Helpdesk migration
Field-level mapping, validation, and rollback between Gmelius and Gorgias. We move data and schema; workflows are rebuilt natively in Gorgias.
Gmelius
Source
Gorgias
Destination
Compatibility
7 of 12
objects map 1:1 between Gmelius and Gorgias.
Complexity
CModerate
Timeline
2-4 weeks
Overview
Moving from Gmelius to Gorgias means leaving a Gmail-embedded collaboration layer for a purpose-built ecommerce helpdesk. Gmelius operates as an extension on top of Gmail, storing shared inboxes, labels, and conversations in Google Workspace rather than as independent records; Gorgias expects formal Tickets, Customers, and Macros in a standalone database. We resolve this structural gap by exporting via the Gmail API and Google Contacts API, then transforming every email thread into a Gorgias ticket with a linked customer record. Shared Labels become Tags, Email Templates become Macros, and SLA configurations transfer as custom metadata. Automation Rules and Kanban board configurations do not migrate as code; we screen-record the live rules UI during discovery and deliver a written reconstruction guide for Gorgias Rules and Views. Teams switching from Gmelius's per-user model to Gorgias's per-ticket model must validate volume assumptions before cutover to avoid billing surprises on low-volume plans.
Every standard and custom field arrives verified.
AI proposes the map; you confirm before any record moves.
Parent–child, lookups, and ownership stay linked.
Calls, emails, meetings — with original timestamps.
Documents, uploads, and inline notes move with the record.
Why teams make this switch
Leaving
What's pushing teams away
Choosing
What's pulling them in
Object mapping
Each row shows how a Gmelius object lands in Gorgias, including any object-level transformations, lookup resolution, or schema-design dependencies.
Typical mapping — final map is confirmed during the sample migration step.
Gmelius
Shared Inbox
Gorgias
Channel
lossyGmelius Shared Inboxes are workspaces inside Gmail that aggregate email threads from specific addresses (support@, sales@, billing@). We map each Shared Inbox to a Gorgias Channel configured with the same email address. Channel metadata (display name, incoming email address, team assignment) is replicated during setup. Teams with multiple Shared Inboxes (support@, sales@, general@) map to multiple Gorgias channels in a 1:1 relationship.
Gmelius
Email Conversation (thread)
Gorgias
Ticket
1:manyEach Gmelius conversation thread maps to a single Gorgias Ticket. We export the full thread via the Gmail API, extracting message bodies, timestamps, sender addresses, and attachment references. In Gorgias, the first message becomes the Ticket body and subsequent messages appear as ticket events in chronological order. External customer emails are linked to a Gorgias Customer record created from the sender's email address. Internal Gmelius notes (@mentions) become internal ticket comments in Gorgias visible only to agents.
Gmelius
Contact (via Google Contacts API)
Gorgias
Customer
1:1Gmelius does not maintain a standalone contact database; contacts live in Google Contacts. We export via Google Contacts API, extracting name, email address, phone number, company association, and any Gmelius-specific tags applied to conversations with that contact. Each contact becomes a Gorgias Customer record. Email address is the dedupe key: if a Customer with the same email already exists in Gorgias, we merge rather than duplicate. Custom fields on the Gmelius contact (if stored as Google Contact fields) migrate to Gorgias custom fields on the Customer object.
Gmelius
Shared Label
Gorgias
Tag
1:1Gmail labels used by Gmelius for conversation categorization (e.g., urgent, billing, escalated) are exported via the Gmail API and recreated as Gorgias Tags. Label-to-conversation associations are preserved as Tag assignments on the migrated Ticket. We deduplicate label names during extraction: if the same label name appears across multiple Shared Inboxes, we create a single tag in Gorgias and assign it to all relevant tickets.
Gmelius
Email Template
Gorgias
Macro
1:1Gmelius shared email templates with variable placeholders (merge fields) map to Gorgias Macros. We export the full template library including subject line, body HTML/text, and merge field syntax, then recreate as Gorgias Macros with the same variable syntax converted to Gorgias's supported format. Template folders map to Macro categories if the customer's Gorgias plan supports categorization.
Gmelius
Shared Draft
Gorgias
Macro
1:manyGmelius shared drafts are collaborative email drafts that exist in draft state within a Shared Inbox. Gorgias does not have a separate draft object. We export shared drafts as Gorgias Macros (saved responses) rather than live drafts, preserving the text and variable placeholders. The customer's admin can use Macros to recreate the same draft-to-send workflow in Gorgias.
