Migration Playbook

Zammad Help Scout

Zammad to Help Scout: The Complete Migration Playbook

A 35-step runbook across six phases — track your progress, and open the right tool at every step.

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TL;DR

Zammad to Help Scout migration requires custom API scripting — no native path exists. Map tickets/articles to conversations/threads, always use imported: true, and budget for the 100-thread cap.

Migrating from Zammad to Help Scout requires fully custom API scripting, as no native migration tool, vendor connector, or built-in migration path exists between these two platforms. The fundamental data model difference centers on how messages are stored: Zammad records ticket messages as discrete articles attached to a ticket, while Help Scout stores them as threads within a conversation, requiring a structural transformation of every message record during the migration. Additional architectural gaps include Zammad's first-class Organization entity having no direct equivalent in Help Scout, richer Zammad article types that must be mapped to a smaller set of Help Scout thread types, and a strict agent/customer separation in Help Scout that does not exist in Zammad's unified User model. A complete migration requires extracting data from Zammad's REST API, transforming object structures, and loading through Help Scout's Mailbox API 2.0 and the separate Docs API for knowledge base content.

Read this first

Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.

Neither Zammad nor Help Scout provides an official migration tool for this direction

Zammad documents inbound migrations (e.g., Zendesk → Zammad), but every production Zammad → Help Scout path requires custom API scripting.

The /api/v1/ticket_articles/by_ticket/{id} endpoint does not support pagination — it

The /api/v1/ticket_articles/by_ticket/{id} endpoint does not support pagination — it returns all articles for a ticket in a single response. For tickets with hundreds of articles, this can produce very large payloads. Plan your memory allocation accordingly.

pending status requires a waitUntil field

If you map any Zammad ticket to Help Scout's pending status without including a waitUntil ISO 8601 timestamp in the conversation payload, the API returns 400 Bad Request. Zammad's pending reminder state stores a pending_time field on the ticket — use that value. For pending close tickets where no reminder time is set, default to a reasonable future timestamp (e.g., 24 hours from migration time) or map to active instead.

If you omit imported

true, Help Scout will treat the import as live activity. It will send actual emails to customers for every migrated thread, update reporting metrics for the current day, trigger active webhooks, and reopen closed conversations. There is no bulk undo. Always set imported: true.

100-thread limit per conversation

Help Scout enforces a hard cap of 100 threads per conversation. If you try to add a thread to a conversation that already has 100 threads, the API returns HTTP 412. For Zammad tickets exceeding 100 articles, you must either split into multiple conversations (with cross-reference tags and notes) or consolidate system-generated articles into a single summary note.

Zammad KB articles can have internal, published, and archived states

Help Scout Docs articles support published and notpublished. Map Zammad's internal articles to notpublished in Help Scout, or omit them entirely if they're intended for agent-only use and you'd prefer to maintain them in a separate internal wiki tool.

The runbook

Work top to bottom. Tick steps as you go — your progress is saved in this browser.

01 Discovery Establish why you are moving, what "done" means, and who signs off. 0/5

Objective A written scope with agreed success criteria, a named owner per workstream, and a budget approved by finance.

  1. Pull the real numbers out of Zammad

    Support ops 1 day

    Export counts for tickets (open and closed separately), contacts, organisations, attachments, macros, triggers, automations, views and SLA policies. Note the oldest ticket date — history depth drives the whole timeline. Estimating from memory is the single most common cause of a blown migration window.

    Data Profiler Get real record counts instead of estimating from memory
  2. Decide what history actually moves

    Support lead 2 days

    Agree a cut-off with the support lead: all history, last 24 months, or open tickets plus a read-only archive. Every extra year of closed tickets adds API time and cost without adding much agent value. Get this in writing — it is the decision people relitigate mid-cutover.

    A "move everything" default is what turns a two-week migration into a two-month one.

