Use Zendesk's Ticket Import API to preserve timestamps. Files over 50MB need external hosting. Plan 5 to 12 business days for a single-brand Re:amaze migration.
Migrating from Re:amaze to Zendesk has no native migration path and requires significant data model translation. Re:amaze uses a continuous, reopenable Conversation model with freeform custom data hashes, while Zendesk enforces discrete Ticket lifecycles with pre-defined Custom Fields and structured CC/Follower models. Custom work is required to transform conversations into tickets, map recipient arrays to Zendesk's capped CC model, pre-create custom fields from Re:amaze's freeform data hashes, and manually rebuild Response Templates (which use Shopify Liquid variables), Workflows, and staff permissions.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
Undocumented pagination behavior
Re:amaze's conversation listing paginates with page and page_size parameters but does not guarantee consistent ordering during active support operations. Extract during low-traffic hours to avoid missed or duplicated records.
Zendesk rejects tickets where the requester is suspended
If any Re:amaze contacts were archived or blocked, you must either skip their conversations or temporarily create them as active users in Zendesk.
GDPR and data privacy
Migrating customer PII between platforms requires a lawful basis under GDPR (typically legitimate interest or contract performance). Ensure you have a Data Processing Agreement (DPA) with both Re:amaze and Zendesk. If any contacts have exercised right-to-erasure requests in Re:amaze, do not migrate their data. For EU-based teams, document the migration in your Records of Processing Activities (ROPA).
Always tag imported tickets
Add a tag like migrated-from-reamaze to imported tickets and exclude them from SLA reports. Zendesk metrics and SLAs are not supported for imported tickets and will produce inaccurate data if included.
Empty comment bodies will fail
Zendesk's Ticket Import API rejects comments with empty bodies. Re:amaze messages that contain only an attachment and no text body need placeholder text like "(Attachment only)" to prevent rejection.
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 Reamaze
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 Zendesk can hold your support model
Walk your current workflow through Zendesk: 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 Reamaze → Zendesk 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.
Reamaze → Zendesk specifics
- Integration ecosystem
- Zendesk's marketplace lists 1,500+ pre-built integrations. Re:amaze lists roughly 40 native integrations. Teams needing deep connections to Salesforce, Jira, or BI tools outgrow Re:amaze's ecosystem quickly.
- Enterprise reporting and SLA management
- Zendesk Explore offers native SLA policies, custom dashboards, and granular CSAT/NPS analytics. Re:amaze's built-in reporting covers volume and response time but lacks the depth required for enterprise compliance.
- Multi-channel scale
- Zendesk's omnichannel routing engine, Answer Bot, and AI-powered Intelligent Triage are architecturally more mature for teams handling 50,000+ conversations per month.
- HIPAA and compliance posture
- Zendesk offers a HIPAA-eligible environment (Business Associate Agreement on Enterprise plans). Re:amaze does not offer a comparable compliance tier.
- Ticket lifecycle governance
- Re:amaze centers on conversations with Shopify order data, draft orders, refunds, and Liquid variables inside the support workflow. Zendesk gives you first-class ticket lifecycle states, multi-brand governance, Guide permissioning, and a dedicated historical Ticket Import API.
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 Reamaze 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 Reamaze 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 Reamaze 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
Reamaze → Zendesk specifics
- Re:amaze Cues (proactive messages)
- No import path. Rebuild as Zendesk proactive messaging triggers.
- Re:amaze Peek (live visitor activity)
- Zendesk does not have a native equivalent.
- E-commerce sidebar data (Shopify order context, BigCommerce data)
- This is a live integration, not stored data. Reinstall the Zendesk Shopify app post-migration. Decide which parts should become Zendesk fields, tags, or rebuilt integrations.
- Unlisted FAQ articles
- Re:amaze supports unlisted articles in help content, but the public article API documents only published, draft, and internal states. Unlisted articles need explicit testing and manual handling.
- Staff permissions
- Re:amaze exposes a staff role hash, but its own docs indicate this is not a stable permissions API. Rebuild permissions in Zendesk manually.
