Helpdesk migration

Migrate from Pega Customer Service to Gorgias

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

Pega Customer Service logo

Pega Customer Service

Source

Gorgias

Destination

Gorgias logo

Compatibility

67%

8 of 12

objects map 1:1 between Pega Customer Service and Gorgias.

Complexity

CModerate

Timeline

4-6 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Moving from Pega Customer Service to Gorgias is a migration from a BPM-powered enterprise case-management platform to an ecommerce-focused helpdesk. Pega organizes around Cases with SLA timers, Workgroup queues, and Microjourney workflow templates stored in a proprietary rule repository; Gorgias organizes around Tickets with a unified inbox, AI Agent automation, and deep Shopify integration. We extract Pega case data through custom export scripts (Pega has no bulk public API), map Cases to Tickets, preserve SLA thresholds as ticket metadata, translate Workgroup structures to Gorgias Teams, and export Knowledge Articles as Gorgias knowledge base content. Rule-based configurations (routing logic, Microjourneys, SLA escalation triggers) do not export as flat data; we deliver a written rule audit documenting every active rule for the customer's admin to rebuild in Gorgias macros and automation rules. We do not migrate workflows, Pega RPA bots, Constellation UIKit components, or reporting dashboards as code.

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

Pega Customer Service logo

Pega Customer Service

What's pushing teams away

  • The licensing and implementation cost is prohibitive for smaller and mid-sized organizations, with ongoing maintenance fees adding significant total cost of ownership over time.
  • The agent interface and overall UI design feel dated compared to modern SaaS platforms, leading to poor user experience and agent frustration in daily use.
  • Organizations find the available customization options too restrictive, forcing them to compromise on desired workflows or interface design for compatibility.
  • Pega lacks a broad developer community and extensive public tutorials, making it difficult for in-house teams to find answers and build expertise without certified Pega resources.
  • Switching away from Pega is costly and complex due to deep customization, proprietary rule-based architecture, and the absence of straightforward data export tooling.

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 Pega Customer Service objects map to Gorgias

Each row shows how a Pega Customer Service 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.

Pega Customer Service

Case

maps to

Gorgias

Ticket

1:1
Fully supported

Pega Cases map to Gorgias Tickets. The Pega case identifier is preserved in a custom field source_case_id__c for audit. Case status (New, Open, Pending, Resolved, Closed) maps to Gorgias Ticket status values that we configure before migration. Case priority maps to a Gorgias priority field or a custom ticket priority field. We handle active SLA timer records by documenting them in the rule audit and flagging them for admin review since Gorgias SLA timers start at ticket creation rather than inheriting historical timers.

Pega Customer Service

Contact

maps to

Gorgias

Customer

1:1
Fully supported

Pega Contact records map to Gorgias Customer. We map name, email, phone, address, and organization associations. Custom Contact properties (picklists, dates, integers) are detected during field discovery and mapped to Gorgias custom fields on the Customer object. Email serves as the dedupe key during import.

Pega Customer Service

Workgroup

maps to

Gorgias

Team

1:1
Fully supported

Pega Workgroups define agent team structures and queue ownership. We preserve Workgroup names, descriptions, and their assignment to routing queues as Gorgias Teams. The Workgroup-to-Agent relationship maps to the Gorgias agent assignment model, where agents are assigned to Inboxes and routing rules determine which team handles which ticket source.

Pega Customer Service

Agent / User

maps to

Gorgias

Agent

1:1
Fully supported

Pega Agent records carry role, skill, and authorization data. We export agent profiles including skill ratings and assignment rules. Skill profiles must be mapped to Gorgias's agent-level settings; Pega's skills-based routing is an add-on tier feature in Gorgias (not available on Starter or Basic plans), so we document the skill configuration and recommend the appropriate Gorgias plan upgrade if skills-based routing is required.

Pega Customer Service

Knowledge Article

maps to

Gorgias

Knowledge Base Article

1:1
Fully supported

Pega Knowledge articles (text, categories, metadata, intent models) export as Gorgias Knowledge Base articles. HTML-formatted article content often requires content cleaning (stripping inline styles, fixing relative links, normalizing image references) before insertion into Gorgias's knowledge base format. We deliver cleaned article content with categories mapped to Gorgias knowledge base sections.

Pega Customer Service

Service Level Agreement

maps to

Gorgias

SLA (First Response Time / Next Reply Time)

lossy
Fully supported

Pega SLA rules attached to Case Types (thresholds, escalation triggers, timer configurations) export as structured metadata. SLA thresholds translate to Gorgias SLA policies configured per inbox or per ticket category. Escalation triggers and branching SLA logic require manual reconstruction in Gorgias SLA rules; we deliver a written SLA mapping document with the Pega SLA configuration documented and the Gorgias SLA equivalent specified.

Pega Customer Service

Case Type Configuration

maps to

Gorgias

Ticket Category + Routing Rule

lossy
Fully supported

Pega Case Types define workflow stages, assignment logic, and routing rules. These are rule-based configurations stored in the Rules Repository, not attribute data. We export stage definitions and routing rule metadata as structured records in the rule audit document. Branching logic and Microjourney configurations must be reconstructed in Gorgias as automation rules and macros; we do not migrate them as executable code.