    COI & ROI Calculator Build the 36-month business case you will need for sign-off
  3. Confirm Help Scout can hold your support model

    Solution architect 2-3 days

    Walk your current workflow through Help Scout: multi-brand, business hours, SLA targets, CSAT, side conversations, public vs internal notes, and any channel you depend on (voice, chat, WhatsApp, social). List anything with no native equivalent — those are project risks, not configuration details.

  4. Build the business case

    Project sponsor 1-2 days

    Model licence delta, migration effort, agent retraining, and the cost of staying put (Cost of Inaction). Executives approve a number, not a plan, and you will be asked for it again at the go/no-go.

    Helpdesk Migration Planner Turn ticket volume into a dated Zammad → Help Scout timeline
  5. Name owners and set the go/no-go date

    Project manager 1 day

    One named owner each for data, configuration, integrations, and agent enablement, plus a decision-maker who can call a rollback. Put the go/no-go meeting in calendars now, 48 hours before the freeze.

Zammad → Help Scout specifics

Managed hosting vs. self-hosted overhead
Zammad can run self-hosted or on Zammad's hosted offering. Teams that don't want to manage infrastructure, updates, and Elasticsearch clusters move to a fully managed SaaS platform like Help Scout.
Simplicity over configurability
Zammad's depth — custom object attributes, role-based permissions, knowledge base granularity — is powerful but adds operational complexity. Help Scout's mailbox-centric model is deliberately simpler.
Shared inbox workflow
Help Scout was designed around the shared inbox metaphor. Teams that primarily work through email, without heavy use of Zammad's state machines, SLA timers, or complex escalation rules, find Help Scout's UX faster for agents.
Ecosystem integrations
Help Scout has native integrations with HubSpot, Shopify, Jira, and Slack. Zammad's integration ecosystem relies more heavily on its REST API for custom connections.
Data residency note for EU teams
Zammad can be self-hosted in any region. Help Scout is a US-hosted SaaS (AWS us-east-1). Teams with GDPR or data residency obligations should evaluate whether Help Scout's Data Processing Agreement and Standard Contractual Clauses satisfy their requirements before migration.

Don't move on until

  • Record counts confirmed for tickets, contacts, organisations and macros
  • Success criteria signed off by the support lead
  • Freeze window provisionally booked with the business
02 Data Audit Find out what is actually in the data before you try to move it. 0/6

Objective A profiled, cleaned export with every quality defect either fixed at source or explicitly accepted.

  1. Take a full Zammad export and profile it

    Data engineer 1-2 days

    Export to CSV or JSON and profile every file: row counts, null rates per column, distinct values, and type consistency. Compare row counts against the API totals from Discovery — a gap here means your export is silently truncated, usually by pagination.

    Data Profiler Profile the Zammad export for nulls, outliers and type drift
  2. Validate file structure before anyone writes a transform

    Data engineer 1 day

    Check delimiters, quoting, encoding (expect UTF-8, watch for BOMs and Latin-1), duplicate headers, and embedded newlines in ticket bodies. Ticket descriptions with raw newlines and commas break naive CSV parsers and silently shift columns.

    A single unescaped quote in one ticket body can shift every subsequent column without any error.

    CSV Validator Catch broken headers and ragged rows in the raw export
  3. Inventory PII and set retention

    Compliance / DPO 2 days

    Scan for emails, phone numbers, payment card fragments, national IDs and anything else regulated in ticket bodies and custom fields — support tickets are where customers paste things they should not. Decide what gets migrated, masked, or dropped, and record the legal basis.

    Ticket bodies and attachments routinely contain card and ID data that never appears in a structured field.

    PII & Compliance Scanner Find regulated fields before they land in a new system
  4. Quantify duplicates, orphans and dead references

    Support ops 1-2 days

    Count duplicate contacts (same email, different casing), tickets whose requester no longer exists, organisations with no members, and attachments whose parent ticket is gone. Fix these in Zammad where you can — migrating them just moves the mess.

    Data Cleaner Strip empty rows, stray whitespace and dead columns
  5. Clean and normalise the export

    Data engineer 2 days

    Trim whitespace, drop empty rows and columns, normalise casing on emails and tags, and standardise every timestamp to UTC ISO 8601. Timezone drift is invisible at load time and shows up weeks later as SLA reports nobody can reconcile.

