Helpdesk migration

Migrate from Glassix to Gorgias

Field-level mapping, validation, and rollback between Glassix and Gorgias. We move data and schema; workflows are rebuilt natively in Gorgias.

Glassix logo

Glassix

Source

Gorgias

Destination

Gorgias logo

Compatibility

75%

9 of 12

objects map 1:1 between Glassix and Gorgias.

Complexity

BStandard

Timeline

1-2 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Moving from Glassix to Gorgias means trading an omnichannel communication platform built for messaging-first teams for a helpdesk purpose-built for ecommerce brands with deep Shopify integration. The migration surfaces several structural differences: Glassix organizes interactions as Tickets flowing through Channels (email, chat, WhatsApp, social) into a unified inbox, while Gorgias uses a flat Ticket model with channel metadata attached. Glassix REST API access is tier-gated—Starter workspaces have zero API access and Growth tier has limited endpoints—so scoping must confirm the Glassix tier before any migration plan is designed. We sequence Customer records first (as Gorgias Customers), then Agent mapping (as Gorgias Users), then Ticket migration with full conversation history attached. Custom fields on Glassix Tickets map to Gorgias Ticket and Customer custom fields using the Gorgias custom-fields API. AI chatbot configurations, Workflow automation rules, and Glassix Departments do not migrate as code; we deliver a written inventory for the customer's admin to rebuild in Gorgias Automate or as Teams.

Field-level fidelity

Every standard and custom field arrives verified.

Schema-aware mapping

AI proposes the map; you confirm before any record moves.

Relationships preserved

Parent–child, lookups, and ownership stay linked.

Full activity history

Calls, emails, meetings — with original timestamps.

Attachments & notes

Documents, uploads, and inline notes move with the record.

Why teams make this switch

Two sides of the same decision

Leaving

Glassix logo

Glassix

What's pushing teams away

  • Over-reliance on automated responses and AI processes can lead to impersonal customer experiences that alienate users who prefer human interaction.
  • Support response times frustrate customers when issues arise, with acknowledged slowdowns acknowledged in official responses from Glassix leadership.
  • Limited customization of reporting and analytics compared to enterprise platforms forces data-savvy teams to export data for analysis elsewhere.
  • API access restrictions on Starter and Growth tiers block integration-heavy workflows and prevent customers from building custom automation without upgrading.

Choosing

Gorgias logo

Gorgias

What's pulling them in

  • Shopify-native integrations pull order details, shipment status, and return data directly into the ticket view, eliminating the need for agents to switch between apps.
  • Unlimited user seats mean growing support teams do not trigger billing changes; pricing scales only on billable ticket volume.
  • AI Agent automates responses to high-volume queries like order status and returns, measurably reducing the number of billable tickets each month.
  • Omnichannel inbox consolidates email, live chat, Facebook, Instagram, WhatsApp, SMS, and voice into a single threaded view.
  • SOC 2 Type II certification and GDPR-aligned data handling satisfy enterprise procurement requirements for customer support platforms.

Object mapping

How Glassix objects map to Gorgias

Each row shows how a Glassix 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.

Glassix

Tickets

maps to

Gorgias

Tickets

1:1
Fully supported

Glassix Tickets map directly to Gorgias Tickets. The Glassix ticket status (open, pending, resolved, closed), priority (low, medium, high, urgent), assignee, department, and channel origin migrate as typed fields in Gorgias. We use the Gorgias POST /tickets endpoint with the ticket data structured as {subject, status, priority, channel, assignee_email, tags, custom_fields}. If Glassix tickets carry an external_id reference, we preserve it in a custom field glassix_ticket_id__c for audit traceability.

Glassix

Customers

maps to

Gorgias

Customers

1:1
Fully supported

Glassix Customer profiles (name, email, phone, channel preferences, interaction history) map to Gorgias Customers. We extract the Glassix customer email as the primary key and resolve it against Gorgias existing customers to avoid duplicate creation. Channel opt-in flags migrate to the corresponding Gorgias channel metadata fields. If Glassix Customers reference a company record, we create a matching organization in Gorgias before importing customers to satisfy the organization_id lookup.

