LiveAgent to Zoho Desk migration requires API v3 extraction and the Zoho Desk Imports API to preserve timestamps. Plan 1–4 weeks depending on ticket volume and custom field complexity.
There is no native LiveAgent-to-Zoho Desk migration connector; the closest first-party option is Zoho Zwitch's generic 'Other services' CSV flow, which is limited to a single department and cannot preserve full conversation threading. The fundamental data model mismatch is significant: LiveAgent stores all ticket interactions as a flat array of typed messages within a unified inbox, while Zoho Desk enforces a department-centric architecture where public replies are Threads and internal notes are Comments — two distinct API objects requiring separate write operations. Custom ETL pipeline work is required to parse LiveAgent message type flags (complicated by a breaking type-normalization change in v5.62), map five fixed LiveAgent statuses to Zoho Desk's configurable status system, provision agents and departments ahead of import, and handle attachment transfers within Zoho Desk's per-file upload limits. Plan for one to four weeks of engineering effort depending on ticket volume, number of departments, custom field complexity, and total attachment size.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
TL;DR: LiveAgent to Zoho Desk Migration
LiveAgent's built-in CSV export drops conversation threads, internal notes, and attachments. A complete migration requires extracting via LiveAgent API v3 (GET /tickets/{ticketId}/messages) and loading via Zoho Desk's Imports API (POST /api/v1/imports) to preserve original timestamps. The core architectural challenge is mapping LiveAgent's flat inbox and message model into Zoho Desk's department-enforced, thread-and-comment structure. LiveAgent's API caps at 180 requests per minute and 10,000 tickets per filter query. Zoho Desk's API uses a daily credit system that varies by plan. Plan for 1–4 weeks depending on ticket volume, custom field complexity, and attachment size.
Note typing is not stable across LiveAgent versions
In LiveAgent v5.62, note typing changed. Older notes appear as message type N with internal group type I. Newer notes can appear as message type M with group type U. A single ticket can contain both styles with mixed integer and UUID IDs. If your extractor filters only on type == 'M', you may accidentally include some internal notes in customer-facing threads while missing older notes entirely. Normalize by semantic intent — public conversation, internal note, attachment, or system noise — not solely by type flag. (support.liveagent.com)
Zwitch's single-department limitation
Zoho's Zwitch FAQ states its migration engine moves data into one department. Moving tickets to another department later resets them to Open and wipes the original department's SLA and automation context. For multi-department setups, this is a deal-breaker. (help.zoho.com)
Data center routing matters
EU orgs must use desk.zoho.eu, AU orgs use desk.zoho.com.au, IN orgs use desk.zoho.in. Hitting the wrong endpoint returns authentication errors — not a routing error that names the correct URL. Always derive the base URL from the api_domain field in your token response, not from hardcoded assumptions.
Throughput math
At 180 requests/minute, extracting a ticket with its messages takes at least 2 API calls. For 10,000 tickets, that's ~20,000 calls minimum — roughly 111 minutes at full throttle, before accounting for contacts, attachments, or pagination.
Thread timestamps cannot be preserved
Threads and comments added via the Threads and Comments APIs carry the current timestamp, not a historical one. If exact thread timestamps are critical, the only workaround is to prepend the original timestamp as a metadata line in the thread body itself — for example, a line reading [Original reply: 2023-06-15 10:30 UTC] before the message content.
The runbook
Work top to bottom. Tick steps as you go — your progress is saved in this browser.
01 Discovery Establish why you are moving, what "done" means, and who signs off.
Objective A written scope with agreed success criteria, a named owner per workstream, and a budget approved by finance.
Keep these open
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Pull the real numbers out of LiveAgent
Export counts for tickets (open and closed separately), contacts, organisations, attachments, macros, triggers, automations, views and SLA policies. Note the oldest ticket date — history depth drives the whole timeline. Estimating from memory is the single most common cause of a blown migration window.
Data Profiler Get real record counts instead of estimating from memory -
Decide what history actually moves
Agree a cut-off with the support lead: all history, last 24 months, or open tickets plus a read-only archive. Every extra year of closed tickets adds API time and cost without adding much agent value. Get this in writing — it is the decision people relitigate mid-cutover.
A "move everything" default is what turns a two-week migration into a two-month one.
COI & ROI Calculator Build the 36-month business case you will need for sign-off -
Confirm Zoho Desk can hold your support model
Walk your current workflow through Zoho Desk: multi-brand, business hours, SLA targets, CSAT, side conversations, public vs internal notes, and any channel you depend on (voice, chat, WhatsApp, social). List anything with no native equivalent — those are project risks, not configuration details.
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Build the business case
Model licence delta, migration effort, agent retraining, and the cost of staying put (Cost of Inaction). Executives approve a number, not a plan, and you will be asked for it again at the go/no-go.