  6. Produce a masked copy for sandbox work

    Data engineer 0.5 day

    Generate a realistic but fake version of the export for testing and for any vendor who needs sample data. Loading real customer PII into a sandbox is a breach in most jurisdictions, and sandboxes are rarely covered by your DPA.

    PII Masker Generate a safe copy for sandbox and vendor testing

Zammad → Help Scout specifics

How many tickets?
This determines total API calls and migration duration.
How many articles per ticket?
Tickets with more than 100 articles will hit Help Scout's thread limit.
Custom object attributes?
Map which Zammad custom fields have equivalents in Help Scout's custom fields (limited to text, number, dropdown, date types).
Multi-language KB content?
Help Scout Docs has no native multi-language structure — you must choose a resolution strategy before scripting (see KB section below).
Data Profiling
Query Zammad to get total counts of tickets, articles, users, and attachments. Identify multi-language KB content, tickets with 100+ articles, and attachments over 7.5 MB. Calculate your estimated API runtime using the duration table above.

Don't move on until

  • Export parses cleanly with no ragged rows or encoding errors
  • PII inventory complete and retention decisions recorded
  • Duplicate and orphan records quantified and triaged
03 Field Mapping Turn two schemas into one signed-off mapping spec. 0/6

Objective A reviewed field-level mapping covering every object, with an explicit decision for every field that has no target.

  1. Generate the first-pass Zammad → Help Scout field map

    Solution architect 2 days

    Start from an automated match on both schemas, then review every row by hand. Automated matching gets the obvious 70% right and is confidently wrong on the rest — especially anything named "type", "status" or "custom_field_1".

    Schema Mapper Opens pre-loaded with the Zammad → Help Scout field pair
  2. Map status, priority and channel values, not just field names

    Support lead 1-2 days

    Enumerate every value in each picklist on both sides and map them explicitly. Value-level mismatches are the defect class that survives all the way to production because the field itself mapped fine — a ticket that should be "Pending" arriving as "Open" reopens SLA clocks.

    Statuses with no target equivalent (on-hold, pending-customer) need a policy decision, not a best guess.

  3. Decide how custom fields land

    Solution architect 2 days

    Create the target custom fields first, matching type exactly (a dropdown mapped to free text can never be mapped back). Where Help Scout has no equivalent, decide between a new custom field, a tag, or a note appended to the ticket body — and record which.

  4. Resolve identity and threading

    Data engineer 1 day

    Decide how source IDs are preserved — most platforms will not let you set the primary key, so keep the original ID in a custom field. Without it, reconciliation becomes fuzzy matching and every future support question about an old ticket is unanswerable.

    Losing the original ticket ID makes reconciliation and rollback effectively impossible.

  5. Plan attachments, inline images and threading order

    Data engineer 1-2 days

    Confirm size limits, allowed MIME types, and whether inline images survive as attachments or need rehosting. Decide the comment ordering and author attribution rules: comments loaded out of order, or all attributed to the API user, destroy the conversation history agents rely on.

  6. Freeze and sign off the mapping spec

    Project manager 1 day

    Version the spec, walk the support lead through it row by row, and get explicit sign-off. Any change after this point goes through change control — mid-flight mapping edits are how partial loads happen.

Don't move on until

  • Every source field is mapped, deliberately dropped, or parked in a custom field
  • Status, priority and channel value maps agreed with the support lead
  • Mapping spec version-controlled and signed off
04 Test Migration Prove the pipeline on a small, representative slice. 0/6

Objective A pilot load into a Help Scout sandbox that reconciles cleanly and has been reviewed by real agents.

  1. Stand up a Help Scout sandbox that matches production config

    Solution architect 2-3 days

    Create the custom fields, groups, brands, business hours and SLA policies first. A pilot into a default sandbox tests nothing, because the failures you care about are all configuration mismatches.

