Migration Playbook

Help Scout Dixa

Help Scout to Dixa: The Complete Migration Playbook

A 38-step runbook across six phases — track your progress, and open the right tool at every step.

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TL;DR

Help Scout conversations extract via the Mailbox API 2.0 (400 req/min) and load into Dixa via POST /v1/conversations/import with timestamp preservation. The workflow redesign — mailboxes to Flows and Queues — is the hardest part.

Migrating from Help Scout to Dixa requires a full architectural shift from a pull-based, mailbox-centric email platform to a push-based, queue-and-flow routing engine — no native migration path or built-in export tool exists for conversation content. Core data entities including conversations, threads, customers, and tags can be extracted via Help Scout's Mailbox API 2.0 and loaded into Dixa through the POST /v1/conversations/import endpoint, but structural differences in field types, status values, and agent identity models require custom transformation logic. Help Scout's mailbox organization and flat IF/THEN workflows have no direct equivalent in Dixa and must be completely redesigned using Dixa's visual Flow Builder and Queue system. Additionally, the Help Scout Docs knowledge base, saved replies, and historical satisfaction ratings all require separate handling outside the primary conversation import pipeline.

Read this first

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

TL;DR Conversation history, contacts, tags, and custom fields extract cleanly from Help

TL;DR Conversation history, contacts, tags, and custom fields extract cleanly from Help Scout via the Mailbox API 2.0 and load into Dixa via POST /v1/conversations/import. Help Scout's API rate limit is 400 requests per minute per OAuth token; Dixa's import API allows 10 requests per second per token (864,000/day). The routing redesign (Help Scout mailboxes + workflows → Dixa Flows + Queues) is the most time-consuming task. Help Scout's Docs knowledge base must be migrated separately into Dixa Knowledge. Realistic timelines range from 2–3 weeks for a simple email-only migration to 5–8 weeks for complex multi-channel setups with heavy workflows.

No direct mapping for

Help Scout folders (Dixa uses Flows + queue filters), Help Scout Beacon widget (Dixa has its own widget SDK), Help Scout spam status (Dixa has no spam queue — decide whether to import these as closed or exclude them), and Help Scout reporting views (Dixa analytics are structured differently and cannot import historical metric aggregates).

If running multiple integrations concurrently during migration (e.g., your Salesforce CRM

If running multiple integrations concurrently during migration (e.g., your Salesforce CRM sync and your migration pipeline), provision a separate OAuth app and token per integration. Rate limits are enforced per token, not per account, so token isolation prevents starvation.

Merged conversation gotcha

Help Scout returns HTTP 301 for merged conversations for 60 days after merging, then returns 404. If your dataset includes recently merged conversations, complete your extraction before the 60-day window expires or you will lose access to the redirected conversation thread permanently.

Channel type constraint

The Dixa import endpoint currently supports email and widgetchat channel types. Phone conversations from Help Scout integrations (Aircall, etc.) must be imported as email-type records with metadata in the subject or a custom attribute indicating the original channel, or stored in an external data warehouse.

Image dependency risk

Images in Help Scout Docs articles are hosted on Help Scout's CDN. Canceling Help Scout without re-hosting these images produces broken images in every migrated article. This step is consistently underestimated in effort — a Docs site with 200 articles and average 5 images each means 1,000 images to download, re-host, and rewrite.

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. 0/8

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 Help Scout

    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 Dixa can hold your support model

    Solution architect 2-3 days

    Walk your current workflow through Dixa: 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 Help Scout → Dixa 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.

  6. Create end users

    Every requester must exist as an end user in Dixa. Use POST /v1/endusers. If the end user is missing, the import call returns a 400 or 422 error. Deduplicate by email address before bulk creation — Dixa will reject duplicate email entries.

  7. Map agents

    Outbound messages require a valid Dixa agentId (UUID). Provision agents in Dixa via the UI or SCIM before import. Match Help Scout agent email addresses to Dixa agent UUIDs and store the mapping in a lookup table.

