Helpdesk migration
Field-level mapping, validation, and rollback between Mava and Gorgias. We move data and schema; workflows are rebuilt natively in Gorgias.
Mava
Source
Gorgias
Destination
Compatibility
6 of 12
objects map 1:1 between Mava and Gorgias.
Complexity
CModerate
Timeline
2-4 weeks
Overview
Switching from Mava to Gorgias is a platform-level shift from a community-native support tool built for web3, gaming, and SaaS companies managing Discord and Telegram channels, to a full-featured eCommerce helpdesk with deep Shopify integration, a per-ticket pricing model, and a structured REST API. The migration centers on resolving Mava's Discord and Telegram user identifiers to Gorgias's email-based Customer object, mapping per-channel AI bot intents to Gorgias Macros and Rules, and preserving tag and SLA metadata as custom fields since Gorgias does not natively support Mava's full SLA configuration model. We do not migrate Mava's AI bot configurations or webhook payloads as executable code; we deliver a written inventory of both for the customer's admin to rebuild in Gorgias's Rules engine. Import into Gorgias proceeds at approximately 720 tickets per hour, making migration duration a function of conversation volume rather than platform complexity.
Every standard and custom field arrives verified.
AI proposes the map; you confirm before any record moves.
Parent–child, lookups, and ownership stay linked.
Calls, emails, meetings — with original timestamps.
Documents, uploads, and inline notes move with the record.
Why teams make this switch
Leaving
What's pushing teams away
Choosing
What's pulling them in
Object mapping
Each row shows how a Mava 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.
Mava
Conversations
Gorgias
Ticket
1:1Mava Conversations map directly to Gorgias Tickets. The conversation ID becomes the ticket's external_id field for reconciliation. Channel source (Discord, Telegram, web) maps to Gorgias's channel field, and message history migrates as ticket comments. Mava's conversation status (open, pending, resolved, closed) maps to Gorgias Ticket status with the caveat that Gorgias does not auto-sync status changes post-import; any Mava status updates after import require manual updates in Gorgias.
Mava
Users/Members
Gorgias
Customer
1:1Mava community members linked to verified email addresses map to Gorgias Customer by email. Mava members identified only by Discord user ID or Telegram user ID require enrichment before migration: we flag these records during scoping, and the customer can either enrich them with email addresses pre-migration or accept that they will create Gorgias Customer records without email (stored as a note or external_id). The external_id field on Gorgias Customer preserves the original platform identifier (discord:123456789 or telegram:987654321) for reconciliation.
Mava
Agents
Gorgias
Agent
1:1Mava Agent records (name, email, role) map directly to Gorgias Agent. Agent email is used as the dedupe and matching key. If a Mava Agent email does not have a corresponding Gorgias Agent account, we create a placeholder during migration and assign tickets to it with a flag; the customer's admin provisions the live Agent account and remaps tickets post-migration.
Mava
Teams
Gorgias
Group
1:1Mava team structures (name, member list, assignment rules) map to Gorgias Groups. Team-based routing in Mava becomes Group assignment in Gorgias. If Mava teams have channel-specific routing logic (a team handling only Discord tickets, for example), we document that as a Gorgias Rule condition rather than migrating it as automated logic.
Mava
Tags
Gorgias
Tag
1:1Mava conversation tags map directly to Gorgias Ticket Tags. Tags are simple key-value strings in both platforms with no transformation required. We preserve tag count and usage statistics in the migration manifest for the customer to reference when rebuilding reporting in Gorgias.
Mava
AI Bots (intent catalog)
Gorgias
Macro
lossyMava's per-channel AI bot intents and automated responses do not migrate as executable automation. We extract the full intent catalog across all channels (Discord, Telegram, web) and map each intent's trigger phrase and response text to a Gorgias Macro. The customer reviews the intent catalog during scoping and rebuilds the routing logic in Gorgias Rules. Channel-specific conditions that apply only to Discord or Telegram do not have a direct Gorgias equivalent since Gorgias does not natively route by Discord role or Telegram group.
Mava
Custom Webhooks
Gorgias
HTTP Integration
1:1Mava's webhook configurations (endpoint URLs, trigger conditions) are extracted and documented in the migration manifest. Webhook payloads are custom per customer and do not follow a standardized Mava schema, so payload transformation requires manual mapping in Gorgias. We provide the endpoint URLs and trigger logic, but the customer or a developer configures the Gorgias HTTP Integration and maps the payload fields.
Mava
SLA Policies
Gorgias
SLA Policy
lossyMava's first-response and resolution time SLA rules are channel or team-scoped. Gorgias SLA policies are scoped to ticket priority and channel. We extract the Mava SLA configuration (targets in minutes, applicable channels, escalation rules) and map it to Gorgias SLA policies with the understanding that team-based SLA scoping in Mava becomes priority-based scoping in Gorgias. Any Mava SLA rules that cannot map to Gorgias's model are flagged in the manifest for manual configuration.
Mava
Tags
Gorgias
Custom Field (Ticket)
lossyIf Mava conversation tags carry structured metadata (for example, tag values that indicate ticket category, severity, or source system), we map these to Gorgias Ticket custom fields of the appropriate type (text, boolean, or number). The customer defines the custom field schema during scoping, and we create the fields in Gorgias via the API before migration begins.
Mava
Channel Source Metadata
Gorgias
Custom Field (Ticket)
lossyMava's channel source (Discord, Telegram, web) is preserved as a text custom field on the Gorgias Ticket. This is useful for teams that want to preserve reporting on channel distribution post-migration, since Gorgias's native channel field does not include Discord or Telegram as native options.
