Re:amaze to Gorgias is an API-to-API migration taking 5 to 14 days. The biggest risk is omitting sent_datetime, which causes Gorgias to email imported messages to live customers.
There is no native migration path from Re:amaze to Gorgias; the transfer is an API-to-API project requiring custom scripting against both platforms' REST APIs. The fundamental data model difference is that Re:amaze is conversation-led and brand-scoped with flexible custom data storage, while Gorgias enforces a strict ticket model where every ticket must begin with a message, supports only two statuses (open and closed), limits custom fields to 25 per ticket and 4 per customer, and operates as a single-brand-per-account system. Custom work is required to map and collapse statuses, flatten excess custom data attributes, rebuild all automations and workflows from scratch, and carefully set the sent_datetime field on every imported message to prevent Gorgias from re-sending historical messages to customers.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
TL;DR: Re:amaze to Gorgias Migration
A Re:amaze to Gorgias migration is a medium-complexity, API-to-API project. Realistic timeline: 5 to 14 days for a typical dataset of 10,000 to 100,000 conversations. The single biggest risk is the sent_datetime trap — omitting this field when creating messages via the Gorgias API causes Gorgias to treat every imported historical message as new outbound mail and send it to your customers. Re:amaze's five conversation statuses collapse to Gorgias's two API statuses (open and closed). Satisfaction ratings, FAQ articles, response templates, and workflows cannot be migrated via the Gorgias API and must be rebuilt manually. Teams with fewer than 5,000 conversations and no complex custom data can self-serve with a careful API script. Anything larger, with multi-channel threads or multi-brand setups, benefits from a managed migration service.
CSAT history does not migrate
Historical customer satisfaction ratings cannot be imported into Gorgias via the API. Export your Re:amaze CSAT data to CSV for historical reporting and communicate this baseline reset to CS leadership before cutover. Plan to re-establish CSAT benchmarks over the first 30 days in Gorgias.
Never omit sent_datetime
Any message created via the Gorgias API without sent_datetime is treated as a new outbound message. Gorgias will asynchronously send it to the customer via the configured channel. This is the single most common cause of migration disasters. Always set sent_datetime to the original Re:amaze created_at timestamp for every imported message — on both the initial message and all subsequent appended messages. (developers.gorgias.com)
The runbook
Work top to bottom. Tick steps as you go — your progress is saved in this browser.
01 Discovery Establish why you are moving, what "done" means, and who signs off.
Objective A written scope with agreed success criteria, a named owner per workstream, and a budget approved by finance.
Keep these open
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Pull the real numbers out of 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 Gorgias can hold your support model
Walk your current workflow through Gorgias: 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 → Gorgias 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 → Gorgias specifics
- Deeper Shopify integration
- Gorgias surfaces live order data, refund actions, and shipping status directly inside the ticket sidebar. Agents can process returns, duplicate orders, and award loyalty points without switching tabs. Re:amaze connects to Shopify but does not offer in-ticket transactional order actions at the same depth.
- Ticket-based pricing
- Gorgias charges by billable ticket volume (only tickets where an agent or automation sends a response count as billable), not by seat count. For teams with many agents but moderate ticket volume, this can reduce costs. Note: imported closed tickets do not count as billable tickets since no new agent response is generated.
- AI Agent capabilities
- Gorgias's AI Agent auto-resolves repetitive tickets using store data, order history, and shipping information. It operates as a fully autonomous resolution loop tied to e-commerce context — handling order status inquiries, cancellation requests, and return initiation without human intervention.
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
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 → Gorgias 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 → Gorgias 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 Gorgias 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.
Reamaze → Gorgias specifics
- Custom field verification
- Verify that ticket fields and customer fields contain correct values and that no data was truncated at the 2,000-character limit.
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 Gorgias sandbox that reconciles cleanly and has been reviewed by real agents.
Keep these open
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Stand up a Gorgias 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 Gorgias'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 → Gorgias specifics
- Field-level spot checks
- Sample 50 tickets at random across all channels (email, chat, social, phone). Verify subject, tags, status, message count, customer email, channel type, and timestamps match source data.