  8. Create tags

    Tags must exist in Dixa before they can be referenced in import payloads. Create them via the UI or POST /v1/tags API endpoint.

Help Scout → Dixa specifics

Pre-create custom attributes
All Help Scout custom field definitions must have a corresponding custom attribute configured in Dixa (matching type and, for dropdowns, matching option values) before import payloads reference them.

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 Help Scout 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 Help Scout 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 Help Scout 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

Help Scout → Dixa specifics

List mailboxes
GET /v2/mailboxes — identify which mailboxes to include in the migration scope.
List conversations
GET /v2/conversations?mailbox={id}&status=all — paginated at 25 conversations per page. The default returns only active conversations; status=all is required to retrieve historical closed/pending records. Use the modifiedSince parameter for incremental passes during the delta sync phase.
Get threads per conversation
GET /v2/conversations/{id}/threads — message bodies live here, not in the list response. This requires one API call per conversation, which is the primary rate limit bottleneck.
Get customers
GET /v2/customers — paginated. Includes emails, phones, and profile data.
Get attachments
GET /v2/attachments/{id}/data — returns base64-encoded file content. Run as a separate background pass to avoid consuming rate limit budget during conversation extraction.

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 Help Scout → Dixa 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 Help Scout → Dixa 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 Dixa 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.

Help Scout → Dixa specifics

Get custom fields
GET /v2/mailbox-fields/{mailboxId} — returns field definitions including dropdown option IDs and display labels. Required to decode option IDs stored in conversation records.

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 Dixa sandbox that reconciles cleanly and has been reviewed by real agents.

  1. Stand up a Dixa 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 Dixa'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.

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 Dixa, 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 Help Scout 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 Dixa'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 Help Scout 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 Help Scout read-only rather than cancelled — cancelling the old contract on day one removes your only fallback.

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 Help Scout and Dixa 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 Dixa, 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 Help Scout 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.

Help Scout Dixa 20 fields
Help Scout fieldDixa fieldNotes
id external_id Store the Help Scout ID in Dixa for audit trails and delta syncs
Mailbox Queue + Contact Endpoint Mailboxes map to email integration endpoints; routing logic moves to Flows and Queues
Conversation Conversation 1:1 mapping; channel type (email, widgetchat) must be specified
subject subject Direct string mapping
status status Help Scout: active, pending, closed, spam. Dixa: open, pending, closed. No spam equivalent — filter or discard
createdAt created_at Must use Dixa's historical import endpoint to preserve original timestamp
Thread (type: customer) Inbound message Author = end user (requester)
Thread (type: reply) Outbound message Author = agent; requires valid agentId UUID in Dixa
Thread (type: note) Internal note Separate API call: POST /v1/conversations/{id}/notes
Customer End user Create via POST /v1/endusers before importing conversations
firstName + lastName name Concatenate with a space separator for Dixa's single name field
emails [] email Help Scout supports multiple emails per customer; Dixa supports multiple contact endpoints per end user
phones [] phone_number Normalize to E.164 format (+15551234567) before import
User (agent) Agent Must exist in Dixa before import; match by email address to obtain Dixa UUID
Tags Tags Create tags in Dixa first via API or UI; then apply via import payload
Custom fields Custom attributes Type conversion required; see field-type matrix below
Saved replies Templates No automated migration; recreate manually in Dixa
Docs articles Dixa Knowledge articles Separate migration via Help Scout Docs API v1
Satisfaction ratings Conversation ratings Help Scout Great/Okay/Not Good (3-point) → no direct equivalent in Dixa's CSAT (1–5 scale). Apply a mapping convention before import
Workflows Flows Complete redesign required; no import path exists
Cus m Field Type Compatibility Matrix 5 fields medium

Help Scout supports multiple emails per customer while Dixa uses multiple contact endpoints per end user, and phone numbers must be normalized to E.164 format before import, requiring data cleansing.

