Helpdesk migration

Migrate from Glassix to Intercom

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

Glassix logo

Glassix

Source

Intercom

Destination

Intercom logo

Compatibility

73%

8 of 11

objects map 1:1 between Glassix and Intercom.

Complexity

BStandard

Timeline

2-4 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Moving from Glassix to Intercom is a migration from a unified inbox with built-in voice to a conversation-first support platform with stronger API depth at lower tiers. Glassix Starter blocks all API access, forcing customers to upgrade before any programmatic migration can begin; Growth tier provides limited REST access that constrains large conversation histories. Intercom enforces a strict import order: contacts must exist before conversations can be linked, and custom attributes must be defined before their values are written. We resolve the Glassix-to-Intercom object model differences—the ticket-versus-conversation paradigm, department-to-team routing, and channel attribution—during scoping, then execute the migration in Intercom's required dependency order. We do not migrate AI chatbot configurations or workflow automation rules; we deliver a written inventory of every Glassix chatbot trigger and workflow condition for your admin to rebuild in Intercom Fin AI and Operators.

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

Intercom logo

Intercom

What's pulling them in

  • Instant chat and message threading on websites and apps gives support teams a single inbox without context-switching, according to reviewers on Capterra and G2 who highlight fast response times as a primary benefit.
  • Fin AI handles repetitive inbound queries automatically, reducing agent workload measurably — G2 reviewers report fewer escalations and faster first-response times once Fin is configured.
  • Automation workflows (Outbound, Operator, and custom bots) allow teams to qualify leads and route tickets without manual intervention, appealing to growth-stage SaaS companies managing high ticket volumes.
  • Help center articles and self-service deflection are natively integrated, so knowledge base content and chat conversations live in the same workspace, simplifying reporting.
  • Multi-channel support (live chat, email, SMS, WhatsApp, Phone) consolidates customer touchpoints into one inbox, reducing the operational overhead of managing separate tools.

Object mapping

How Glassix objects map to Intercom

Each row shows how a Glassix object lands in Intercom, 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

Intercom

Tickets

1:1
Mapping required

Glassix Tickets map to Intercom Tickets, preserving status, priority, assignee, department, and channel origin. The Glassix channel property (email, chat, WhatsApp, Facebook, Instagram, Apple Messages) maps to the Intercom conversation source field. Ticket custom fields migrate to Intercom custom attributes on Tickets, which must be created in Intercom Settings > Data > Tickets > Attributes before migration begins. Closed tickets preserve their original Created_at and Updated_at timestamps per Intercom migration documentation.

Glassix

Customers

maps to

Intercom

Contacts (Users and Leads)

1:1
Fully supported

Glassix Customer profiles map to Intercom Contacts. Each Contact requires an email or user_id per Intercom's import requirements—contacts without either are held in a reconciliation queue. The Glassix channel opt-in flags migrate to HasOptedOutOfEmail and a custom attribute glassix_channel_preference__c. Phone number validation should be disabled in Intercom Settings > Your Workspace > People Data > Phone before migration to avoid rejecting invalid formats present in Glassix data.

Glassix

Agents

maps to

Intercom

Admins

1:1
Fully supported

Glassix Agent records (name, email, role, department, availability status) map to Intercom Admins. We resolve by email match against the Intercom workspace admin list. Agents without a matching Intercom admin are held for the customer's admin to provision before record import resumes. Department assignments on Glassix agents map to Intercom Teams, which scope inbox access and ticket assignment permissions.

Glassix

Conversations

maps to

Intercom

Conversations

1:1
Mapping required

Glassix Conversation records (threaded messages attached to Tickets and Customers) map to Intercom Conversations. Intercom requires that the parent Contact exist before a Conversation can be created and linked. We implement a two-pass approach: first pass creates all Contacts, second pass creates Conversations with Contact ID resolved via email lookup. Internal notes on Glassix Conversations map to Intercom internal notes on the Conversation.

Glassix

Departments

maps to

Intercom

Teams

1:1
Fully supported

Glassix Departments group agents and tickets for organizational routing. These map to Intercom Teams, which define inbox scope, assignment rules, and admin permissions. We create equivalent team structures in Intercom before agent reassignment, then remap Glassix agent-department relationships to Intercom team membership. If Glassix uses nested departments, we flatten to a single team level per Intercom's team model.

Glassix

Channels

maps to

Intercom

Channels

1:1
Mapping required

Glassix Channels define communication mediums (email, chat, WhatsApp, Facebook, Instagram, Apple Messages). Channel type maps to Intercom's conversation source field on each Conversation record. WhatsApp on Intercom requires an additional WhatsApp add-on configuration not present in all plans—we flag any Glassix WhatsApp tickets that require this add-on to be enabled in the destination Intercom workspace.

Glassix

Custom Fields (Tickets)

maps to

Intercom

Custom Attributes (Tickets)

lossy
Mapping required

Glassix custom fields on Tickets via setField migrate to Intercom Ticket custom attributes. Custom attributes must be created in Intercom Settings before importing ticket data—values cannot be written to undefined attributes. We identify all Glassix custom field schemas during scoping, define equivalent Intercom attributes (with correct type: string, number, date, boolean, or list), then execute ticket import in the second phase after attribute creation. This ordering is mandatory per Intercom's API requirements.

