Helpdesk migration

Migrate from Request Tracker to Intercom

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

Request Tracker logo

Request Tracker

Source

Intercom

Destination

Intercom logo

Compatibility

91%

10 of 11

objects map 1:1 between Request Tracker and Intercom.

Complexity

CModerate

Timeline

3-5 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Moving from Request Tracker to Intercom is a migration from a queue-centric, email-driven ticketing system to a messenger-first, conversation-centric support platform. Request Tracker organizes work around persistent Queues with granular staff and requestor permission models, while Intercom uses Teams, Contacts, and Conversations as its core objects. We extract RT data via tab-delimited spreadsheet exports or direct database queries (RT has no bulk REST API), sanitize delimiter collisions, and load into Intercom in the required order: Contacts first, then Conversations, then attachments. RT's Custom Fields, Articles, Time Tracking data, and transaction history all migrate, but RT Scrips and Templates are Perl server artifacts that cannot run in Intercom and do not transfer. We deliver a written inventory of every RT queue configuration and Scrip for the customer's admin to rebuild as Intercom Rules and macros post-migration.

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

Request Tracker logo

Request Tracker

What's pushing teams away

  • RT's web interface is widely described as dated, text-heavy, and visually sparse compared to modern ITSM tools, leading teams with less technical users to migrate toward platforms like Jira Service Management or Freshservice.
  • Self-hosting requires ongoing server maintenance, security patching, and Perl module dependency management that smaller IT teams find operationally burdensome, pushing them toward fully-managed SaaS alternatives.
  • RT lacks native integrations with popular enterprise tools—SolarWinds, Confluence, Slack, and Microsoft Teams require custom scripting or workarounds that teams without dedicated DevOps staff cannot sustain.
  • Teams that need visual Kanban boards, modern mobile apps, and a polished agent experience find RT's feature set insufficient and migrate to platforms purpose-built for those workflows.

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 Request Tracker objects map to Intercom

Each row shows how a Request Tracker 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.

Request Tracker

Ticket

maps to

Intercom

Conversation

1:1
Fully supported

RT Tickets map directly to Intercom Conversations. The RT Subject becomes the conversation title, RT Status (new, open, resolved, rejected, etc.) maps to Intercom's open, closed, and snoozed states, and RT Priority maps to a custom conversation priority attribute. RT's Queue field becomes an Intercom Team assignment; if RT has multiple queues, we create multiple Intercom Teams during provisioning. We preserve RT ticket creation and last-updated timestamps as Created_at and Updated_at on the Intercom conversation. Every RT Transaction (reply, comment, status change) becomes an Intercom Conversation Part in chronological order.

Request Tracker

Queue

maps to

Intercom

Team

1:1
Fully supported

RT Queues define organizational silos and ticket routing. Each RT Queue maps to an Intercom Team. We export Queue names, descriptions, and SLA configurations (if RT-Extension-SLA is present) and create corresponding Teams in Intercom during workspace provisioning. RT's per-queue access control lists (who can reply, who can own tickets) do not have a direct Intercom equivalent; we document the ACL structure in the handoff deliverable for the customer to recreate using Intercom's Team and teammate permission settings. Queue-specific custom fields require additional custom attribute creation per queue in Intercom.

Request Tracker

User (Privileged)

maps to

Intercom

User (Admin/Agent)

1:1
Fully supported

RT Privileged users (staff with login access) map to Intercom Users with admin or agent roles. We extract Name, email, phone, and disabled status from the RT Users table. Matching is by email address. Any RT Privileged user without a matching Intercom User is placed in a reconciliation queue for the customer to provision before record import. Role assignment (superuser, staff, or requestor-only in RT) maps to Intercom's admin vs agent vs teammate access levels.

Request Tracker

User (Unprivileged)

maps to

Intercom

Contact

1:1
Fully supported

RT Unprivileged users (requestors who submit tickets but do not have staff login) map to Intercom Contacts. RT stores Name, email, organization, and phone for each requestor. We export all distinct requestor addresses from the Tickets table, deduplicate by email, and create Intercom Contacts before importing any Conversations. Requestors without an email address require special handling; we flag these as an exception item during scoping.

