LiveChat to Help Scout migration requires API-based extraction, data model translation, and the imported flag to preserve history without triggering notifications.
There is no native import path between LiveChat and Help Scout — LiveChat is not a one-click source in Help Scout's core product, though a third-party importer (Import2) is available for standard datasets. The fundamental challenge is a data model translation: LiveChat's chat → thread → event hierarchy must be flattened into Help Scout's conversation → thread structure, where a LiveChat "thread" (a conversation session) maps to a Help Scout conversation and each LiveChat "event" (a message) maps to a Help Scout "thread." Full-fidelity migration requires custom API work using the LiveChat Agent Chat API for extraction and the Help Scout Mailbox API v2 for loading, with careful handling of Help Scout's 100-thread-per-conversation cap, 2x write rate limits, and the imported: true flag to preserve timestamps without triggering notifications.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
Help Scout limits each conversation to 100 threads maximum
If any LiveChat chat has more than 100 individual messages (events), the API will return HTTP 412 when you attempt to add thread 101. You must split these into multiple Help Scout conversations or consolidate messages before loading.
Change freeze
Once you approve the mapping schema, do not alter tags, routing rules, or custom properties in LiveChat. Changes during migration create drift between source and target that is expensive to reconcile.
Help Scout does not support user creation via the API
All agents must be invited through the Help Scout UI (or via SCIM on the Pro plan) before migration. Build a User ID lookup map (agent email → Help Scout integer User ID) before starting the import. Query GET /v2/users to retrieve IDs for all pre-created users.
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.
Objective A written scope with agreed success criteria, a named owner per workstream, and a budget approved by finance.
Keep these open
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Pull the real numbers out of LiveChat
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 -
Decide what history actually moves
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 -
Confirm Help Scout can hold your support model
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.
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Build the business case
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 LiveChat → Help Scout timeline -
Name owners and set the go/no-go date
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.
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Migrate via API
Chat transcripts, customer records, tags, custom field values, attachments
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Rebuild manually
Canned responses → Saved Replies, Auto-greetings → Help Scout Messages, Routing rules → Help Scout Workflows
LiveChat → Help Scout specifics
- Consolidation into a shared inbox
- Help Scout's conversation model treats every interaction — email, chat, phone — as a unified thread. Teams running LiveChat alongside a separate email tool want a single pane of glass for all support channels.
- Simpler pricing and agent experience
- Help Scout charges per user with unlimited contacts and an intentionally minimal interface. Teams that find LiveChat's higher-tier per-seat pricing expensive, or who don't need LiveChat's e-commerce and sales features, often downsize.
- Knowledge base integration
- Help Scout Docs and the Beacon widget provide a self-service layer tied directly to the inbox. Teams that want help center content and chat in one system land here.
- Small team, < 5,000 chats, low eng bandwidth
- Start with Help Scout's in-product importer. Run the sample import and verify edge case coverage.
- Ongoing sync during transition
- Zapier or Make for new chats, API migration for history.
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.
Objective A profiled, cleaned export with every quality defect either fixed at source or explicitly accepted.
Keep these open
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Take a full LiveChat export and profile it
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 LiveChat export for nulls, outliers and type drift -
Validate file structure before anyone writes a transform
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 -
Inventory PII and set retention
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 -
Quantify duplicates, orphans and dead references
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 LiveChat where you can — migrating them just moves the mess.
Data Cleaner Strip empty rows, stray whitespace and dead columns -
Clean and normalise the export
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.
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Produce a masked copy for sandbox work
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
LiveChat → Help Scout specifics
- Customers
- Total unique customers, customers with email vs. anonymous visitors
- Custom properties
- Document all custom chat properties and pre/post-chat survey fields; Help Scout has hard limits on these
- Attachments
- Estimate total file count and size; check for expired CDN links
- Canned responses
- These cannot be migrated via API — export and rebuild manually as Help Scout Saved Replies
- Chats exceeding 100 messages
- Query LiveChat to identify these upfront; they require splitting logic
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.
Objective A reviewed field-level mapping covering every object, with an explicit decision for every field that has no target.
Keep these open
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Generate the first-pass LiveChat → Help Scout field map
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 LiveChat → Help Scout field pair -
Map status, priority and channel values, not just field names
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.
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Decide how custom fields land
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.
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Resolve identity and threading
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.
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Plan attachments, inline images and threading order
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.
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Freeze and sign off the mapping spec
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.
Objective A pilot load into a Help Scout sandbox that reconciles cleanly and has been reviewed by real agents.
Keep these open
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Stand up a Help Scout sandbox that matches production config
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.
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Pick a deliberately nasty pilot sample
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.
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Run the load with masked data and instrument everything
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 -
Measure real throughput against the rate limit
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.
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Reconcile the pilot and triage every failure
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 -
Put real agents in front of the pilot data
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.