  2. Pick a deliberately nasty pilot sample

    Data engineer 0.5 day

    Take 500-1000 records chosen for difficulty, not convenience: the longest ticket threads, tickets with the most attachments, non-Latin character sets, merged and split tickets, deleted requesters, and every status value. A clean random sample proves only that easy records are easy.

  3. Run the load with masked data and instrument everything

    Data engineer 1-2 days

    Log every API request and response with its source record ID. When 40 records fail out of 10,000 you need to know exactly which ones and why, without re-running the whole batch.

    PII Masker Never load real customer PII into a sandbox
  4. Measure real throughput against the rate limit

    Data engineer 1 day

    Record achieved records-per-hour under Help Scout's actual rate limits, including retries and backoff. Extrapolate to the full volume: if the maths says the full load exceeds your freeze window, you fix that now, not on cutover night.

    Published rate limits are ceilings, not throughput. Assume real-world rates are meaningfully lower once retries and backoff are counted.

  5. Reconcile the pilot and triage every failure

    Data engineer 1-2 days

    Diff source against target on record counts and field-level values. Every discrepancy gets a root cause and a fix — "probably fine" at pilot scale becomes thousands of broken records at full scale.

    Migration Validation Tool Diff the pilot batch against source before scaling up
  6. Put real agents in front of the pilot data

    Support lead 2 days

    Have two or three agents work sample tickets end to end in the sandbox. They find the things reconciliation cannot see: unreadable threading, missing context, macros that no longer make sense. Fix the mapping, then re-run.

Zammad → Help Scout specifics

Sandbox Run
Map a subset of data (e.g., 1,000 closed tickets) into a Help Scout trial account. Verify formatting, attachments, timestamps, thread ordering, and that no emails were sent to customers.

Don't move on until

  • Pilot batch reconciles to 100% on record counts
  • Agents have reviewed sample tickets and confirmed they are workable
  • Measured throughput extrapolates to a viable full-load window
05 Cutover Execute the switch inside a controlled, reversible window. 0/6

Objective All in-scope data live in Help Scout, agents working in the new system, and a rollback path that stayed available throughout.

  1. Pre-load history before the freeze

    Data engineer 3-10 days

    Load closed tickets and contacts days or weeks ahead while Zammad stays live. Only open tickets and the final delta need to move inside the freeze — this is the single biggest lever on window length.

    Helpdesk Migration Planner Size the freeze window from Help Scout's real API limits
  2. Publish the runbook with times, owners and abort criteria

    Project manager 1 day

    A timed sequence: freeze start, final export, delta load, channel switch, smoke test, go/no-go, agent switch. Name who does each step and the explicit condition that triggers a rollback. Decide the abort criteria before the night, when nobody wants to be the one to call it.

  3. Freeze Zammad and take the final delta

    Support ops 2-4 hours

    Stop new ticket creation, let agents finish in-flight replies, then export everything changed since the pre-load. Announce the freeze to the whole business, not just support — someone always tries to raise a ticket during it.

    Tickets created during an unenforced freeze land in the old system and are the most common source of permanently lost data.

  4. Load the delta and open tickets

    Data engineer 2-6 hours

    Run the delta load, then reconcile counts before touching any channel. Do not repoint email until the delta has verified — an inbound ticket arriving mid-load is far harder to untangle than a few extra minutes of freeze.

    Migration Validation Tool Confirm the final delta landed before you reopen
  5. Repoint channels and verify with live traffic

    IT / integrations 2-4 hours

    Switch email forwarding and MX or connector settings, update chat widgets and web forms, and re-authorise integrations. Then send real test tickets through every channel and confirm each lands, routes and triggers the right automation.

    Email forwarding changes can take up to a full DNS TTL to propagate — check the TTL days in advance and lower it if needed.

    Cron Expression Builder Schedule the delta syncs that run through the freeze
  6. Run the go/no-go and switch the agents

    Project sponsor 1-2 hours

    Walk the exit criteria with the decision-maker, call it explicitly, then move agents over with a named person on hand for the first few hours. Keep Zammad read-only rather than cancelled — cancelling the old contract on day one removes your only fallback.