Pega Customer Service

Attachment

maps to

Gorgias

Attachment

1:1
Fully supported

File attachments linked to Pega cases and knowledge articles export by reference. We download binary files and associate them with the target Gorgias ticket or knowledge base article. Large attachments (over 10 MB) require chunked transfer handling. We verify attachment MIME types during export and preserve original filenames for audit traceability.

Pega Customer Service

Custom Field (Cases and Contacts)

maps to

Gorgias

Custom Field (Ticket and Customer)

1:1
Fully supported

Pega custom fields on Cases and Contacts are detected during field discovery. Each custom property is type-mapped (picklist to dropdown, date to date field, integer to number, text to text) and created in Gorgias before migration begins. We use Gorgias's custom-fields API endpoint with object_type parameter set to Ticket or Customer. Custom field values are transformed during import using the mapping defined in the field discovery output.

Pega Customer Service

Conversation / Interaction History

maps to

Gorgias

Ticket Message (channel = email/chat/social/phone)

1:1
Fully supported

Pega chat, email, and phone interaction transcripts stored in case history export as structured message records. We export transcript text, channel metadata (email, chat, social, phone), and thread ordering. Each transcript maps to a Gorgias Ticket Message with the channel identified. Structured message metadata (sender, recipient, timestamp) preserves the conversation timeline inside the ticket.

Pega Customer Service

Microjourney

maps to

Gorgias

Macros / Automation Rules (reconstruction)

lossy
Fully supported

Pega Microjourneys are multi-step service workflow templates stored in the Rules Repository. They do not export as flat data. We export the Microjourney configuration as structured metadata (step sequence, conditions, actions, branching logic) in the rule audit document. The customer's admin reconstructs Microjourneys as Gorgias Macros (canned responses with conditional logic) and Automation Rules (trigger-action workflows). We provide the documented equivalent for each Microjourney during the handoff.

Pega Customer Service

Pega RPA Bots (attended and unattended)

maps to

Gorgias

Gorgias AI Agent

lossy
Fully supported

Pega RPA (Robotic Process Automation) bots handle attended and unattended automation within Pega. Gorgias AI Agent provides automated ticket resolution (up to 60 percent of tickets per Gorgias customer testimonials) with on-brand responses to order status, returns, and shipping queries. We do not migrate RPA bots to Gorgias. We document the Pega RPA bot list and recommended Gorgias AI Agent equivalent automations in the handoff document.

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.

Pega Customer Service logo

Pega Customer Service gotchas

High

UIKit to Constellation migration is a hard fork

High

Minimum user tier gating on enterprise features

Medium

Cloud migration timelines scale with database volume

Medium

No straightforward public data export API

Medium

Custom rules and Microjourneys do not export as flat data

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

  • Pega has no public bulk data export API

    Pega's API architecture is oriented toward application integration rather than bulk extraction. Exporting cases, contacts, knowledge articles, and attachment binaries requires custom export scripts that interact with Pega's REST or SOAP connectors. We build these scripts as part of the migration engineering phase. This engineering time adds significant cost compared to platforms with straightforward REST or Bulk APIs, and the scripts must be validated against Pega's current connector versions before migration begins.

  • Microjourneys and routing rules do not export as flat data

    Pega's rule-based configuration system stores workflow logic in its Rules Repository rather than as attribute data in case records. When migrating to Gorgias, case data and contact data port cleanly, but branching logic, routing rules, and Microjourney definitions must be manually reconstructed in Gorgias as macros and automation rules. We provide a rule audit export documenting every active rule (trigger, conditions, actions, branching) so the implementation team has a complete blueprint for reimplementation in Gorgias.

  • Active SLA timers cannot transfer as live countdown clocks

    Pega SLA rules attached to Case Types track elapsed time and escalation triggers that are active at the moment of migration. Gorgias SLA timers start from ticket creation rather than inheriting historical elapsed time. Cases with active SLA timers are flagged during migration scoping, and we preserve the SLA metadata (threshold, elapsed time, escalation level) in custom fields so that the customer's Gorgias admin can reapply SLA policies manually or via automation rules after cutover.

  • Pega Constellation UIKit components require reimplementation audit

    Pega is transitioning from UIKit and Theme-Cosmos to the Constellation architecture. Dialog definitions, intent tasks, and intent rules written for UIKit must be rewritten for Constellation compatibility. ConstellaKit (available on Pega Marketplace) assists with Constellation migration but is a Pega-internal migration tool, not a Gorgias export path. We include a UI layer audit during scoping to document which components require reimplementation in Gorgias after data lands.

  • Skills-based routing is gated behind Gorgias plan tier

    Pega's omni-channel routing directs cases to the appropriate agent based on skills, availability, and priority. Gorgias's skills-based routing is an add-on or higher-tier feature not available on Starter or Basic plans. We confirm the customer's required Gorgias plan tier during discovery based on the complexity of agent skill assignments in Pega. If skills-based routing is critical, we recommend the Advanced plan ($750/month for 5,000 tickets) or Enterprise custom pricing.