Glassix

AI Chatbots

maps to

Intercom

Fin AI Agent / Operators

lossy
Mapping required

Glassix chatbot configurations (trigger rules, response templates, training data) do not migrate as executable code. We extract the chatbot logic schema, trigger conditions, and response content and deliver it as a written inventory. The customer's admin uses this to configure Intercom Fin AI Agent (FAQ-based resolution) or Operators (custom workflow builder). AI training data and conversation summaries from Glassix are documented for retraining in Intercom's Fin AI interface. This is not a code migration; it is a configuration handoff.

Glassix

Workflows (Automation Rules)

maps to

Intercom

Workflows (Intercom Operators / Rules)

lossy
Mapping required

Glassix Workflows automate ticket routing, escalation, and responses based on conditions. These do not migrate as executable automation. We deliver a written inventory of every active Glassix Workflow with its trigger, conditions, actions, and a recommended Intercom Operators or Rules equivalent. The customer's admin rebuilds workflow logic in Intercom's automation builder post-migration. Workflows that depend on Glassix-specific AI training data are flagged separately because the trigger conditions may need redesign for Intercom's Fin AI context.

Glassix

KB Articles

maps to

Intercom

Articles

1:1
Mapping required

Glassix Knowledge Base articles power chatbot responses and self-service. We export article content, categories, and article-to-category associations, then import them into Intercom Help Center as Articles within Collections. Article body content migrates as HTML or markdown per the destination format. Article publish status, author, and created/modified timestamps are preserved. Links between articles are documented for the customer to update post-import if internal linking structure differs.

Glassix

Reports (Analytics)

maps to

Intercom

Reports (Documentation)

1:1
Not supported

Glassix analytics dashboards (response times, CSAT, resolution rates, channel performance) are rendered data, not raw records accessible via API. We do not migrate historical analytics. We document the Glassix report schema and metric definitions so the customer's admin can rebuild equivalent reports in Intercom's reporting interface using migrated conversation and ticket data. CSAT scores embedded in individual ticket records migrate as custom attributes.

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

Intercom logo

Intercom gotchas

High

S3 JSON export omits conversation transcripts

High

Workspace isolation prevents workflow migration

Medium

Fin AI resolution fees compound with automation success

Medium

Two-year conversation history limit on historical export

Low

Private app rate limits share workspace quota

Pair-specific challenges

  • Glassix Starter tier blocks all API access during migration

    Glassix Starter workspaces have zero API access—no tickets, contacts, conversations, or agents are retrievable programmatically. If your Glassix workspace is on Starter, we cannot initiate migration via 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 API access sufficient for small migrations; Enterprise unlocks higher rate limits needed for large conversation histories. This is a pair-specific gotcha because the Starter-tier lockout directly prevents the Glassix-to-Intercom migration from starting.

  • Intercom requires contacts created before conversations

    Intercom's API enforces a parent-record dependency: every Conversation must be linked to an existing Contact via email or user_id. Attempting to create conversations before their associated contacts exist results in errors and silent failures. We implement a mandatory two-phase import: Phase 1 extracts and creates all Glassix Customer records as Intercom Contacts, Phase 2 extracts and creates all Glassix Conversation records with Contact ID resolved via email lookup. Skipping this ordering results in incomplete conversation migration.

  • Custom attributes must exist before ticket data import

    Intercom requires that custom attributes be defined in Settings > Data before their values can be written via API. Glassix custom fields on Tickets (setField API) have no equivalent if the corresponding Intercom attribute does not exist. We identify all Glassix custom field schemas during scoping, create equivalent Intercom Ticket attributes (with correct type: string, number, date, boolean, or list), then execute ticket import in a subsequent phase. This sequence is mandatory and must be validated in a Sandbox run before production migration.

  • Glassix Growth API rate limits constrain large migrations

    Glassix Growth tier enforces per-minute rate limits on REST API calls that differ from Enterprise unlimited access. Large conversation histories (tens of thousands of messages) require pagination over multiple sessions to avoid 429 Too Many Requests responses. We implement exponential backoff logic tuned to the detected tier and chunk conversation batches into manageable pages. If migration speed is unacceptable on Growth limits, we advise upgrading to Enterprise for the duration of the migration and downgrading afterward.

  • Intercom campaigns and automations consume API budget during migration

    Intercom operates under API rate limits that are shared across all requests including active Outbound campaigns and automated workflows. Migrating data while campaigns are running can throttle the migration and slow both processes. We advise disabling active automated email campaigns in Intercom (Outbound > Campaigns) before migration begins and keeping them disabled until the migration completes. This is documented in Intercom's own migration guides and applies to any high-volume import scenario.