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 Reamaze → Zendesk 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 Reamaze → Zendesk 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 Zendesk 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 Zendesk sandbox that reconciles cleanly and has been reviewed by real agents.
Keep these open
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Stand up a Zendesk 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 Zendesk'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.
Reamaze → Zendesk specifics
- Professional and above
- One sandbox included. Request via Zendesk Admin Center → Account → Sandbox.
- Team and Growth
- No sandbox included. Use a separate trial Zendesk instance as a test target, or request a temporary sandbox from Zendesk support.
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 Zendesk, 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 Reamaze 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 Zendesk'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 Reamaze 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 Reamaze 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 Reamaze and Zendesk 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 Zendesk, 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 Reamaze 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.
amaze Objects Map Zendesk
| Reamaze field | Zendesk field | Notes |
|---|---|---|
| Conversation | Ticket | One Conversation = one Ticket. Use Re:amaze slug as Zendesk external_id for idempotent reruns and reconciliation. |
| Message (visibility: 0) | Public Comment | Request include=original_body and map HTML to html_body. Re:amaze /messages returns newest first—reverse before import. |
| Message (visibility: 1) | Internal Note | Map to Zendesk comment with public: false. |
| Message (visibility: 2) | Skip or audit note | Collision-detected system message, not ordinary customer history. Fold into a private note or skip entirely. |
| Contact | User (end-user) | Contacts can hold multiple identities (email, phone, social). Map primary email first, then add identities. Contacts are account-scoped, not brand-scoped. |
| Staff | User (agent) | Must be created before ticket import so assignee_id resolves. Re:amaze staff role is informational only in the public API. Zendesk tickets cannot be assigned to an agent without a group. |
| Channel | Group | Re:amaze Channels (e.g., "support", "sales") map to Zendesk Groups. No single Zendesk field preserves all Re:amaze channel meaning—preserve category slug and origin in custom fields or tags. |
| Brand | Brand | Direct 1:1 mapping if using Zendesk multi-brand. Must exist before ticket import. |
| Tag | Tag | Direct 1:1 transfer. Zendesk tags are lowercase and do not support spaces (spaces become underscores). Verify formatting before import. |
| Article (FAQ) | Help Center Article | Requires separate Help Center API calls. HTML body transfers, but Re:amaze-specific embeds do not. Map Re:amaze Topics to Zendesk Sections. |
| Response Template | Macro | Must be manually rebuilt. Re:amaze exposes templates via API, but Shopify Liquid variables do not transfer. No automated migration path. |
| Workflow | Trigger/Automation | Must be manually rebuilt. No programmatic migration path. |
| Note (Contact Note) | User internal note | Zendesk User API supports notes field (text only). |
| Custom Data (data hash) | Custom Ticket/User Field | Freeform key-value pairs must be mapped to pre-created Zendesk Custom Fields with defined types. |
| Recipients | CCs / Followers | Re:amaze recipients array must be split into Zendesk collaborator_ids (CCs) or follower_ids. Zendesk caps CCs at 48. |
| Satisfaction Rating | Satisfaction Rating | Historical ratings can be imported but require custom handling. Zendesk has its own CSAT system. |
| Shopify/BigCommerce context | Zendesk Shopify App sidebar | Live e-commerce context does not migrate. Reconnect via Zendesk's Shopify integration post-migration. |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Tickets (Conversations) | medium | One-to-one mapping is straightforward, but status translation (especially Archived to Closed and the irreversibility of Zendesk's Closed state) and message ordering (Re:amaze returns newest first) require careful handling. |
| Comments (Messages) | medium | Public, internal, and collision-detected messages must be mapped by visibility flag, HTML bodies require the original_body include parameter, and message order must be reversed before import. |
