Helpdesk migration
Field-level mapping, validation, and rollback between Keeping and Gorgias. We move data and schema; workflows are rebuilt natively in Gorgias.
Keeping
Source
Gorgias
Destination
Compatibility
8 of 12
objects map 1:1 between Keeping and Gorgias.
Complexity
CModerate
Timeline
2-4 weeks
Overview
Keeping is a Slack-native helpdesk built for small teams who want to manage support tickets without leaving their messaging tool. It has no standalone database export, no native CRM layer, and no reporting module; the customer record lives inside ticket metadata and Slack channel context. Migrating to Gorgias means moving from a messaging-tool extension to a dedicated e-commerce helpdesk with deep Shopify integration, per-ticket pricing, and a full API for contacts and tickets. We extract every Keeping ticket and its associated customer context from Slack-thread export, reconstruct the customer record in a staging layer, then map it to the Gorgias Customer and Ticket objects. We preserve the original ticket timestamps, assignee resolution, and any custom properties stored in Slack message metadata. We do not migrate Slack Channels, automations, macros, or reports as code; we deliver a written inventory of these for your admin to rebuild in Gorgias. Gorgias charges per ticket volume on all tiers, not per-agent, which changes the cost model significantly for high-volume support teams.
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 Keeping 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.
Keeping
Ticket
Gorgias
Ticket
1:1Keeping tickets are the primary data object and map directly to Gorgias Ticket. We extract the ticket subject, body, channel of origin (email or Slack), status, assignee (by email resolution to Gorgias User), priority, and tags from the Slack thread. The original Slack thread timestamp becomes the Gorgias created_datetime and last_message_datetime fields. Custom properties stored in Slack message metadata (such as order numbers or internal tracking flags) map to Gorgias custom fields on Ticket, which we pre-create via the Gorgias API using the external_id, object_type=Ticket, label, and definition structure.
Keeping
Customer
Gorgias
Customer
1:1Keeping does not have a standalone Customer object; customer data lives inside ticket metadata as email addresses, names, and sometimes phone numbers extracted from Slack thread context. We reconstruct the customer record by iterating every ticket, extracting unique customer identifiers, and deduplicating by email. The reconstructed Customer record maps to Gorgias Customer with email, name, phone, and any extracted e-commerce identifiers. Customer external_id is set to the Keeping ticket ID for traceability. If no email is present in the thread, we flag that record for manual review during migration.
Keeping
Slack Channel
Gorgias
Tag or Macro
lossyKeeping organizes tickets by Slack Channel, and each channel represents a support queue or topic. We treat Slack Channels as Gorgias Tags on the Ticket object, preserving the channel-to-tag relationship so that Gorgias agents can filter by the original Keeping queue. Alternatively, if the customer uses Slack Channels as routing rules (e.g., billing-channel routes to a billing team), we convert these to Gorgias Macros with routing actions, though macros are not migrated as code and require rebuild.
Keeping
Engagement: Email
Gorgias
Message
1:1Keeping email tickets contain a message thread with sender, recipient, subject, and body. These map to Gorgias Ticket Messages in chronological order. We preserve the original sender email address, timestamp, and message body (plain text or HTML). Any inline images in email bodies migrate as embedded assets linked to the message.
Keeping
Engagement: Slack Thread Reply
Gorgias
Message
1:1Slack thread replies from agents and customers are captured as ticket messages in Keeping. We map each Slack thread message to a Gorgias Ticket Message with the same timestamp sequence, preserving the conversation order. The Slack message author maps to the Gorgias User by email resolution. Customer replies in the Slack thread map to customer-side messages in the Gorgias ticket.
Keeping
Attachment (Slack message file)
Gorgias
Attachment
1:1Keeping tickets attached to Slack messages may contain files (screenshots, PDFs, order exports). We extract these from the Slack thread export and attach them to the corresponding Gorgias Ticket Message. We flag any attachments that were stored as Slack message files but are inaccessible due to workspace permission changes or deleted workspace files. Attachments migrate as binary blobs via the Gorgias API, preserving filename and MIME type.
Keeping
Agent / Owner
Gorgias
User
1:1Keeping Agents are Slack workspace members who have been given access to specific channels. We resolve Keeping agents to Gorgias Users by email match. Any agent without an email in the Keeping export is flagged in the reconciliation queue. We provision the Gorgias Users (name, email, role) before ticket import so that assignee resolution is satisfied at insert time.
Keeping
Customer Email Address
Gorgias
Customer Email
1:1Email addresses extracted from Keeping tickets become the primary identifier on the Gorgias Customer object. The email address is set as the Customer.email field and used as the dedupe key during import. If the same customer appears across multiple tickets (same email address), we merge them into a single Gorgias Customer with multiple associated tickets.
Keeping
Ticket Timestamp
Gorgias
Ticket created_datetime and last_message_datetime
lossyKeeping derives ticket creation time from the first Slack message in the thread. We preserve this as the Gorgias Ticket created_datetime and last_message_datetime fields. This is critical for SLA reporting in Gorgias and for historical audit. We do not reset timestamps to migration time; the original Slack timestamp is the system of record.
Keeping
Ticket Tags
Gorgias
Tag
lossyKeeping supports channel-based tagging and any custom tags applied by agents. We extract all tags from the Keeping ticket metadata and map them to Gorgias Tags on the Ticket. Tags are stored as string arrays in Gorgias. If tags represent categories (billing, shipping, refund), they map directly; if tags represent internal routing (assigned-to-jane, escalated), we document them for the customer's admin to configure as Gorgias Rules or Macros post-migration.