Migration approach

Six steps for a successful Pega Customer Service to Gorgias data migration

  1. Discovery and export script engineering

    We audit the source Pega system for record counts (Cases, Contacts, Agents, Workgroups, Knowledge Articles), active SLA configurations, Microjourney count, attachment volume, and data volume estimate. We build and validate custom export scripts against Pega's REST or SOAP connectors to extract data in structured form. This phase also includes confirming the Pega instance version, UI framework (UIKit vs Constellation), and whether any Constellation migration tooling (ConstellaKit, Migration Assistant) has already been applied, which affects the data model we export from.

  2. Gorgias plan selection and custom field schema

    We recommend the Gorgias plan tier based on ticket volume, SLA requirements, and skills-based routing needs. We create the destination schema in Gorgias: custom fields on Ticket and Customer objects (using the custom-fields API), Teams (mapped from Pega Workgroups), knowledge base categories (mapped from Pega Knowledge categories), and SLA policies (translated from Pega SLA rules). All schema is validated in a Gorgias sandbox or trial account before production migration begins.

  3. Export, transform, and load into Gorgias sandbox

    We run a full export from Pega using the validated export scripts. The data undergoes transformation: case status to ticket status, contact properties to customer fields, Pega custom fields to Gorgias custom fields, and workgroup names to team names. The transformed dataset loads into a Gorgias sandbox for reconciliation. The customer's admin spot-checks 25-50 records against Pega source data and signs off on mapping before production migration.

  4. Knowledge base and attachment pre-load

    We pre-load the Gorgias knowledge base with cleaned Pega Knowledge articles. HTML content is stripped of inline styles and normalized before insertion. Attachment binaries are downloaded from Pega and staged for association during ticket migration. Large attachments (over 10 MB) are chunked for transfer. Knowledge base category hierarchy is mapped to Gorgias sections, and article URLs are preserved or redirected as needed.

  5. Production migration in dependency order

    We run production migration in dependency order: Customers (first, as ticket recipients), Teams (from Workgroups), Agents (with skill assignments noted for manual tier upgrade if needed), Tickets (with source_case_id__c, SLA metadata, and conversation history), and Knowledge Base articles. SLA metadata is preserved in custom fields; active SLA timers are flagged for manual reapplication. Each phase emits a row-count reconciliation report before the next phase begins.

  6. Cutover, validation, and rule audit handoff

    We freeze Pega writes during cutover, run a final delta migration of records modified during the migration window, then enable Gorgias as the system of record. We deliver the Microjourney rule audit, SLA mapping document, RPA bot inventory, and Constellation UI component audit to the customer's admin team. We support a one-week hypercare window for reconciliation issues. We do not rebuild Pega workflows, routing rules, or RPA bots as Gorgias macros and automation rules inside the migration scope; that is separate work documented for the customer's admin or a Gorgias implementation partner.

Platform deep dives

Context on both ends of the pair

Pega Customer Service logo

Pega Customer Service

Source

Strengths

  • AI-powered next-best-action guidance integrates directly into the agent desktop without requiring external tooling.
  • Low-code App Studio enables business teams to build and modify customer service workflows without deep technical involvement.
  • Omni-channel routing directs cases to the appropriate agent based on skills, availability, and priority across all communication channels.
  • Unified desktop presents the full customer context including prior cases, account details, and external system data without requiring agents to switch screens.
  • Robotic Process Automation capabilities cover both attended automation (agent-triggered) and unattended automation (server-side) within the same platform.

Weaknesses

  • Per-user or per-case pricing model generates high total cost for large contact centers with thousands of daily cases.
  • Agent interface and overall UI design are widely described as outdated and difficult to customize without compromising functionality.
  • Limited public documentation and a small developer community make internal skill-building challenging without Pega-certified resources.
  • Restricted customization options force organizations to adapt processes to the software rather than adapting the software to their needs.
  • Switching away from Pega is costly due to proprietary rule-based architecture, extensive custom configuration, and the absence of simple data export tooling.
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?

Moderate Helpdesk migration. 3 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 Pega Customer Service 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

    Pega Customer Service: Not publicly documented.

  • Data volume sensitivity

    B

    Pega Customer Service doesn't expose a bulk API — REST + parallelization used for high-volume runs.

Estimator

Estimate your Pega Customer Service 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 Pega Customer Service to Gorgias data migrations

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

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Most migrations land between four and six weeks for accounts under 20,000 cases and 5,000 contacts with no active SLA timers and a straightforward knowledge base. Migrations with large case histories (over 50,000 records), active SLA timer preservation, multi-language knowledge bases, or extensive Microjourney documentation move to eight to twelve weeks because of export script engineering time and the SLA translation and knowledge article content cleaning phases.

Adjacent paths

Related migrations to explore

Ready when you are

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