Mava
SLA Metadata
Gorgias
Custom Field (Ticket)
lossyMava SLA metadata that does not map to Gorgias native SLA policies (for example, SLA breach timestamps, escalation level, or SLA tier name) is preserved as custom fields on the Gorgias Ticket. This preserves historical SLA data for reporting even if the active SLA enforcement is rebuilt from scratch in Gorgias.
Mava
Customer Type
Gorgias
Custom Field (Customer)
lossyIf Mava tracks community member type (for example, admin, moderator, verified user, or general member), we map this to a Gorgias Customer custom field. This is particularly relevant for web3 and gaming companies where community role affects support priority or SLA tier. The customer defines the picklist values during scoping.
| Mava | Gorgias | Compatibility | |
|---|---|---|---|
| Conversations | Ticket1:1 | Fully supported | |
| Users/Members | Customer1:1 | Mapping required | |
| Agents | Agent1:1 | Fully supported | |
| Teams | Group1:1 | Fully supported | |
| Tags | Tag1:1 | Fully supported | |
| AI Bots (intent catalog) | Macrolossy | Fully supported | |
| Custom Webhooks | HTTP Integration1:1 | Mapping required | |
| SLA Policies | SLA Policylossy | Mapping required | |
| Tags | Custom Field (Ticket)lossy | Fully supported | |
| Channel Source Metadata | Custom Field (Ticket)lossy | Fully supported | |
| SLA Metadata | Custom Field (Ticket)lossy | Fully supported | |
| Customer Type | Custom Field (Customer)lossy | Fully supported |
Gotchas + challenges
Platform-specific issues from each side, plus the pair-specific challenges that don't show up on either platform's page on its own.
Mava gotchas
Community identity linkage may be incomplete
Bot configurations are channel-specific
Webhook payloads lack standardized schema
Gorgias gotchas
AI Agent adds outcome-based fees on top of billable ticket costs
Overage billing for tickets scales nonlinearly
API rate limits restrict bulk export throughput
Agent data visibility cannot be restricted by role for GDPR use cases
Knowledge Base translations require separate API calls per locale
Pair-specific challenges
Migration approach
Discovery and scoping
We audit the source Mava instance for conversation volume, channel distribution (Discord, Telegram, web), agent count, team structure, tag taxonomy, SLA configurations, and webhook endpoints. We identify community identity records that lack email addresses and flag them for enrichment. We review the Mava AI bot intent catalog across all channels and document the routing logic for the Macro inventory. The discovery output is a written migration scope covering object counts, identity resolution requirements, custom field definitions, and a timeline estimate.
Identity enrichment and resolution
Before migration begins, we work with the customer to enrich Mava community records that lack email addresses. Options include exporting the Discord member list with email visibility, pulling Telegram contact exports, or asking customers to submit updated contact information. Records that cannot be enriched are mapped to anonymous Gorgias Customer records with the original platform identifier preserved in external_id. This step is critical for SLA reporting and ticket attribution post-migration.
Schema preparation in Gorgias
We create the required custom fields in Gorgias for any Mava metadata that does not map to native Gorgias fields (channel source, SLA metadata, community role). We configure Gorgias Groups to match the Mava team structure. We define the tag taxonomy in Gorgias based on the Mava tag export. All schema changes are made via the Gorgias API in a staging context before production migration begins.
Agent and Group provisioning
We extract all Mava Agent records and map them to Gorgias Agents by email match. If a Mava Agent email does not correspond to a Gorgias Agent account, we create a placeholder with a migration flag. The customer's admin provisions any missing Agent accounts before production migration. Team assignments from Mava are mapped to Gorgias Groups and verified before ticket migration begins.
Conversation migration with delta reconciliation
We migrate Mava Conversations to Gorgias Tickets in dependency order: Customers first (with identity resolution), then Agents, then Groups, then Tickets with message history and tags. The import runs in batches to stay within Gorgias API rate limits. After the initial import, we run a delta migration to capture any Mava records created or modified during the migration window. Each batch emits a row-count reconciliation report before the next batch begins.
Cutover and automation inventory handoff
We freeze Mava writes during cutover, run a final delta migration, then enable Gorgias as the system of record. We deliver the AI bot intent catalog (mapped to Gorgias Macro templates), the webhook configuration manifest, and the SLA rule inventory to the customer's admin team. We support a one-week hypercare window to resolve reconciliation issues. We do not rebuild Mava bot configurations as Gorgias Rules or Macros inside the migration scope; that work is a separate configuration engagement.
Platform deep dives
Mava
Source
Strengths
Weaknesses
Gorgias
Destination
Strengths
Weaknesses
Complexity grading
Moderate Helpdesk migration. 3 of 7 objects need a mapping; the rest are 1:1.
Overall complexity
Moderate migration
Derived from compatibility, mapping clarity, API constraints, and data volume across Mava and Gorgias.
Object compatibility
3 of 7 objects need a mapping; the rest are 1:1.
Field mapping clarity
Field mapping is derived from defaults — final spec confirmed during the sample migration.
Timeline complexity
7-object category — typical timelines run 2–7 days end-to-end.
API constraints
Mava: Not publicly documented..
Data volume sensitivity
Mava doesn't expose a bulk API — REST + parallelization used for high-volume runs.
Estimator
Rule-based pricing — no per-record fees, no manual quotes. Migrations over 2M records are scoped individually.
Step 1
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Category
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