Migration approach

Six steps for a successful Glassix to Intercom data migration

  1. Discovery and tier verification

    We audit the source Glassix workspace across tier (Starter/Growth/Enterprise), API key presence, record volumes (tickets, customers, agents, conversations, KB articles), custom field schemas, active chatbot configurations, and active workflows. This phase identifies the Glassix tier and flags the Starter-tier API lockout as a prerequisite blocker. We also audit the destination Intercom workspace for existing contacts, teams, and custom attributes that may conflict with the migration schema. The discovery output is a written migration scope with a tier-upgrade recommendation if applicable.

  2. Intercom schema pre-creation

    We create all required Intercom custom attributes (on Contacts, Companies, and Tickets), Teams (mirroring Glassix Departments), and ticket attributes before any data import begins. This follows Intercom's mandatory attribute-pre-creation requirement. We also disable phone number validation in Intercom Settings > Your Workspace > People Data > Phone to prevent rejecting Glassix contacts with invalid phone formats, and configure default assignment settings for unassigned tickets in Settings > Inbox Settings > Assignment Preferences.

  3. Contact pre-migration and reconciliation

    We extract all Glassix Customer records and import them into Intercom as Contacts. Each Contact requires an email or user_id; records without either are held in a reconciliation queue for the customer's admin to resolve (add email, merge with existing record, or suppress). We preserve Glassix channel opt-in flags, any custom field values on Customer records, and the original Glassix customer_id in a custom attribute glassix_original_id__c for audit trail. This phase must complete before any Conversation import begins.

  4. Agent-to-Admin mapping and team structure

    We extract Glassix Agent records and map them to Intercom Admins by email match. Agents without a matching Intercom admin are queued for admin provisioning. Glassix Departments map to Intercom Teams, which are created in this phase. Agent-department assignments translate to Intercom team membership. Once all teams and admins are provisioned and mapped, we proceed to ticket and conversation migration.

  5. Ticket and conversation migration in dependency order

    We migrate Glassix Tickets as Intercom Tickets, with the Glassix channel property mapped to Intercom's conversation source field. Tickets are imported after Contact pre-creation but before Conversation migration, establishing the parent-record relationships. Glassix Conversations are then imported as Intercom Conversations, with Contact ID resolved via email lookup from Phase 3. Internal notes on Glassix conversations map to Intercom internal notes. Timestamps (Created_at, Updated_at) are preserved per Intercom migration documentation. We implement rate-limit backoff and batch chunking tuned to the Glassix workspace tier.

  6. KB article migration and Fin AI configuration handoff

    We export Glassix KB articles (content, categories, associations) and import them into Intercom Help Center as Articles within Collections. Article metadata (author, publish status, timestamps) is preserved. We do not migrate chatbot configurations or workflow automation rules as code. We deliver a written inventory of every active Glassix chatbot trigger, response template, and workflow condition with recommended Intercom Fin AI Agent and Operators equivalents. The customer's admin rebuilds these in Intercom post-migration. Reports schema documentation is also delivered so the admin can rebuild Glassix analytics in Intercom reporting.

  7. Cutover, validation, and migration sign-off

    We freeze Glassix writes during cutover, run a final delta migration of any records modified during the migration window, then enable Intercom as the system of record. We deliver a row-count reconciliation report (Contacts in, Tickets in, Conversations in, Articles in) and a spot-check sample of 25-50 records against the Glassix source. We support a one-week hypercare window for reconciliation issues. Workflow and chatbot rebuild handoff documentation is delivered at this point. We do not rebuild Glassix workflows as Intercom Operators or configure Fin AI inside the migration scope; those are separate engagements.

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.
Intercom logo

Intercom

Destination

Strengths

  • Integrated AI agent (Fin) for automated resolution with per-resolution billing that rewards high automation rates.
  • Multi-channel inbox consolidating live chat, email, SMS, WhatsApp, and Phone into a single threaded view.
  • Native help center with articles, collections, and self-service deflection capabilities.
  • Workflow automation for routing, qualification, and proactive outbound messaging across channels.
  • Strong API ecosystem with 10,000 req/min rate limits for private apps enabling high-throughput migration pipelines.

Weaknesses

  • Pricing model compounds with seat count, AI resolution fees, channel costs, and multiple add-ons, making total cost hard to predict.
  • Workspace-level isolation prevents moving workflows or content between environments, requiring manual rebuilds.
  • S3 JSON export deliberately excludes conversation transcripts, necessitating REST API calls for full message history.
  • Outages are reported as frequent enough to be a concern for always-on support operations.
  • Setup complexity means teams often require internal guidance or professional services to configure bots and automation correctly.

Complexity grading

How hard is this migration?

Standard Helpdesk migration. 2 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 Intercom.

  • Object compatibility

    B

    2 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 Intercom 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 Intercom data migrations

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

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Migrations under 10,000 tickets, 5,000 contacts, and no KB article sets land between two and four weeks. Migrations with large conversation histories (over 100,000 message records), KB article sets, custom ticket fields, or multi-department team structures move to five to eight weeks because of Intercom's mandatory contact-first import sequencing and custom attribute pre-creation. Glassix Starter workspaces require a tier upgrade before migration can begin, which adds one to two weeks to the overall timeline.

Adjacent paths

Related migrations to explore

Ready when you are

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