Glassix

Agents

maps to

Gorgias

Users

1:1
Fully supported

Glassix Agents (name, email, role, department, availability status) map to Gorgias Users. We match by email as the dedupe key. The Glassix agent role maps to Gorgias permission levels (agent, admin) with a custom field glassix_role__c preserving the original role name. Department mapping is covered separately—Glassix Departments map to Gorgias Teams, and the agent's department membership is recreated via the Gorgias team-user assignment after Users are created.

Glassix

Conversations (Messages)

maps to

Gorgias

Ticket Comments

1:1
Fully supported

Glassix Conversations are threaded message records attached to Tickets. We migrate each Glassix conversation entry as a Gorgias Ticket Comment using the POST /tickets/{id}/messages endpoint. Internal notes (agent-to-agent) are differentiated from customer-facing messages using the public boolean flag. Attachment URLs migrate as Gorgias attachment references. The message chronology is preserved by setting the comment timestamp to the original Glassix created_at value. This is the most data-dense step: a Glassix workspace with 10,000 tickets and an average of 6 message entries each generates approximately 60,000 comment inserts.

Glassix

Channels

maps to

Gorgias

Ticket Channel field

lossy
Mapping required

Glassix Channels (email, chat, WhatsApp, Facebook, Instagram, Apple Messages, voice) map to the Gorgias channel attribute on Tickets. Voice channel tickets from Glassix cannot natively carry call recordings into Gorgias unless the Gorgias Voice add-on is active on the destination; we flag any voice-channel ticket and note the recording attachment path for manual handoff. SMS and WhatsApp tickets migrate with channel metadata intact if the equivalent Gorgias integration is configured.

Glassix

Custom Fields (Tickets)

maps to

Gorgias

Custom Fields (Tickets)

1:1
Mapping required

Glassix custom fields on Tickets (defined via setField) map to Gorgias Ticket custom fields. We query the Glassix workspace for custom field definitions during scoping, then create matching Gorgias custom fields via the POST /custom-fields endpoint with object_type=Ticket before migration begins. Field types are matched: string to string, number to number, boolean to boolean, date to date. Multi-select fields on Glassix become multi-select picklists in Gorgias. The custom field mapping is validated in a pre-migration field audit so no data is dropped during the ticket import phase.

Glassix

Custom Fields (Customers)

maps to

Gorgias

Custom Fields (Customers)

1:1
Fully supported

Glassix customer-level custom fields (used for contact preference tracking, CRM data, or segmentation) map to Gorgias Customer custom fields via POST /custom-fields with object_type=Customer. We identify the customer custom field schema during scoping and pre-create all destination fields so that the customer import phase has no drop-on-insert failures. Customer custom field data types follow the same string/number/boolean/date mapping rules as ticket custom fields.

Glassix

Departments

maps to

Gorgias

Teams

1:1
Fully supported

Glassix Departments group agents and tickets for organizational routing. We map each Glassix Department to a Gorgias Team created via the POST /teams endpoint before agent migration. The department-agent assignment in Glassix becomes a team-user assignment in Gorgias. If Glassix Departments carry routing rules (auto-assign to department on channel trigger), we document those as Automate rules to rebuild in Gorgias since automation rules do not migrate as code.

Glassix

KB Articles

maps to

Gorgias

Knowledge Base Articles

1:1
Mapping required

Glassix Knowledge Base articles (used for chatbot responses and self-service) export as content, categories, and associations. We map article titles, body content, category assignments, and publication status to Gorgias Help Center articles via the Gorgias Help Center API. Article-to-category hierarchy migrates as folder structure in Gorgias. We do not migrate article view counts, SEO metadata, or version history—these are rendered data with no exportable storage in Glassix.