- Thread integrity
- Sample at least one long thread (10+ messages) from each major channel. Verify chronological order of messages is correct and no messages are missing or duplicated.
- Internal note preservation
- Confirm that Re:amaze internal notes (visibility: 1) appear as internal notes in Gorgias, not as customer-facing messages. Check at least 10 tickets with internal notes.
- No outbound sends
- Check the Gorgias activity log to confirm no imported messages were sent to customers. This is the most important validation check. Search for any "email sent" events on tickets with external_id containing reamaze_.
- Shopify integration test
- Open a ticket for a known customer with recent orders. Confirm order data appears in the Gorgias sidebar.
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 Gorgias, 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 Gorgias'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 Gorgias 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 Gorgias, 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.
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Record count reconciliation
Compare total conversations extracted from Re:amaze against total tickets created in Gorgias. Tolerance: zero discrepancy. Account for any intentional exclusions (e.g., spam conversations). Separately reconcile customer counts.
Reamaze → Gorgias specifics
- Attachment verification
- For a sample of 20 tickets with attachments, confirm files are accessible and downloadable in Gorgias. Verify image attachments render correctly inline.
- Search verification
- Search by subject, email, phone, and external_id inside Gorgias to confirm records are discoverable.
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 Gorgias
| Reamaze field | Gorgias field | Notes |
|---|---|---|
| Conversation | Ticket | Slug-to-ID mapping required. Status collapses from 5+ states to 2. Use slug as external_id. |
| Message (visibility: 0) | Message (public) | Must set sent_datetime to prevent re-sending. Load oldest to newest. |
| Message (visibility: 1) | Message (channel: internal-note) | Internal notes carry over cleanly. |
| Contact | Customer | Re:amaze contacts are account-level, not brand-level. Dedupe before load. Email is the primary identifier; phone numbers must be E.164 formatted (e.g., +14155551234). |
| Contact Identities | Customer channels | Re:amaze identities span email, Twitter, Facebook, Instagram, and mobile. See social channel notes below. |
| Staff User | User | Gorgias users must exist before ticket assignment. Create or invite first. |
| Brand | N/A (account-scoped) | Gorgias is single-brand per account. Map to tags, teams, or separate accounts. |
| Channel / Category | Integration / Channel type | Map Re:amaze channel values to Gorgias channel strings: email, chat, phone, sms, api. |
| Tag | Tag | Direct 1:1 mapping. Tags are created on-the-fly in Gorgias when included in ticket creation. |
| Custom Data (conversation) | Ticket Field or meta | Max 25 active ticket fields. Overflow goes to meta JSON. |
| Custom Data (contact) | Customer Field | Max 4 active customer fields. Text capped at 2,000 characters. |
| FAQ Article | N/A | Gorgias Help Center articles must be recreated manually or via separate import. |
| Satisfaction Rating | N/A | Historical CSAT scores cannot be imported via the Gorgias API. Baseline resets at go-live. |
| Response Template | Macro | No API import path for full macro behavior. Text can be imported via Gorgias macro CSV (fields: name, body_text, tags, id). Actions, variables, and attachments must be rebuilt manually. |
| Workflow / Automation | Rule | No export from Re:amaze. Gorgias Rules are event-driven and must be rebuilt from scratch. |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Tickets (Conversations) | medium | Conversations migrate as tickets via API but require slug-to-ID mapping, status collapsing from 5+ states to 2, and careful message ordering to satisfy Gorgias's strict first-message-in-payload requirement. |
| Messages | high | Omitting the sent_datetime field on imported messages causes Gorgias to treat every historical message as new outbound mail and send it to customers, making this the single highest-risk entity in the migration. |
| Contacts (Customers) | medium | Re:amaze contacts are account-level and may have duplicates across brands, requiring deduplication before load and E.164 formatting for phone numbers. |
| Tags | low | Tags have a direct 1:1 mapping and are auto-created in Gorgias when included in the ticket creation payload, making them the lowest-risk entity to migrate. |