Gmelius
User / Team Member
Gorgias
Agent
1:1Gmelius users correspond to Google Workspace accounts. We export the user list (display name, email address, role) and map them to Gorgias Agents. Gmelius role levels (member, admin) map to Gorgias Agent permission levels. If a Gmelius user has been deactivated but still has assigned conversations, we map those to a designated fallback agent in Gorgias to avoid orphaned tickets.
Gmelius
Automation Rule
Gorgias
Rule (rebuild as documented handoff)
lossyGmelius Automation Rules (conditional routing, auto-assignment, SLA timers, follow-up sequences) are stored as extension-local state with no export mechanism. We capture the active rules configuration during a live discovery walkthrough, screen-recording each rule's trigger, conditions, and actions. We deliver a written inventory of every active rule with a Gorgias Rule equivalent specification for the customer's admin to rebuild in Gorgias Rules. Multi-step rules with AI dispatching (Pro tier) require the most manual reconstruction effort.
Gmelius
Kanban Board
Gorgias
Views
lossyGmelius Kanban boards visualize email pipelines by status columns (e.g., Open, In Progress, Resolved). We map board column names to Gorgias Views with matching filters. Card-to-conversation associations are preserved during migration so that the ticket retains its column history. Custom board layouts with multiple columns per board require the customer's admin to configure equivalent Views in Gorgias, as Gorgias's view model is filter-based rather than board-based.
Gmelius
SLA Configuration
Gorgias
SLA (metadata on Ticket)
1:1SLA rules in Gmelius (first response time, next response time, resolution time by priority) are tier-gated (Growth and Pro plans). We export SLA metadata as custom fields on each migrated Ticket: sla_first_response_due__c, sla_resolution_due__c, sla_status__c. The customer's admin configures the active SLA policy in Gorgias for new tickets going forward. Historical SLA compliance data is preserved as field values but not enforced by Gorgias on imported tickets.
Gmelius
Email Analytics
Gorgias
Reports (rebuild required)
1:1Gmelius Email Analytics dashboards (thread volume, response times, SLA compliance, team performance) are tier-gated and do not export as data. We extract the underlying metrics (conversation count, thread timestamps, assignee, tag distribution) during migration so the customer's admin can rebuild Gorgias Reports from the imported ticket data. Historical dashboards are not replicated in Gorgias; the analytics timeline restarts at cutover.
Gmelius
Email Note / @mention
Gorgias
Internal Ticket Comment
1:1Gmelius email notes and @mentions inside threads are internal collaboration annotations. We export them as Gorgias internal comments on the relevant Ticket, preserving the note text, timestamp, and author (mapped via Google Workspace email to Gorgias Agent). Internal comments in Gorgias are visible only to agents, matching the privacy intent of Gmelius notes.
| Gmelius | Gorgias | Compatibility | |
|---|---|---|---|
| Shared Inbox | Channellossy | Fully supported | |
| Email Conversation (thread) | Ticket1:many | Fully supported | |
| Contact (via Google Contacts API) | Customer1:1 | Fully supported | |
| Shared Label | Tag1:1 | Fully supported | |
| Email Template | Macro1:1 | Fully supported | |
| Shared Draft | Macro1:many | Fully supported | |
| User / Team Member | Agent1:1 | Fully supported | |
| Automation Rule | Rule (rebuild as documented handoff)lossy | Fully supported | |
| Kanban Board | Viewslossy | Mapping required | |
| SLA Configuration | SLA (metadata on Ticket)1:1 | Fully supported | |
| Email Analytics | Reports (rebuild required)1:1 | Fully supported | |
| Email Note / @mention | Internal Ticket Comment1:1 | Fully supported |
Gotchas + challenges
Platform-specific issues from each side, plus the pair-specific challenges that don't show up on either platform's page on its own.