Glassix

AI Chatbots

maps to

Gorgias

Automate Rules

lossy
Mapping required

Glassix AI chatbot configurations (trigger rules, response templates, training data, and automated response rules) are extracted as a structured configuration document. There is no direct API endpoint for chatbot logic export on Growth-tier workspaces. We pull available response templates and routing rules via the Glassix REST API where accessible, and document the full chatbot workflow for the customer's admin to rebuild in Gorgias Automate or as AI Agent training intents. This is a configuration rebuild, not a data migration—the chatbot logic itself does not transfer programmatically.

Glassix

Workflows (Automation Rules)

maps to

Gorgias

Automate Rules

lossy
Mapping required

Glassix Workflows (conditional ticket routing, escalation, and auto-response rules) map to Gorgias Automate rules. We extract the workflow trigger (channel, condition, time-based), the condition logic (field equals, contains, priority thresholds), and the resulting action (assign, tag, status change, auto-reply). Because workflow logic does not migrate as code, we deliver a written inventory of every active Glassix Workflow with its trigger conditions, actions, and a recommended Gorgias Automate equivalent. The customer's admin rebuilds these in Gorgias Automate post-migration.

Glassix

Reports (Analytics)

maps to

Gorgias

Reports

1:1
Not supported

Glassix analytics dashboards (response times, CSAT scores, resolution rates, channel performance metrics) are rendered data stored as UI aggregates rather than raw records. We do not migrate analytics. We deliver a data dictionary documenting the Glassix report schema (metric names, calculation logic, time granularity) so the customer's admin can rebuild equivalent dashboards in Gorgias reporting or a connected BI tool. Historical CSAT scores that exist as individual ticket-level custom fields migrate as part of the ticket custom field mapping described above.

Gotchas + challenges

What specifically takes care here

Platform-specific issues from each side, plus the pair-specific challenges that don't show up on either platform's page on its own.

Glassix logo

Glassix gotchas

High

Starter tier blocks all API access during migration

Medium

Rate limits vary significantly by subscription tier

Medium

AI capabilities are add-on pricing, not core tier inclusion

Gorgias logo

Gorgias gotchas

High

AI Agent adds outcome-based fees on top of billable ticket costs

High

Overage billing for tickets scales nonlinearly

Medium

API rate limits restrict bulk export throughput

Medium

Agent data visibility cannot be restricted by role for GDPR use cases

Low

Knowledge Base translations require separate API calls per locale

Pair-specific challenges

  • Glassix Starter tier has zero API access—migration cannot initiate without a tier upgrade

    Glassix Starter workspaces have no API access whatsoever. No tickets, no customers, no conversations are retrievable programmatically. If your Glassix workspace is on Starter, we cannot initiate migration via the API. We identify the workspace tier during scoping (Settings > Developers > API Keys) and advise upgrading to Growth or Enterprise before migration begins. Growth tier provides limited REST endpoints sufficient for small migrations; Enterprise unlocks unlimited API calls for large-scale exports. The tier upgrade cost is separate from FlitStack AI migration fees.

  • Gorgias per-ticket pricing means volume spikes can exceed Glassix per-user costs post-migration

    Gorgias charges per resolved ticket, not per agent. At low-to-moderate volume (under 300 tickets/month) the Starter or Basic plan is cost-effective, but ecommerce teams routinely cite overage fees during peak seasons (Black Friday, product launches) as a source of bill shock. A Reddit user estimated $500+/month for AI Agent resolutions plus $200+/month for Gorgias voice at their volume. We calculate the customer's average monthly ticket volume during scoping and model the Gorgias cost at that volume against their current Glassix cost to flag whether the pricing model change is favorable or a hidden cost increase.

