Helpdesk migration

Migrate from Mava to Gorgias

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

Mava logo

Mava

Source

Gorgias

Destination

Gorgias logo

Compatibility

50%

6 of 12

objects map 1:1 between Mava and Gorgias.

Complexity

CModerate

Timeline

2-4 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

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.

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

Mava logo

Mava

What's pushing teams away

  • Limited third-party integrations beyond Discord, Telegram, and website chat mean teams with established tech stacks often outgrow Mava and migrate to more flexible platforms.
  • Small review sample size makes it difficult to assess long-term reliability and enterprise-readiness before committing to the platform at scale.
  • Enterprise tier pricing is not publicly documented, which creates uncertainty for mid-market companies evaluating budget and scoping requirements.

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 Mava objects map to Gorgias

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

maps to

Gorgias

Ticket

1:1
Fully supported

Mava 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

maps to

Gorgias

Customer

1:1
Mapping required

Mava 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

maps to

Gorgias

Agent

1:1
Fully supported

Mava 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

maps to

Gorgias

Group

1:1
Fully supported

Mava 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

maps to

Gorgias

Tag

1:1
Fully supported

Mava 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)

maps to

Gorgias

Macro

lossy
Fully supported

Mava'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

maps to

Gorgias

HTTP Integration

1:1
Mapping required

Mava'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

maps to

Gorgias

SLA Policy

lossy
Mapping required

Mava'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

maps to

Gorgias

Custom Field (Ticket)

lossy
Fully supported

If 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

maps to

Gorgias

Custom Field (Ticket)

lossy
Fully supported

Mava'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

maps to

Gorgias

Custom Field (Ticket)

lossy
Fully supported

Mava 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

maps to

Gorgias

Custom Field (Customer)

lossy
Fully supported

If 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.

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.

Mava logo

Mava gotchas

Medium

Community identity linkage may be incomplete

Low

Bot configurations are channel-specific

Low

Webhook payloads lack standardized schema

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

  • Community identity records lack verified email

    Mava links community members to their Discord ID or Telegram ID rather than a verified email address in many conversation records. Gorgias requires an email to create a standard Customer record. We flag every Mava conversation where the associated user lacks an email address during scoping. The customer must either enrich these records with email addresses before migration or accept that they will land in Gorgias as anonymous or placeholder Customer records with the original platform identifier stored in external_id. Unresolved identities can affect SLA reporting and routing logic post-migration.

  • AI bot intents are not migratable as automation code

    Mava's AI bot intents and channel-specific routing rules are stored as JSON payloads that vary by channel type. Gorgias does not have a native equivalent for Discord-role-based routing or Telegram-group-based intent triggering. We extract the full intent catalog across all Mava channels and deliver it as a structured inventory document with trigger phrases and response texts mapped to Gorgias Macro templates. The customer's admin rebuilds the routing logic in Gorgias Rules. We do not migrate bot configurations as executable automation.

  • Webhook payloads require manual remapping

    Mava's webhook integrations are customer-defined with no documented standard payload schema. We extract endpoint URLs, trigger conditions, and payload structures during migration, but Gorgias HTTP Integration requires the customer or a developer to manually map the field names and data types. Payload transformation logic built in Mava (for example, formatting Discord embed structures into a unified notification format) does not carry forward and must be rebuilt.

  • Gorgias import rate caps at ~720 tickets per hour

    Gorgias's native import process averages 720 tickets per hour depending on message count per ticket. Large Mava instances with deep conversation history (two or more years of Discord, Telegram, and web chat threads) can take multiple days to import via the Gorgias API even with batch processing. We coordinate the import schedule to run during off-peak hours and run delta migrations for any records modified during the initial import window. Customers should plan for a multi-day migration window rather than expecting same-day completion.

  • SLA enforcement does not auto-rebuild in Gorgias

    Mava's SLA policies (first-response and resolution time targets scoped to channels or teams) do not map 1:1 to Gorgias SLA policies. Gorgias SLA policies are scoped to ticket priority and channel, not team membership. Any Mava team-based SLA escalation logic must be rebuilt in Gorgias as Rules that check the assignee's team membership. We document the existing Mava SLA configuration in full during scoping so the customer's admin has a complete reference for the rebuild.

Migration approach

Six steps for a successful Mava to Gorgias data migration

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

Context on both ends of the pair

Mava logo

Mava

Source

Strengths

  • Deep Discord and Telegram native integration for community-first support workflows
  • AI bot automation with intent-based routing reduces manual triage workload
  • Free tier available for small teams and early-stage community projects
  • Pricing tiers scale from free through enterprise with clear feature differentiation

Weaknesses

  • Limited third-party integrations beyond core community channels
  • No publicly documented API or developer documentation in the research data
  • Enterprise pricing opaque without direct sales engagement
  • Small review sample size limits visibility into long-term reliability
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 Mava 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

    Mava: Not publicly documented..

  • Data volume sensitivity

    B

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

Estimator

Estimate your Mava 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 Mava to Gorgias data migrations

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

Can't find your answer?

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Book a free 30 minute consultation

Most migrations land between two and four weeks for Mava instances with fewer than 10,000 conversations and email-resolvable community identities. Instances with high volumes of Discord-only or Telegram-only identities requiring pre-migration enrichment, deep conversation history exceeding one year, or complex SLA configurations requiring full rebuild planning move to five to eight weeks. Gorgias's import rate of approximately 720 tickets per hour is the primary duration driver for large conversation histories.

Adjacent paths

Related migrations to explore

Ready when you are

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