Helpdesk Migration Planner Turn ticket volume into a dated LiveAgent → Zoho Desk 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.
Don't move on until
- Record counts confirmed for tickets, contacts, organisations and macros
- Success criteria signed off by the support lead
- Freeze window provisionally booked with the business
02 Data Audit Find out what is actually in the data before you try to move it.
Objective A profiled, cleaned export with every quality defect either fixed at source or explicitly accepted.
Keep these open
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Take a full LiveAgent export and profile it
Export to CSV or JSON and profile every file: row counts, null rates per column, distinct values, and type consistency. Compare row counts against the API totals from Discovery — a gap here means your export is silently truncated, usually by pagination.
Data Profiler Profile the LiveAgent export for nulls, outliers and type drift -
Validate file structure before anyone writes a transform
Check delimiters, quoting, encoding (expect UTF-8, watch for BOMs and Latin-1), duplicate headers, and embedded newlines in ticket bodies. Ticket descriptions with raw newlines and commas break naive CSV parsers and silently shift columns.
A single unescaped quote in one ticket body can shift every subsequent column without any error.
CSV Validator Catch broken headers and ragged rows in the raw export -
Inventory PII and set retention
Scan for emails, phone numbers, payment card fragments, national IDs and anything else regulated in ticket bodies and custom fields — support tickets are where customers paste things they should not. Decide what gets migrated, masked, or dropped, and record the legal basis.
Ticket bodies and attachments routinely contain card and ID data that never appears in a structured field.
PII & Compliance Scanner Find regulated fields before they land in a new system -
Quantify duplicates, orphans and dead references
Count duplicate contacts (same email, different casing), tickets whose requester no longer exists, organisations with no members, and attachments whose parent ticket is gone. Fix these in LiveAgent where you can — migrating them just moves the mess.
Data Cleaner Strip empty rows, stray whitespace and dead columns -
Clean and normalise the export
Trim whitespace, drop empty rows and columns, normalise casing on emails and tags, and standardise every timestamp to UTC ISO 8601. Timezone drift is invisible at load time and shows up weeks later as SLA reports nobody can reconcile.
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Produce a masked copy for sandbox work
Generate a realistic but fake version of the export for testing and for any vendor who needs sample data. Loading real customer PII into a sandbox is a breach in most jurisdictions, and sandboxes are rarely covered by your DPA.
PII Masker Generate a safe copy for sandbox and vendor testing
LiveAgent → Zoho Desk specifics
- Total ticket count by date window
- determines timeline and API credit budget. If any month exceeds 10,000 tickets, you must shard extraction queries further since LiveAgent's API returns at most 10,000 records per filter. (support.liveagent.com)
- Departments
- map each LiveAgent department to a Zoho Desk department; create a catch-all archive department for tickets that lack clear routing data
- Agent list
- agents must exist in Zoho Desk before ticket assignment
- Attachment volume
- large attachments slow extraction and may hit Zoho's per-file upload limits
- Knowledge base articles
- count articles, categories, and languages
Don't move on until
- Export parses cleanly with no ragged rows or encoding errors
- PII inventory complete and retention decisions recorded
- Duplicate and orphan records quantified and triaged
03 Field Mapping Turn two schemas into one signed-off mapping spec.
Objective A reviewed field-level mapping covering every object, with an explicit decision for every field that has no target.
Keep these open
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Generate the first-pass LiveAgent → Zoho Desk field map
Start from an automated match on both schemas, then review every row by hand. Automated matching gets the obvious 70% right and is confidently wrong on the rest — especially anything named "type", "status" or "custom_field_1".
Schema Mapper Opens pre-loaded with the LiveAgent → Zoho Desk 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 Zoho Desk 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.
LiveAgent → Zoho Desk specifics
- Custom fields
- document every field code name, type, and validation rule
- Custom field values
- verify picklist values transferred correctly
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 Zoho Desk sandbox that reconciles cleanly and has been reviewed by real agents.
Keep these open
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Stand up a Zoho Desk 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 Zoho Desk'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 Zoho Desk, agents working in the new system, and a rollback path that stayed available throughout.
Keep these open
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Pre-load history before the freeze
Load closed tickets and contacts days or weeks ahead while LiveAgent stays live. Only open tickets and the final delta need to move inside the freeze — this is the single biggest lever on window length.
Helpdesk Migration Planner Size the freeze window from Zoho Desk's real API limits -
Publish the runbook with times, owners and abort criteria
A timed sequence: freeze start, final export, delta load, channel switch, smoke test, go/no-go, agent switch. Name who does each step and the explicit condition that triggers a rollback. Decide the abort criteria before the night, when nobody wants to be the one to call it.
