com, etc. will all be auto-assigned to the same Company in Plain. Override these assignments via API or exclude free domains from Company auto-assignment.
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
Does Plain have a built-in Zendesk importer?
Yes. Plain offers a native Zendesk importer under Settings → Zendesk importer. It imports end users as Customers, tickets as Threads, all messages (including internal notes), and ticket tags as Labels. After the initial import, it auto-syncs new data. However, it does not import custom fields, organizations, or satisfaction ratings, and changes to existing Zendesk tickets (status, priority, assignee) do not keep syncing.
How do Zendesk ticket statuses map to Plain?
Zendesk uses six statuses (New, Open, Pending, On-hold, Solved, Closed). Plain has three: Todo, Done, and Snoozed. New/Open map to Todo, Pending maps to Snoozed (Waiting for Customer), Solved/Closed map to Done. On-hold can map to either Todo or Snoozed depending on your team's semantics — these two Zendesk statuses are not operationally identical, so don't map them blindly to the same Plain state.
What data doesn't transfer from Zendesk to Plain?
Macros, triggers, automations, SLA policies, ticket forms, satisfaction ratings, audit logs, and Zendesk custom objects (Sunshine) have no migration path. They must be rebuilt manually or surfaced via Plain's Customer Cards and rule engine. Custom ticket fields also don't carry over through the native importer — you need API-based scripting with importThread for those.
How do Zendesk organizations map to Plain?
Plain has two organizational concepts: Companies (auto-assigned by customer email domain) and Tenants (which map to your product's workspace or org concept). Zendesk Organizations don't import directly via the native importer. Use Company for the business identity and Tenant when you need to model product workspaces. You'll need to create Tenants via the API and assign customers through scripting.
Do I need OAuth for a Zendesk API-based migration?
For new integrations, yes. Zendesk recommends OAuth and has announced that API tokens created in Admin Center will be permanently deactivated on April 30, 2027. If you're building a migration script now, use OAuth to avoid having to redo authentication later.