Request Tracker

Custom Field

maps to

Intercom

Custom Attribute

lossy
Fully supported

RT supports unlimited Custom Fields of types Select-Box, Freeform text, Date, IP Address, and others, scoped globally or to specific queues. We export CF definitions and values and create equivalent custom attributes in Intercom. Global CFs become Intercom custom attributes on the Contact or conversation data object depending on whether the CF applies to users or tickets. Queue-specific CFs require per-queue Team attribute configuration in Intercom. Select-Box CFs with enumerated values map to Intercom dropdown or multiple-choice custom attributes. We document any CF that has no clean Intercom type equivalent as a flag item for scoping review.

Request Tracker

Article

maps to

Intercom

Help Center Article

1:1
Fully supported

RT Articles live in named classes (e.g., General) with Name, Summary, Content, and Custom Fields. We export Articles as structured JSON using RT::Extension::Import::CSV with the --article-class flag and map them to Intercom Help Center Articles. RT Article classes become Intercom Collections, and the Article Name and Summary map to Article title and summary. Content with embedded commas triggers CSV parsing errors; we pre-process with quoting-aware sanitization before import. RT Article custom fields map to Intercom Article attributes.

Request Tracker

Group / Role

maps to

Intercom

Team

1:1
Fully supported

RT Groups organize users for queue-level or ticket-level permission grants (AdminCc, Cc, OwnerDelegated). Group membership does not export in a single flat file—we reconstruct it from the GroupMembers table. Intercom Teams function differently from RT Groups; Intercom Teams define inbox assignment and agent permissions rather than granular ACL grants. We map RT Groups to Intercom Teams where possible, and document the mapping in the handoff deliverable. Any RT Group that does not map cleanly to an Intercom Team is flagged for manual review.

Request Tracker

Transaction

maps to

Intercom

Conversation Part

1:1
Fully supported

Every RT ticket action—reply, comment, status change, field update—creates a Transaction record. We export the full transaction log ordered by Created date and replay it as Intercom Conversation Parts. RT reply actions become Intercom part_type=comment from the contact; RT comment actions become internal notes (part_type=note in Intercom); RT status changes and field updates become conversation metadata updates. Attachment references in Transactions are resolved by querying the Attachments table and re-attaching to the corresponding Conversation Part.

Request Tracker

Attachment

maps to

Intercom

Conversation Attachment

1:1
Fully supported

RT stores file attachments as base64-encoded blobs inside the Attachments database table linked to Transactions by ID. There is no file system path for RT attachments. We run a targeted SQL export per ticket's attachment IDs, decode the base64 blob, reconstruct the original filename and MIME type, and attach the resulting file to the corresponding Intercom Conversation Part. Large attachment blobs (over 10 MB per file) may require chunked extraction and upload due to RT database query timeouts and Intercom's attachment size limits.

Request Tracker

Time Tracking

maps to

Intercom

Conversation Data Attribute

1:1
Mapping required

RT stores Estimated-minutes and Worked-minutes natively on each ticket. If RT-Extension-TimeTracking is installed, it adds structured time-entry records with User, Ticket, Time Worked, and Note. We export both native time values and TimeTracking extension entries and map them to custom numeric attributes on the Intercom conversation (rt_time_estimated_minutes, rt_time_worked_minutes). Intercom does not have a native time-tracking object, so these values appear as conversation metadata rather than a native timesheet feature.

Request Tracker

Template

maps to

Intercom

Macro

1:1
Fully supported

RT Templates define email and notification text used by Scrips. We export Template names and content as text data, preserving token placeholders and conditional logic. Intercom has no direct equivalent to RT's server-side Templates, but Intercom Macros serve a similar notification-and-reply purpose. We deliver Template content mapped to suggested Macro actions as part of the handoff inventory, noting that the customer will need to recreate the templates as Macros manually since Intercom's macro model uses a different action schema. Scrip logic (Perl code) does not migrate and is inventoried separately for the admin's rebuild scope.

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.