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Freeze LiveAgent and take the final delta
Stop new ticket creation, let agents finish in-flight replies, then export everything changed since the pre-load. Announce the freeze to the whole business, not just support — someone always tries to raise a ticket during it.
Tickets created during an unenforced freeze land in the old system and are the most common source of permanently lost data.
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Load the delta and open tickets
Run the delta load, then reconcile counts before touching any channel. Do not repoint email until the delta has verified — an inbound ticket arriving mid-load is far harder to untangle than a few extra minutes of freeze.
Migration Validation Tool Confirm the final delta landed before you reopen -
Repoint channels and verify with live traffic
Switch email forwarding and MX or connector settings, update chat widgets and web forms, and re-authorise integrations. Then send real test tickets through every channel and confirm each lands, routes and triggers the right automation.
Email forwarding changes can take up to a full DNS TTL to propagate — check the TTL days in advance and lower it if needed.
Cron Expression Builder Schedule the delta syncs that run through the freeze -
Run the go/no-go and switch the agents
Walk the exit criteria with the decision-maker, call it explicitly, then move agents over with a named person on hand for the first few hours. Keep LiveAgent read-only rather than cancelled — cancelling the old contract on day one removes your only fallback.
LiveAgent → Zoho Desk specifics
- Initial load
- Migrate all historical data up to a specific timestamp (e.g., Friday at midnight).
- Delta load
- Push updates to Zoho Desk. Use ticketExtId to detect whether the Zoho record already exists; update if yes, create if no.
- Channel cutover
- Update email forwarding, chat widgets, and web forms to point to Zoho Desk.
Don't move on until
- Full historical load complete and counts matched
- Inbound channels repointed and verified with live test tickets
- Rollback decision point passed explicitly, not by default
06 Validation Prove the migration is complete, then close it out.
Objective Documented evidence that data, workflow and reporting all survived, and a signed acceptance.
Keep these open
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Run the full reconciliation
Compare source and target on every object: total counts, counts by status, counts by group, attachment counts, and field-level spot checks on a random sample. Produce one report you can hand to an auditor.
Migration Validation Tool Reconcile LiveAgent and Zoho Desk 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 Zoho Desk, and file the evidence with your PII decisions from the audit phase.
PII & Compliance Scanner Produce the compliance evidence your auditor will ask for -
Sign off, then decommission on a schedule
Get written acceptance against the Discovery success criteria. Keep LiveAgent read-only for an agreed period (30-90 days is typical), take a final archive export, and only then cancel. Diarise the decommission date so it does not quietly renew.
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Record counts
verify ticket, contact, and account counts match the source
LiveAgent → Zoho Desk specifics
- Spot-check conversations
- randomly sample 50–100 tickets and verify thread order, content, and visibility
- Agent assignments
- confirm tickets are assigned to the correct agents
- Tag associations
- verify tags are present on the correct tickets
- Attachment integrity
- spot-check that attachments open and render correctly
- Internal note visibility
- verify that private comments are not visible in the customer Help Center
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.
Status Recommended Zoho Desk Status
| LiveAgent field | Zoho Desk field | Notes |
|---|---|---|
| New | Open | Direct map |
| Open (Answered) | Open or custom "Answered" | Create custom status if SLA behavior differs |
| Postponed | On Hold | Direct map |
| Resolved | Closed or custom "Resolved" | LiveAgent treats Resolved as a pre-close state; enforce via Blueprint if needed |
| Closed | Closed | Direct map |
| Spam / Deleted | Skip or archive | Do not migrate into active departments; isolate in a hidden archive department |
Concept Equivalent
| LiveAgent field | Zoho Desk field | Notes |
|---|---|---|
| Ticket | Ticket | 1:1, but status mapping required |
| Message (type 'M') | Thread (email reply) | Filter by message type; normalize for v5.62 note changes |
| Internal Note | Comment (private) | Visibility flag must be set correctly |
| Contact | Contact | lastName is required in Zoho Desk |
| Company | Account | accountName is required in Zoho Desk |
| Department | Department | Departments control layouts, statuses, and routing in Zoho |
| Agent | Agent | Must be pre-provisioned before ticket import |
| Tag | Tag | Direct mapping via associate/dissociate API |
| Custom Field | Custom Field (cf_*) | Type mapping required |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Tickets | medium | Tickets migrate as 1:1 records but require status remapping and a valid departmentId on every payload, making bulk failures likely if the department or status mapping table is incomplete at load time. |
| Threads (Email Replies) | high | LiveAgent stores email replies as flat message objects that must be correctly identified by type flag and posted to Zoho Desk's separate Threads API endpoint, with v5.62 type inconsistencies creating a real risk of misrouting customer-facing content. |