  • Glassix AI chatbot configurations are not fully API-exportable on Growth tier

    On the Growth tier, AI chatbot capabilities are listed as an add-on and some chatbot configurations may not be accessible via standard REST API endpoints on all Growth workspaces. We extract chatbot response templates and routing rules where the API surfaces them, but trigger conditions, training data, and AI decision trees require a manual configuration audit. We deliver a written chatbot inventory documenting the available configuration data and flag anything that requires the Enterprise tier or AI add-on to confirm scope before migration begins.

  • Voice channel ticket attachments (call recordings) require Gorgias Voice add-on to receive native data

    Glassix includes built-in voice infrastructure as a core feature. Call recordings attached to voice-channel tickets in Glassix have no native equivalent in Gorgias unless the Voice add-on is active on the destination workspace. We flag all voice-channel tickets during scoping, extract any recording attachment URLs from Glassix, and store them in a custom field glassix_voice_recording_url__c on the migrated Gorgias ticket. If the customer wants live call handling inside Gorgias, they activate the Voice add-on separately post-migration.

Migration approach

Six steps for a successful Glassix to Gorgias data migration

  1. Tier confirmation and API access audit

    We confirm the Glassix workspace tier (Starter, Growth, or Enterprise) via Settings > Developers > API Keys. If the workspace is on Starter, we flag that API access is unavailable and advise a Growth or Enterprise upgrade before migration scoping begins. On Growth tier we test the available endpoints (tickets, customers, agents, conversations) against the actual workspace data to measure API capacity and pagination behavior. We also confirm whether the AI chatbot add-on is active, which affects chatbot configuration extraction scope.

  2. Source data inventory and custom field schema audit

    We enumerate all Glassix objects available via API: ticket count, customer count, agent count, conversation message density, custom field definitions on tickets and customers, department count, KB article count, and active workflow count. For each custom field we record the field name, data type, and whether it is a required or optional field in Glassix. This inventory determines the pre-migration custom field creation phase in Gorgias (POST /custom-fields for both Ticket and Customer object types) and informs the overall migration timeline estimate.

  3. Destination schema creation in Gorgias

    Before any data moves, we create the target schema in Gorgias. This includes pre-creating all Ticket and Customer custom fields (with correct data types matching Glassix), creating Teams (mapped from Glassix Departments), provisioning Users (matched by email from Glassix Agents), and configuring the Knowledge Base structure (mapped from Glassix KB categories). Channel integrations (WhatsApp, Facebook, Instagram, email) are enabled in Gorgias Settings > Channels to ensure the channel metadata on migrated tickets is valid. We run this schema creation against a Gorgias Sandbox if the customer has an Enterprise plan; otherwise against the production workspace with a rollback plan.

  4. Sample migration and reconciliation

    We run a sample migration of the most recent 100-200 Glassix tickets (including conversation history, customer records, and custom field data) into Gorgias. The customer's team spot-checks 20-30 records against the Glassix source to validate ticket subject accuracy, conversation chronology, custom field values, and agent assignment. Any mapping corrections (field name mismatches, type errors, lookup resolution failures) are resolved in the sample phase before the full migration begins. This step is the last opportunity to adjust the field mapping without impacting production data.

  5. Full production migration in dependency order

    We execute production migration in record-dependency order: Teams (departments) first, then Users (agents), then Customers (with organization resolution), then Tickets with full conversation history attached as Comments, then KB articles. Custom field values are inserted inline during each record phase. We monitor Glassix API rate limit responses (429 Too Many Requests) and implement exponential backoff tuned to the detected tier. The Gorgias Bulk API is used for high-volume ticket inserts where batch endpoints are available. Each phase emits a row-count reconciliation report before the next phase begins.

  6. Cutover, delta sync, and automation rebuild handoff

    We freeze Glassix writes during the cutover window, run a final delta migration capturing any records created or modified during the migration, then enable Gorgias as the system of record. We deliver the Workflow and AI chatbot configuration inventory document to the customer's admin team with recommended Gorgias Automate and AI Agent equivalents for each Glassix workflow. We do not rebuild Glassix Workflows or chatbot configurations as Gorgias Automate rules inside the migration scope; that is a separate configuration engagement. A 72-hour hypercare window covers reconciliation of any record-level data issues surfaced post-cutover.