Zammad → Help Scout specifics

Delta Sync & Cutover
On cutover day, run a delta script that only queries Zammad for tickets updated since the Historical Sync began (updated_at > {sync_start_timestamp}). This takes minutes, enabling near-zero downtime.

Don't move on until

  • Full historical load complete and counts matched
  • Inbound channels repointed and verified with live test tickets
  • Rollback decision point passed explicitly, not by default
06 Validation Prove the migration is complete, then close it out. 0/6

Objective Documented evidence that data, workflow and reporting all survived, and a signed acceptance.

  1. Run the full reconciliation

    Data engineer 1-2 days

    Compare source and target on every object: total counts, counts by status, counts by group, attachment counts, and field-level spot checks on a random sample. Produce one report you can hand to an auditor.

    Migration Validation Tool Reconcile Zammad and Help Scout record-for-record
  2. Verify field completeness, not just record counts

    Data engineer 1 day

    Re-profile the loaded data and compare null rates per field against the source profile. Matching record counts with a field that silently arrived empty is the failure mode counts alone will never catch.

    Data Profiler Prove field completeness held up through the load
  3. Rebuild reporting and compare against baselines

    Support ops 2-3 days

    Recreate your core dashboards — volume, first response time, resolution time, CSAT — and compare to pre-migration figures for the same period. Explain every variance; a changed SLA calculation is a real finding, not a rounding error.

    SLA and first-response metrics are usually recalculated from the loaded timestamps, so they will differ if any timestamp mapping was approximate.

  4. Test the workflow layer end to end

    Support ops 2 days

    Fire every trigger, automation, SLA escalation, macro and notification with a live ticket. Workflow does not migrate — it gets rebuilt — so it is untested until someone has actually watched it run.

  5. Confirm compliance and produce the audit trail

    Compliance / DPO 1 day

    Re-scan the loaded data for regulated fields, confirm retention and deletion policies are configured in Help Scout, and file the evidence with your PII decisions from the audit phase.

    PII & Compliance Scanner Produce the compliance evidence your auditor will ask for
  6. Sign off, then decommission on a schedule

    Project sponsor 1 day

    Get written acceptance against the Discovery success criteria. Keep Zammad read-only for an agreed period (30-90 days is typical), take a final archive export, and only then cancel. Diarise the decommission date so it does not quietly renew.

Don't move on until

  • Full reconciliation report attached to the project record
  • Reporting baselines match pre-migration figures within agreed tolerance
  • Formal acceptance signed and archive retention scheduled

Field mapping reference

The field-by-field mapping for each object. Use this as the starting point for your mapping spec.

State Status 7 fields
Zammad fieldHelp Scout fieldNotes
new active
open active
pending reminder pending Requires waitUntil timestamp — see below
pending close pending Requires waitUntil timestamp — see below
closed closed
merged closed Add tag merged; see merged ticket handling above
removed — Skip, or map to closed with a tag

Risk matrix

Per-object risk for this pair. Plan extra validation around anything marked high.