Help Scout fieldDixa fieldNotes
dropdown select (single-value) Option IDs must be resolved to label text first (via GET /v2/mailbox-fields/{id}); recreate option values in Dixa
single-line text text Direct string mapping
multi-line text text (multi-line) May need HTML stripping if field contains formatted content
number numeric Validate min/max if Dixa attribute has range constraints
date date Standardize to ISO 8601 (YYYY-MM-DD) before import

Risk matrix

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

ObjectRiskNotes
Conversations low Conversations map 1:1 between platforms and can be imported with original timestamps preserved via Dixa's historical import endpoint, provided the correct channel type is specified.
Threads / Messages medium Thread types map to Dixa message types with reasonable fidelity, but internal notes require a separate API call and agent reply threads require pre-resolved Dixa agent UUIDs, adding transformation complexity.
Customers / End Users medium Help Scout supports multiple emails per customer while Dixa uses multiple contact endpoints per end user, and phone numbers must be normalized to E.164 format before import, requiring data cleansing.
Tags low Tags transfer cleanly provided they are pre-created in Dixa via API or UI before the import payload references them.
Custom Fields / Attributes high Field types do not map 1:1 between systems, dropdown option IDs must be resolved to label text before recreation, and Dixa attribute range constraints must be validated against source numeric data.
Conversation Status medium Help Scout's 'spam' status has no Dixa equivalent, requiring a migration decision to either exclude spam conversations or import them as 'closed', and the mapping must be applied consistently across the entire dataset.
Satisfaction Ratings high Help Scout's 3-point scale (Great/Okay/Not Good) does not correspond directly to Dixa's 1–5 CSAT scale, requiring a custom mapping convention to be defined and applied before import with potential loss of rating fidelity.
Workflows / Flows high No import path exists for Help Scout workflows into Dixa Flows — all routing logic, queue assignments, priority branching, and escalation rules must be rebuilt manually in Dixa's Flow Builder.
Attachments medium Attachments are returned as base64-encoded content via a separate API endpoint and can number in the hundreds of thousands, making them the most time-variable extraction component with potential for significant rate limit consumption.
Docs / Knowledge Base Articles medium Help Scout Docs require extraction via a separate API with its own authentication and rate limits, and must be manually recreated or scripted into Dixa Knowledge as a completely independent migration workstream.

The hard parts

What makes this specific migration difficult, beyond the mechanics.

Workflow and Routing Redesign

Help Scout's flat IF/THEN workflows and mailbox-based organization have no import path into Dixa and must be fully rebuilt from scratch using Dixa's visual Flow Builder, Queue configurations, and skill-based routing logic.

Pull-to-Push Model Transition

Help Scout's agent-driven cherry-pick model must be replaced with Dixa's offer-based, real-time push routing, requiring agent retraining and explicit availability status management before go-live.

API Rate Limit Bottleneck

Help Scout enforces a hard 400 requests-per-minute rate limit per OAuth token, making thread-level extraction the primary bottleneck — fetching 50,000 conversations requires approximately 125 minutes of sustained API calls at the rate limit ceiling.

Custom Field Type Conversion

Help Scout's five custom field types do not map 1:1 to Dixa's custom attribute type system, requiring dropdown option IDs to be resolved to label text via a separate API call before recreation in Dixa.

Agent and End-User Pre-Creation Dependency

All Dixa agents and end users must be created and their UUIDs resolved by email address before conversation import begins, as Dixa's import API requires valid internal UUIDs for both author and requester fields.

Knowledge Base and Saved Replies Gap

Help Scout Docs articles require a separate migration via the Docs API v1 into Dixa Knowledge, and saved replies have no automated migration path — both must be handled outside the primary conversation import pipeline.

What breaks

Known failure modes. Have a recovery plan for each before you cut over.