Gmelius gotchas
Gmail-only lock-in is irreversible for mixed email environments
No formal public API on lower tiers limits programmatic data export
Automation Rules are extension-local state with no export mechanism
All team members must share the same plan tier
Extension conflicts with other Gmail add-ons cause UI instability
Gorgias gotchas
AI Agent adds outcome-based fees on top of billable ticket costs
Overage billing for tickets scales nonlinearly
API rate limits restrict bulk export throughput
Agent data visibility cannot be restricted by role for GDPR use cases
Knowledge Base translations require separate API calls per locale
Pair-specific challenges
Migration approach
Discovery and data audit
We audit the source Gmelius account across all Shared Inboxes, conversation volume (thread count, message count, date range), label taxonomy, email template library, user list with roles, SLA configurations (Growth and Pro tiers), and Kanban board structure. We extract Google Workspace API scopes and permissions required for Gmail API access and confirm these with the customer's Google Workspace admin. We validate that the destination Gorgias account is provisioned and note the plan tier to confirm which features are available (Basic required for knowledge base, Advanced for custom domains and priority support). The discovery output is a written migration scope document listing all objects to migrate, their record counts, and any pre-migration configuration needed in Gorgias.
Google Workspace API extraction
We connect to the customer's Google Workspace environment using a service account with Gmail API read scope and Google Contacts API read scope. We extract conversation threads in chronological order, preserving message bodies, timestamps, sender addresses, CC/BCC fields, attachment references (not the attachments themselves, which remain in Google Drive or Gmail), label associations, and assignee metadata. Gmail API pagination handles high-volume inboxes with rate-limit handling at 250 requests per second per user. Contacts export via Google Contacts API deduplicates by email address. This step produces a structured JSON export of conversations, contacts, labels, templates, and user data ready for transformation.
Schema mapping and Gorgias pre-configuration
We configure the destination Gorgias account before any data loads. This includes creating Channels matching each Gmelius Shared Inbox with the corresponding email address, defining Tags matching the Gmelius label taxonomy, creating Macros from the Gmelius email template library (with variable placeholder syntax converted to Gorgias format), provisioning Gorgias Agents mapped from Gmelius users with matching roles, and creating any custom Customer fields needed for SLA metadata. We set the default ticket status, priority, and channel values to match Gmelius conventions where possible. Gorgias API credentials are obtained from the customer's account for the migration write step.
Transformation and customer deduplication
We transform the Gmail API export into Gorgias API payload format. Email threads become Tickets with the first message as the ticket body and subsequent messages as events. We resolve sender email addresses to Gorgias Customer records, creating new Customers for unknown addresses and merging duplicates for addresses already in Gorgias. Label associations become Tag assignments on each Ticket. SLA metadata (first response due, resolution due) is written to custom Ticket fields. This step generates a transformation manifest showing source-thread-to-destination-ticket mappings for the customer's reconciliation review.
Gorgias API import with rate-limit handling
We load transformed data into Gorgias via the REST API (developers.gorgias.com) using batch operations with exponential backoff on rate-limit responses (429 status codes). Agents, Customers, and Tickets are loaded in dependency order: Agents first (no dependencies), then Customers (no dependencies), then Tickets (requires Customer references). Tags are assigned after Ticket creation using Ticket update calls. We chunk batches at 100 records per request to stay within Gorgias API limits. Each batch emits a write-count and error-count report; we retry failed records up to three times with backoff before flagging for manual resolution.
Automation and Kanban reconstruction handoff
We deliver the documented handoff package containing the screen recordings of Gmelius Automation Rules (trigger, conditions, actions for each rule), the Kanban board column-to-View mapping, the Gorgias Rule equivalent specification, and the SLA policy configuration written as Gorgias rule definitions. The customer's admin rebuilds these in Gorgias Rules and Views post-migration. We do not execute rule recreation as part of the migration scope. We support a one-week hypercare window for data reconciliation issues discovered after cutover, including mis-mapped customers, missing tags, or tickets assigned to incorrect agents.
Platform deep dives
Gmelius
Source
Strengths
Weaknesses
Gorgias
Destination
Strengths
Weaknesses
Complexity grading
Moderate Helpdesk migration. 3 of 7 objects need a mapping; the rest are 1:1.
Overall complexity
Moderate migration
Derived from compatibility, mapping clarity, API constraints, and data volume across Gmelius and Gorgias.
Object compatibility
3 of 7 objects need a mapping; the rest are 1:1.
Field mapping clarity
Field mapping is derived from defaults — final spec confirmed during the sample migration.
Timeline complexity
7-object category — typical timelines run 2–7 days end-to-end.
API constraints
Gmelius: Not publicly documented.
Data volume sensitivity
Gmelius doesn't expose a bulk API — REST + parallelization used for high-volume runs.
Estimator
Rule-based pricing — no per-record fees, no manual quotes. Migrations over 2M records are scoped individually.
Step 1
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