| Custom Fields (Conversation) | high | Gorgias limits active ticket fields to 25 with 2,000-character text caps, so Re:amaze accounts with extensive custom data require significant flattening and overflow handling into meta objects or tags. |
| Custom Fields (Contact) | high | Gorgias allows only 4 active customer fields, so any Re:amaze account with more than 4 customer data attributes requires lossy compression or alternative storage strategies. |
| Satisfaction Ratings (CSAT) | high | Historical CSAT scores cannot be imported via the Gorgias API at all, resulting in a complete baseline reset at go-live with no programmatic workaround. |
| FAQ Articles | high | Gorgias Help Center articles have no bulk API import path and must be manually recreated, which is labor-intensive for large knowledge bases. |
| Automations and Workflows | high | Re:amaze workflows cannot be exported, and Gorgias Rules use a fundamentally different event-driven architecture, requiring complete manual rebuilding from scratch. |
| Social Channel Conversations | medium | Historical Facebook, Instagram, and Twitter conversations import as text transcripts only, losing platform threading context and requiring OAuth reconnection for future live messages. |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
Status Model Collapse
Re:amaze's five or more conversation states (Open, Responded, Done, On-Hold, Spam, Archived) must be collapsed into Gorgias's two API statuses (open and closed), requiring tag-based preservation of original statuses for reporting.
Strict Message Dependency
Gorgias cannot create an empty ticket shell—the first message must be included in the ticket creation payload, requiring careful ordering and bundling of Re:amaze conversation data during extraction.
Custom Data Field Limits
Re:amaze allows unlimited key-value custom data on conversations and contacts, but Gorgias caps active ticket fields at 25 and customer fields at 4 (with 2,000-character text limits), forcing overflow data into tags or meta objects.
Multi-Brand to Single-Brand
Re:amaze supports multiple brands per account with separate channels and queues, while Gorgias is single-brand per account, requiring either consolidation with tag-based routing or provisioning of separate Gorgias instances.
Dual-Side API Rate Limits
Re:amaze enforces undocumented per-minute rate limits without Retry-After headers, while Gorgias uses a shared leaky bucket of 40 requests per 20 seconds (API key), making a 100,000-conversation migration take over two days of continuous runtime.
Non-Migratable Workflow Layer
Satisfaction ratings, FAQ articles, response templates with actions and variables, and automation rules have no API import path in Gorgias and must be manually rebuilt from scratch post-migration.
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
How long does a Re:amaze to Gorgias migration take?
A typical Re:amaze to Gorgias migration takes 5 to 14 days end to end, depending on conversation volume and data complexity. The actual data transfer for 10,000 conversations takes roughly 3 to 6 hours at Gorgias's API key rate limit of 40 requests per 20-second window. Script development, testing, and validation account for the rest of the timeline.
Will Gorgias resend imported messages to my customers?
Yes, if your migration script does not set the sent_datetime field on every imported message. When sent_datetime is empty, Gorgias treats the message as new outbound mail and sends it asynchronously. Always set sent_datetime to the original Re:amaze created_at timestamp.
What data cannot be migrated from Re:amaze to Gorgias?
Historical CSAT ratings, FAQ articles, response template actions, and workflow automations cannot be imported into Gorgias via the API. These must be rebuilt manually. Conversation history, messages, contacts, tags, and custom data attributes can all be preserved.
What are the Gorgias API rate limits for migration?
Gorgias enforces a leaky bucket rate limit of 40 requests per 20-second window for API key integrations and 80 requests per 20-second window for OAuth2 apps. The limit is per account, meaning all integrations share the same budget. Exceeding the limit returns a 429 error with a Retry-After header.
Is there a native Re:amaze to Gorgias migration tool?
Gorgias does not offer a built-in import wizard for Re:amaze. The Gorgias native importer supports Zendesk only. Re:amaze to Gorgias migrations must use both platforms' REST APIs or a third-party migration service like Help Desk Migration.