Keeping
Slack Message Metadata (custom properties)
Gorgias
Custom Field
lossyKeeping stores some custom metadata in Slack message properties (such as order IDs, internal tracking codes, or source attribution). We extract these as key-value pairs and create matching Gorgias custom fields on the Ticket or Customer object via the Gorgias API. The custom field definition must specify the type (boolean, number, text) and the object_type (Ticket or Customer). We pre-create these fields before any record import.
Keeping
Knowledge Base (if applicable)
Gorgias
Help Center Article
1:1If Keeping has been used to share knowledge base articles via Slack (less common), we extract these as plain-text documents and map them to Gorgias Help Center Articles. Gorgias supports article creation via API with title, body, and publication status. This is a lower-confidence migration path because Keeping has no native knowledge base feature; articles are typically shared as Slack messages and require manual content extraction.
| Keeping | Gorgias | Compatibility | |
|---|---|---|---|
| Ticket | Ticket1:1 | Fully supported | |
| Customer | Customer1:1 | Fully supported | |
| Slack Channel | Tag or Macrolossy | Fully supported | |
| Engagement: Email | Message1:1 | Fully supported | |
| Engagement: Slack Thread Reply | Message1:1 | Fully supported | |
| Attachment (Slack message file) | Attachment1:1 | Fully supported | |
| Agent / Owner | User1:1 | Fully supported | |
| Customer Email Address | Customer Email1:1 | Fully supported | |
| Ticket Timestamp | Ticket created_datetime and last_message_datetimelossy | Fully supported | |
| Ticket Tags | Taglossy | Fully supported | |
| Slack Message Metadata (custom properties) | Custom Fieldlossy | Fully supported | |
| Knowledge Base (if applicable) | Help Center Article1:1 | 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.
Keeping gotchas
Data lives in Gmail, not Keeping — extraction needs Gmail API
Internal notes do not appear in Gmail
Enterprise tier has a 10-user minimum at $49/user/month
No public API surface beyond the Chrome extension
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
Slack export audit and data mapping
We request a full Slack workspace export from the Keeping admin covering all support channels, including archived threads and any message edits. We parse the export channel by channel, identifying ticket boundaries (first message in a thread is the ticket open), customer identifier locations (email in message metadata or quoted text), agent attributions, and attachment URLs. We produce a pre-migration data map showing estimated ticket count, customer deduplication estimate, attachment count, and any data gaps (deleted messages, inaccessible files). This audit determines the migration timeline and flags any records that require manual customer-record construction.
Gorgias schema pre-creation
We provision the Gorgias destination environment: creating User accounts for each resolved agent, pre-creating any custom fields on Ticket and Customer objects (via the Gorgias API POST /api/custom-fields with object_type, label, definition, and required flags), and setting up Tags that mirror the Keeping Slack Channel structure. We configure the Gorgias inbox routing rules for each channel-to-team mapping derived from the Keeping Slack architecture. This step runs before any record import so that all lookup dependencies are satisfied at insert time.
Customer record reconstruction
We iterate every Keeping ticket in the parsed Slack export, extract unique customer identifiers (email, name, phone), and build a deduplicated Customer staging table. For each Customer record, we associate all Ticket IDs from which that customer's data was extracted. Customers with no email are flagged with a placeholder and routed to the manual review queue. We write the Customer records to Gorgias via the REST API before any Ticket import, ensuring the Customer ID is available for the Ticket-to-Customer relationship.
Ticket and message import
We import Keeping tickets to Gorgias Tickets in chronological order. Each Ticket is linked to its reconstructed Customer by email lookup. Agent assignment resolves by matching the Slack message author to the pre-provisioned Gorgias User by email. Message history (email body and Slack thread replies) migrates as Ticket Messages in sequence, preserving the original timestamps. Attachments download from Slack, are stored in a temporary file store, and are uploaded to the corresponding Gorgias Ticket Message via the API.
Reconciliation and validation
We produce a row-count reconciliation report comparing Keeping ticket counts (as parsed from Slack) against Gorgias Ticket counts, Customer counts against deduplication estimates, and Message counts against thread reply totals. We spot-check 20-30 randomly selected tickets in Gorgias against the source Slack threads, validating subject accuracy, customer linkage, timestamp preservation, and message sequence. Any discrepancies are corrected in the Gorgias environment before the cutover window opens. We do not modify the source Keeping data at any point.
Cutover and automation handoff
We freeze new ticket creation in Keeping during the cutover window, run a final delta migration of any tickets created or updated since the initial export, and then mark the migration as complete. We deliver the written automation inventory documenting the Slack Channel routing patterns as recommended Gorgias Rules, the tagging structure as Tags, and any implied macros for the customer's admin to implement. We support a five-business-day hypercare window for reconciliation issues. We do not rebuild automations or configure macros as part of the migration scope; those are separate configuration engagements.
Platform deep dives
Keeping
Source
Strengths
Weaknesses
Gorgias
Destination
Strengths
Weaknesses
Complexity grading
Moderate Helpdesk migration. 4 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 Keeping and Gorgias.
Object compatibility
4 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
Keeping: Not publicly documented.
Data volume sensitivity
Keeping 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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FAQ
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