ObjectRiskNotes
Tickets / Conversations low Zammad tickets map directly to Help Scout conversations with clear field equivalents for subject, status, and assignee, though metadata such as Zammad ticket number and original group must be preserved in custom fields.
Articles / Threads medium Zammad articles map to Help Scout threads with reasonable fidelity for standard types, but social channel articles (Twitter, Facebook, Telegram) have no native equivalent and must be downgraded to note threads with channel context embedded in the body.
Attachments medium Attachments must be individually fetched from Zammad's attachment endpoint per ticket and article ID, then re-uploaded to Help Scout threads, creating significant volume and requiring careful memory allocation for large payloads.
Customers / Contacts low Zammad Customer-role users map cleanly to Help Scout Customer objects, and the API supports standard fields including email, phone, and social handles, though role evaluation logic must correctly filter out agent users.
Agents / Users medium Help Scout does not support agent creation via the REST API, requiring all agents to be manually invited through the UI or SCIM before migration so that Zammad agent emails can be resolved to Help Scout User IDs during load.
Organizations high Zammad's Organization entity has no first-class equivalent in Help Scout, requiring all organizational hierarchy, shared visibility settings, and domain associations to be flattened into a single company field on each customer record with potential data loss.
Custom Fields / Object Attributes high Zammad's Object Attributes support custom fields on tickets, users, and organizations with varied types, while Help Scout's custom fields are scoped per mailbox and limited to text, number, dropdown, and date types, meaning complex custom data structures may not migrate faithfully.
Tags low Zammad tags per ticket map directly to Help Scout tags per conversation with no structural difference, making this one of the lowest-risk data entities in the migration.
Merged Tickets medium Zammad merged tickets retain their articles on the source record rather than the target, requiring each merged ticket to be imported as an independent closed conversation with a merged tag and a cross-reference note rather than attempting to reconstruct the merged history.
Knowledge Base Content high Zammad's multi-language KB with per-article visibility settings must be migrated to Help Scout Docs via a separate API with a different collection-category-article hierarchy and no native multi-language support, requiring significant pre-migration structural decisions and custom transformation logic.

The hard parts

What makes this specific migration difficult, beyond the mechanics.

No Native Migration Path

Neither Zammad nor Help Scout provides an official migration tool for this direction, requiring fully custom API scripting for every production migration.

Article-to-Thread Type Mapping

Zammad supports article types such as email, phone, note, web, twitter, facebook, and telegram, which must be manually mapped to Help Scout's narrower set of thread types: customer, reply, note, phone, and chat.

Organization Entity Flattening

Zammad's first-class Organization object with hierarchy and permissions has no equivalent in Help Scout, requiring all organization data to be flattened into the customer's company field with optional tags for filtering.

Agent and Customer Role Separation

Zammad treats agents and customers as Users differentiated by role assignment, while Help Scout enforces a strict API-level separation, requiring extraction scripts to evaluate each Zammad user's role and route them to the correct Help Scout endpoint.

Knowledge Base Structural Mismatch

Zammad's multi-language Knowledge Base with per-article visibility settings must be migrated to Help Scout's Docs API, which uses a different hierarchy and has no native multi-language structure, requiring a resolution strategy before scripting begins.

Help Scout API Rate Limit Management

Help Scout enforces account-level rate limits shared across all connections, meaning parallel extraction workers amplify backoff collisions and require a single-threaded sequential loader with exponential backoff to avoid migration failures.

Tools used in this playbook

All free, all run entirely in your browser — nothing is uploaded.

FAQ

Is there a native migration tool from Zammad to Help Scout?

No. Neither Zammad nor Help Scout provides a built-in migration tool or connector for this direction. You must use API-to-API scripting: extract via Zammad's REST API and load through Help Scout's Mailbox API 2.0 with the imported: true flag.

Will Help Scout send emails to customers during migration?

Only if you forget the imported: true flag on thread creation requests. When imported is set to true, Help Scout suppresses all outgoing emails, prevents closed conversations from being re-opened, and stops data from skewing current-day reporting metrics.

What happens to Zammad organizations in Help Scout?

Help Scout has no first-class Organization object. You must flatten Zammad organization names into the customer's company field and optionally use tags for organization-based filtering or grouping.

How do I handle attachments larger than 7.5 MB?

Help Scout enforces a 10 MB limit per attachment, but base64 encoding adds ~33% overhead, making the effective raw file size limit about 7.5 MB. For files exceeding this, upload them to external storage (like AWS S3) and inject a download link into the Help Scout thread body.

How long does a Zammad to Help Scout migration take?

It depends on ticket volume and your Help Scout plan's rate limits. At 400 requests/minute (Plus plan), 25,000 tickets with 5 articles each takes roughly 5–10 hours of API runtime. Total project time including scripting, testing, and validation is typically 1–3 weeks.

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