Request Tracker logo

Request Tracker gotchas

Medium

Tab-delimited export instead of CSV

Medium

Attachments stored as database blobs

High

RT-to-RT upgrades require original RT directory

High

No native bulk REST API

Low

Comma-heavy article content breaks CSV imports

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

  • RT has no bulk REST API for automated export

    Request Tracker does not publish a bulk or batch REST API endpoint for ticket exports. All programmatic data extraction relies on the tab-delimited spreadsheet export (available at the bottom of any RT search results list), direct database access via SQL query, or community-maintained scripts (rt2redmine, RT::Extension::Import::CSV). For cloud-hosted RT instances where direct database access is unavailable, we use the spreadsheet export workaround in combination with targeted per-record API calls. We advise customers upfront that migration timelines scale linearly with data volume when no bulk API is available, and we include the extraction time estimate in the project scoping document.

  • Intercom requires Contacts created before Conversations

    Intercom's conversation creation API requires an existing Contact record; attempting to create a conversation referencing a non-existent contact returns an error. This creates a hard ordering constraint: we must load all RT Users (both Privileged staff and Unprivileged requestors) into Intercom as Users and Contacts before any Conversation import begins. We handle this by running a Contacts-first migration phase, validating the Intercom contact count against the RT distinct requestor count, and only then proceeding to Conversation import. Any contacts created in Intercom during the delta window after initial migration are reconciled as a final step before cutover.

  • RT tab-delimited export requires pre-processing before CSV use

    RT's built-in spreadsheet export produces tab-delimited text rather than RFC 4180 CSV. Fields containing commas, newlines, or tabs are not always quoted consistently, which breaks naive CSV parsers. Additionally, RT Articles often contain Synopsis and Content fields with embedded commas that cause parsing errors during re-import via RT::Extension::Import::CSV. We pre-process every raw RT export through a sanitizer that detects delimiter collisions, adds quoting where needed, and converts the output to proper CSV before mapping it into our migration pipeline. This step adds processing time proportional to data volume and is included in our timeline estimates.

  • RT queue-to-Intercom Team mapping loses ACL granularity

    RT's queue-level access control lists support granular permission grants per user or group for ticket reply, own, take, and comment actions. Intercom Teams define inbox assignment and agent permissions but do not support the same ACL depth. When we map RT Queues to Intercom Teams, we preserve the team membership and queue assignment, but the fine-grained RT permission model (who can see which queue, who can modify which field) does not transfer. We document the original RT ACL configuration as part of the handoff inventory so the customer's admin can rebuild equivalent access controls using Intercom's Team and teammate permission settings post-migration.

  • RT Scrips and Templates do not migrate to Intercom

    RT Scrips are Perl server-side automation rules triggered by ticket lifecycle events. They are code artifacts tied to a specific RT instance's codebase and cannot run in Intercom's Rules engine. RT Templates are Perl-based email and notification text files that reference RT object properties. Neither Scrips nor Templates have functional equivalents in Intercom; we do not attempt to translate them. We deliver a written inventory of every RT Scrip (with its description, template, and condition code) and every Template (with its name and content) as part of the handoff package. The customer's admin reviews this inventory and rebuilds equivalent automation logic as Intercom Rules and Macros post-migration. Automations do not migrate as code.

Migration approach

Six steps for a successful Request Tracker to Intercom data migration

  1. Discovery and RT export strategy

    We audit the source RT instance across version (4.2 or 5.0), deployment type (self-hosted or cloud), queue count, custom field definitions (global and per-queue), article class structure, time tracking configuration, attachment volume, and transaction history size. We determine the export method: self-hosted RT with direct database access uses SQL queries for maximum fidelity; cloud-hosted RT without DB access uses the tab-delimited spreadsheet export combined with the RT REST API for users and custom field lookups. We produce a written migration scope document with record counts per object, an export method recommendation, and a timeline estimate based on data volume.

  2. RT data extraction and sanitization

    We run data extraction from RT using the agreed method. Tab-delimited exports pass through our sanitizer to convert to proper CSV with consistent quoting for comma-heavy fields. Database exports query the Tickets, Transactions, Attachments, Users, Groups, GroupMembers, Articles, CustomFields, CustomFieldValues, and TimeTracking tables directly. We extract attachment blobs as base64, decode them, and reconstruct filenames and MIME types. RT Templates are exported as text files with their Scrip associations noted. All raw exports are validated against RT record counts before transformation begins.