| Contacts (Users) | medium | Contacts can hold multiple identities (email, phone, social) and are account-scoped rather than brand-scoped, creating deduplication risks in multi-brand migrations. |
| Custom Fields | high | Re:amaze's freeform data hash must be discovered, typed, and pre-created as explicit Zendesk Custom Fields, with no automated schema translation available. |
| Tags | low | Direct one-to-one transfer is supported, but Zendesk enforces lowercase and replaces spaces with underscores, requiring formatting verification before import. |
| Help Center Articles | medium | HTML body content transfers via a separate Help Center API, but Re:amaze-specific embeds do not render, Topics must map to Sections, and unlisted articles require manual handling. |
| Attachments | high | Attachments must be individually downloaded from Re:amaze and re-uploaded to Zendesk, creating significant API load and potential failures for oversized files. |
| Response Templates (Macros) | high | Shopify Liquid variables in Re:amaze templates have no Zendesk equivalent, and there is no automated migration path—all macros must be manually rebuilt. |
| Workflows (Triggers/Automations) | high | No programmatic migration path exists; all Re:amaze workflows must be manually audited and recreated as Zendesk Triggers and Automations. |
| Satisfaction Ratings | medium | Historical ratings can be imported but require custom handling since Zendesk has its own CSAT system with a different data model. |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
Conversation vs. Ticket Lifecycle
Re:amaze Conversations are continuous, reopenable threads, while Zendesk Tickets follow a discrete lifecycle where Closed tickets cannot be reopened, requiring careful status mapping to avoid data loss.
Freeform Custom Data Translation
Re:amaze stores custom fields as a freeform key-value data hash on Conversations and Contacts, but Zendesk requires pre-defined Custom Fields with explicit types (text, dropdown, checkbox, numeric, regex), necessitating schema discovery and field creation before import.
Recipient to CC Mapping
Re:amaze adds recipients to conversations without a traditional CC model, while Zendesk enforces a structured CC and Follower system capped at 48 email_ccs, risking silent truncation on high-recipient threads.
Response Template Rebuild
Re:amaze Response Templates use Shopify Liquid variables that have no equivalent in Zendesk Macros, requiring manual recreation with no automated migration path available.
Multi-Brand Contact Deduplication
Re:amaze API requests are brand-scoped but contacts are account-scoped, creating duplicate and ownership edge cases when migrating across multiple brands into Zendesk.
E-commerce Context Loss
Live Shopify and BigCommerce sidebar data (order context, refunds, draft orders) does not migrate as stored data and must be reconnected post-migration via Zendesk's native Shopify integration.
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
Can I migrate Re:amaze to Zendesk without losing data?
Yes, with the correct approach. Using Zendesk's Ticket Import API preserves original timestamps and comment ordering. The primary data-loss risk is attachments between 50MB and 100MB, which exceed Zendesk's 50MB per-file limit and must be hosted externally. Workflows, Cues, and live e-commerce sidebar data (Shopify/BigCommerce) do not migrate and must be rebuilt.
How long does a Re:amaze to Zendesk migration take?
A typical mid-size migration (10,000 to 50,000 conversations) takes 7 to 13 business days. Small instances under 5,000 conversations can complete in 5 to 7 days. Multi-brand instances with 100,000+ conversations and complex attachments may require 2 to 3 weeks.
What data cannot be migrated from Re:amaze to Zendesk?
Re:amaze Workflows, Cues (proactive messages), Peek (live visitor monitoring), co-browsing sessions, staff permissions, unlisted article visibility, and live e-commerce sidebar data cannot be migrated programmatically. Response Templates must be manually recreated as Zendesk Macros.
Does the Zendesk Ticket Import API trigger automations or SLA timers?
No. Tickets created via the Import API do not trigger Zendesk Triggers or Automations on initial import. If an imported ticket is later updated, triggers will resume. Zendesk metrics and SLAs are not supported for imported tickets and will produce inaccurate data.
How much does a Re:amaze to Zendesk migration cost?
Costs vary by approach. A DIY API migration costs 40 to 80+ hours of internal engineering time. Third-party tools like Help Desk Migration charge per-record fees that can exceed $1,000 for large datasets. Managed migration services typically charge a fixed project fee based on volume and complexity.