| Internal Notes | high | Internal notes must be routed to Zoho Desk's Comments API with the private visibility flag set correctly; a type-parsing error caused by the v5.62 normalization issue could expose agent-only notes to customers. |
| Contacts | low | LiveAgent's Contact-to-Company model maps cleanly to Zoho Desk's Contact-to-Account model, though the 'lastName' field is required in Zoho Desk and must be populated or defaulted for contacts that lack it in LiveAgent. |
| Accounts (Companies) | low | Company records map directly to Zoho Desk Accounts with a required 'accountName' field, representing a minor transformation risk that is easily handled with pre-import validation. |
| Attachments | high | Attachments must be fetched from LiveAgent and re-uploaded to Zoho Desk as separate API calls per file, with large volumes significantly extending migration runtime and per-file size limits potentially causing silent failures. |
| Custom Fields | medium | Each LiveAgent custom field type must be mapped to a Zoho Desk equivalent 'cf_*' field with matching validation rules, and any undiscovered or undocumented fields found after the audit begins can cause mid-migration payload rejections. |
| Departments | medium | Departments are architectural anchors in Zoho Desk controlling layouts, statuses, and routing, so loosely-defined LiveAgent departments with tag-based sub-routing require deliberate redesign decisions before migration can begin. |
| Tags | low | Tags have a direct mapping path via Zoho Desk's associate/dissociate API and do not carry structural dependencies, making them one of the lower-risk entities in the migration. |
| Knowledge Base Articles | medium | KB articles, categories, and multilingual variants must be counted and mapped during the pre-migration audit, as they cannot be migrated via CSV import and require API-level handling with no dedicated LiveAgent connector in Zwitch. |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
Message Type Normalization
LiveAgent v5.62 changed internal note typing from message type 'N'/group 'I' to type 'M'/group 'U', meaning a single ticket can contain both styles with mixed integer and UUID IDs, requiring semantic normalization before routing payloads to Zoho Desk's Threads or Comments API.
Department Architecture Mismatch
Every Zoho Desk ticket must be assigned a valid departmentId at creation time, requiring upfront department design and mapping from LiveAgent's loosely-used routing units before any API writes begin.
Agent Pre-Provisioning Dependency
Zoho Desk maps ticket ownership by agent email address at import time, so any agent not pre-provisioned with a matching email before ticket load will cause assignments to fall back silently to the primary support administrator.
Ticket Status Lossy Collapse
LiveAgent's five fixed statuses do not map directly to Zoho Desk's default status set, requiring explicit custom status creation per department and Blueprint configuration to preserve SLA behavior for states like 'Postponed' and 'Resolved'.
API Rate and Volume Limits
LiveAgent's API caps at 180 requests per minute and returns at most 10,000 records per filter query, while Zoho Desk enforces a daily credit system that varies by plan, requiring sharded extraction windows and credit budgeting before pipeline execution.
Zwitch Single-Department Constraint
Zoho's first-party Zwitch migration tool loads all data into a single target department, and moving tickets to another department afterward resets their status to Open and strips the original SLA and automation context.
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
Can I migrate LiveAgent data to Zoho Desk using a CSV export?
Only for small, flat datasets. LiveAgent's native CSV export only includes ticket metadata and drops conversation threads, internal notes, and attachments. Zoho's self-serve import is limited to 30 MB uploads and 10,000 rows and cannot import threads or comments. For a complete migration, use both platforms' APIs.
How do I preserve original ticket timestamps when migrating to Zoho Desk?
Use Zoho Desk's Imports API (POST /api/v1/imports), which accepts createdTime and modifiedTime fields. The standard Create Ticket API (POST /api/v1/tickets) ignores historical timestamps and stamps all tickets with today's date. Note that conversation threads and comments added via the Threads and Comments APIs will still carry the current timestamp.
What are Zoho Desk's API rate limits for migration?
Zoho Desk uses a daily credit system, not a per-minute rate limit. Enterprise plans get 100,000 base credits plus 1,000 per user per day. Creating a ticket costs 1 credit; listing records costs 3. You can request additional credits from support@zohodesk.com for large migrations.
How do LiveAgent ticket statuses map to Zoho Desk?
LiveAgent's New and Open map to Zoho Desk's Open status. Postponed maps to On Hold. Resolved and Closed map to the Closed state group. Zoho Desk supports custom statuses per department, so you can create a custom Resolved or Answered status if your workflow requires it.
Can LiveAgent automation rules and SLA policies be migrated automatically?
No. Automation rules, SLA policies, canned messages, gamification settings, and report configurations have no programmatic migration path. They must be manually rebuilt as Zoho Desk Workflow Rules, Blueprints, SLAs, Snippets, or Email Templates.