Platform deep dives

Context on both ends of the pair

Glassix logo

Glassix

Source

Strengths

  • Native voice infrastructure built in-house rather than third-party telephony APIs, cutting latency and cost.
  • Multi-channel consolidation across messaging, email, social, and voice in a single unified inbox.
  • AI chatbot with 24/7 automated resolution across WhatsApp, Apple Messages, and social platforms.
  • Real-time reporting dashboards tracking first response time, resolution rates, and customer satisfaction.
  • Per-channel performance visibility gives teams data they previously lacked on chatbot and agent effectiveness.

Weaknesses

  • Starter tier has no API access whatsoever, blocking any programmatic data export or integration.
  • Growth tier REST API access is limited, not sufficient for large-scale migration without tier upgrade.
  • AI features are add-ons on Growth tier rather than included, increasing total cost for AI-dependent workflows.
  • Support response times lag according to customer reviews, creating friction when migration issues arise.
Gorgias logo

Gorgias

Destination

Strengths

  • Shopify and BigCommerce integrations surface order, return, and shipment data natively inside every ticket.
  • Unlimited agent seats remove per-user licensing friction as support teams grow.
  • AI Agent reduces billable ticket volume through automated resolution of high-frequency queries.
  • SOC 2 Type II certified with GDPR-aligned data handling for enterprise procurement readiness.
  • Omnichannel inbox aggregates email, live chat, Facebook, Instagram, WhatsApp, SMS, and voice into a single threaded view.

Weaknesses

  • Ticket-volume pricing with overage fees creates unpredictable monthly costs during seasonal traffic spikes.
  • Custom reporting is shallow; raw event-level data export for BI tooling is not natively supported.
  • Knowledge Base, Macros, and Rules lack simple export tooling, making competitive migrations complex.
  • GDPR compliance limitations mean customer data cannot be hidden from agents by role, blocking use by teams with freelance staff.
  • Performance and glitch reports emerge in G2 reviews at higher ticket volumes.

Complexity grading

How hard is this migration?

Standard Helpdesk migration. 3 of 7 objects need a mapping; the rest are 1:1.

B

Overall complexity

Standard migration

Derived from compatibility, mapping clarity, API constraints, and data volume across Glassix and Gorgias.

  • Object compatibility

    C

    3 of 7 objects need a mapping; the rest are 1:1.

  • Field mapping clarity

    C

    Field mapping is derived from defaults — final spec confirmed during the sample migration.

  • Timeline complexity

    B

    7-object category — typical timelines run 2–7 days end-to-end.

  • API constraints

    B

    Glassix: Max 30 token requests/min across all tiers; per-endpoint per-minute and per-hour limits vary by tier — returns 429 Too Many Requests when exceeded.

  • Data volume sensitivity

    A

    Glassix exposes a bulk API — large-volume migrations stream efficiently.

Estimator

Estimate your Glassix to Gorgias migration cost

Rule-based pricing — no per-record fees, no manual quotes. Migrations over 2M records are scoped individually.

Step 1

What are you migrating?

Pick a category, then your source and destination platforms.

Category

FAQ

Frequently asked questions about Glassix to Gorgias data migrations

Answers to the questions buyers ask most during Glassix to Gorgias migration scoping. Not seeing yours? Book a call.

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Most migrations complete in one to two weeks for workspaces under 10,000 tickets and 5,000 customers with no tier-upgrade dependency. Glassix Starter-tier workspaces require a Growth or Enterprise upgrade before API access is available, which adds one to two weeks to the timeline. Migrations with high conversation density per ticket (over 10 messages per ticket on average), extensive custom field schemas, KB article content, or AI chatbot configuration documentation extend to three to four weeks.

Adjacent paths

Related migrations to explore

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