Merged conversations returning 404

Help Scout redirects merged conversations via HTTP 301 for 60 days. After that, they return 404 with no data. Time your extraction within the 60-day window, or accept that merged conversation history before that cutoff may be irrecoverable.

Attachments as base64

Help Scout's API returns attachment file data as base64-encoded strings. Dixa's import endpoint accepts attachment URLs, not base64 content. Re-host all attachments to S3/GCS and pass URLs.

Custom field dropdown option IDs

Help Scout stores dropdown selections as option IDs (integers), not display labels. The raw conversation export contains fieldId: 42, value: 7. Without calling GET /v2/mailbox-fields/{mailboxId} to resolve 7 → "Enterprise", the data is unreadable. Always resolve option IDs to labels before transformation.

Inline image breakage

Help Scout embeds images in thread HTML with src URLs pointing to storage.helpscout.net. These become inaccessible after account cancellation. Parse and re-host during extraction.

Help Scout spam status

Dixa has no spam queue. Decide pre-migration whether to import spam conversations as closed with a spam tag, or exclude them entirely. The exclusion approach is simpler but loses the historical record.

Chat conversations via Beacon

Help Scout Beacon chat conversations have a different thread structure than email (no subject, different author fields). Map them to Dixa's widgetchat channel type, but validate that the thread structure renders correctly — the interaction model differs significantly.

Satisfaction rating scale mismatch

Help Scout Great/Okay/Not Good (3-point) → Dixa's CSAT (1–5). Recommended mapping: Great → 5, Okay → 3, Not Good → 1. Store the original rating in a custom attribute to preserve raw data.

Timezone inconsistencies

Help Scout's UI export uses company timezone for CSV and UTC for XLSX. The Mailbox API 2.0 returns UTC. Dixa's import endpoint expects ISO 8601 with timezone offset. Standardize all timestamps to UTC during extraction regardless of source format.

Empty end user lookup responses

Dixa's GET /v1/endusers?email={email} returns an empty data: [] array (HTTP 200) when no match is found — not a 404. Your deduplication logic must check data.length === 0 rather than catching an error status.

Agent deactivation

If Help Scout agents have been deactivated but their conversations are in scope, their email addresses may not exist in Dixa. Create placeholder inactive agents in Dixa or map deactivated agents to a generic "Former Agent" account to avoid broken agentId references.

Tools used in this playbook

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

FAQ

Can I migrate Help Scout conversations to Dixa with original timestamps?

Yes. Dixa's POST /v1/conversations/import endpoint accepts a createdAt field, allowing you to preserve the original Help Scout conversation timestamps during import. If you use the standard conversation creation endpoint instead, all imported tickets will reflect the date of the migration.

What are the API rate limits for a Help Scout to Dixa migration?

Help Scout allows 400 API requests per minute per OAuth token. Dixa allows 10 requests per second per API token (864,000 per day). Both return HTTP 429 when limits are exceeded, though Dixa does not include a Retry-After header.

Can I migrate Help Scout attachments to Dixa?

Yes, but it requires extracting attachment files from Help Scout's API (returned as base64), hosting them on S3 or another accessible URL, and passing the new URLs to Dixa during import. If you skip re-hosting, attachment links break when you cancel Help Scout.

How long does a Help Scout to Dixa migration take?

A small migration (under 20K conversations, email only) takes 2–3 weeks. Medium complexity (20K–100K conversations, multiple channels, custom fields) takes 3–5 weeks. Complex migrations with large volumes, knowledge base content, and workflow redesign can take 5–8 weeks.

Can I migrate Help Scout Docs articles to Dixa Knowledge?

Yes, but it's a separate process. Extract articles via Help Scout's Docs API v1, then create them in Dixa Knowledge via the Dixa API. Download and re-host any embedded images before decommissioning Help Scout, or they will break.

Or skip all of this and let us handle it

Book a 30-minute call and we'll scope your migration in a single session.