  3. Intercom workspace provisioning and schema design

    We provision the Intercom workspace, create Teams corresponding to RT Queues, and define custom attributes matching RT Custom Field names and types. We create Collections and Sections corresponding to RT Article classes. Custom attributes are created before any contact or conversation import so that attribute values can map correctly during data load. Intercom's default assignment settings are configured to keep migrated tickets unassigned or assigned to the appropriate team, matching RT's Owner assignment model.

  4. Contacts-first migration

    We load RT Users into Intercom in the required order: Unprivileged users (requestors) as Contacts first, then Privileged users as Users with admin or agent roles. We match by email address and flag any duplicates for manual resolution. RT Group membership is reconstructed from GroupMembers and applied as notes on the corresponding Intercom User record since Intercom Teams use a different permission model. The RT UserCF.Manager field (referenced in community forum discussions on LDAP integration) is preserved as a custom attribute on the Intercom Contact if present.

  5. Conversation migration with transaction threading

    We load RT Tickets as Intercom Conversations in queue order, resolving the Contact reference for each ticket's requestor. Transactions are replayed as Conversation Parts in chronological Created date order: RT comments become internal Intercom notes, RT replies become contact-visible comments, and RT status changes and field updates update conversation metadata. Attachments are re-uploaded to Intercom and linked to the corresponding Conversation Part. SLA timers from RT-Extension-SLA are mapped to Intercom SLA configuration if present. We run reconciliation reports comparing conversation count and transaction count against the RT source after each batch.

  6. Cutover, validation, and Scrip handoff

    We freeze RT ticket creation during cutover, run a final delta migration capturing any records modified during the migration window, and enable Intercom as the system of record. We deliver the Scrip and Template inventory document to the customer's admin team for Intercom Rules and Macro rebuild. We support a one-week hypercare window to resolve reconciliation issues. We do not rebuild RT Scrips as Intercom Rules inside the migration scope; that work is documented and handed off as a separate admin task. Post-cutover, the customer should disable any automated Outbound email campaigns in Intercom during the initial days of production use to avoid API rate-limit pressure from migration tooling.

Platform deep dives

Context on both ends of the pair

Request Tracker logo

Request Tracker

Source

Strengths

  • Fully open source (GPL) with no feature-gating across plans—every capability is available on every tier.
  • Unlimited queues and custom lifecycles let a single instance handle multiple business processes simultaneously.
  • Deep Perl-based customization engine allows complete behavioral modification of ticket lifecycle logic.
  • Integrated email-driven workflow creates tickets from incoming emails and sends notifications from outgoing replies.
  • Long track record with an active community forum and 20+ years of documented migration and upgrade patterns.

Weaknesses

  • No native bulk REST API for automated data extraction—all exports require the tab-delimited spreadsheet workaround, direct database access, or community scripts.
  • Web UI is visually dated with a steep learning curve for non-technical staff compared to modern SaaS helpdesk products.
  • Self-hosted deployments require Linux server administration, Perl module management, and MTA configuration knowledge.
  • Limited native integrations with popular enterprise tools like Slack, Teams, and Confluence without custom development work.
  • Upgrade paths between major RT versions (e.g., 4.2 to 5.0) require careful database migration steps that are non-trivial for understaffed teams.
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?

Moderate Helpdesk migration. 4 of 7 objects need a mapping; the rest are 1:1.

C

Overall complexity

Moderate migration

Derived from compatibility, mapping clarity, API constraints, and data volume across Request Tracker and Intercom.

  • Object compatibility

    C

    4 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

    Request Tracker: Not publicly documented.

  • Data volume sensitivity

    B

    Request Tracker doesn't expose a bulk API — REST + parallelization used for high-volume runs.

Estimator

Estimate your Request Tracker 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 Request Tracker to Intercom data migrations

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

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Most RT to Intercom migrations land between three and five weeks for accounts under 10,000 tickets with one or two queues and straightforward custom fields. Migrations with multiple queues, per-queue custom field configurations, large attachment blobs (over 5 GB combined), long-running transaction histories (over 100,000 transactions), or RT Assets CMDB data move to six to ten weeks. RT's lack of a bulk REST API means extraction timelines scale linearly with data volume; we include extraction time estimates in the project scoping document so the customer can plan accordingly.

Adjacent paths

Related migrations to explore

Ready when you are

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