Objective All in-scope data live in Help Scout, agents working in the new system, and a rollback path that stayed available throughout.
Keep these open
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Pre-load history before the freeze
Load closed tickets and contacts days or weeks ahead while LiveChat 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 -
Publish the runbook with times, owners and abort criteria
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.
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Freeze LiveChat and take the final delta
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.
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Load the delta and open tickets
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 -
Repoint channels and verify with live traffic
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 -
Run the go/no-go and switch the agents
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 LiveChat read-only rather than cancelled — cancelling the old contract on day one removes your only fallback.
LiveChat → Help Scout specifics
- Customer records created during a failed migration cannot be bulk-deleted via API
- Help Scout provides no bulk customer delete endpoint. Options: manually delete via UI, or leave orphaned customer records and merge them post-cleanup. Plan for this before starting — if your migration creates 10,000+ customer records, a failed run creates a messy customer database that requires significant manual cleanup or a support request to Help Scout.
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.
Objective Documented evidence that data, workflow and reporting all survived, and a signed acceptance.
Keep these open
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Run the full reconciliation
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 LiveChat and Help Scout record-for-record -
Verify field completeness, not just record counts
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 -
Rebuild reporting and compare against baselines
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.
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Test the workflow layer end to end
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.
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Confirm compliance and produce the audit trail
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 -
Sign off, then decommission on a schedule
Get written acceptance against the Discovery success criteria. Keep LiveChat 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.
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Record count
Compare total chats extracted vs. conversations created in Help Scout
LiveChat → Help Scout specifics
- Thread count
- Spot-check 20–50 conversations to confirm all messages imported
- Customer matching
- Verify customer records are deduplicated by email
- Tag integrity
- Export Help Scout tags and compare against source
- Attachment spot-check
- Open 10 conversations with files and confirm downloads work
- Timestamp accuracy
- Verify createdAt dates match source data (timezone offsets are a common source of drift)
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.
Concept Equivalent
| LiveChat field | Help Scout field | Notes |
|---|---|---|
| Chat | Conversation | One chat maps to one conversation |
| Thread (session) | Conversation | LiveChat threads within a chat may need to be flattened |
| Event (message) | Thread (message) | Each message becomes a Help Scout thread |
| Customer / Visitor | Customer | Match on email; visitors without email need handling |
| Agent | User | Must be pre-created in Help Scout before migration |
| Group | Mailbox | Create mailboxes before import |
| Tag | Tag | Direct 1:1 mapping; normalize to lowercase |
| Canned Response | Saved Reply | Must be rebuilt manually |
| Pre-chat survey fields | Custom Field or Customer Property | Max 10 custom fields per inbox (Plus plan required) |
| Chat rating | — | Limited import support; store as tag or note |
| Chat properties (custom) | Custom Fields or Customer Properties | 10 custom fields per inbox; 50 customer/company properties globally |
LiveChat Help Scout
| LiveChat field | Help Scout field | Notes |
|---|---|---|
| chat.id | Tag or note | Store as livechat-{id} for traceability |
| chat.threads [0].created_at | conversation.createdAt | Convert ISO 8601 timestamp; must include timezone offset or use UTC |
| chat.users [type=customer].email | conversation.customer.email | Required; handle chats without email separately |
| chat.users [type=customer].name | conversation.customer.firstName/lastName | Split on first space |
| chat.users [type=agent].email | conversation.assignee | Map to Help Scout User ID (integer) via lookup |
| chat.tags | conversation.tags | Normalize to lowercase, remove spaces |
| chat.properties.rating.score | — | Import as tag (rating:good) or note |
| chat.threads [].active | conversation.status | false → closed, true → active |
Event Thread Type
| LiveChat field | Help Scout field | Notes |
|---|---|---|
| message (customer) | customer thread | Set imported: true to prevent reopening |
| message (agent) | reply thread | Map author_id to Help Scout User ID |
| system_message | note thread | Agent-only; not customer-facing |
| file event | Attachment on thread | Base64-encode; max 10 MB per file |
| filled_form (pre-chat) | note or Custom Field | Max 10 custom fields per inbox |
| rich_message | customer or reply | Flatten to HTML or plain text; preserve card/button text as structured content |
Cus mer
Customers with email addresses map cleanly, but anonymous visitors identified only by LiveChat's generated visitor IDs have no direct equivalent in Help Scout and require fallback handling.
| LiveChat field | Help Scout field | Notes |
|---|---|---|
| customer.email | customer.emails [].value | Primary identifier; Help Scout deduplicates on email |
| customer.name | customer.firstName + customer.lastName | Split on first space |
| customer.fields (custom) | Customer Properties | Requires Plus plan; max 50 globally |
| customer.last_visit.ip | — | Not importable; store in notes if needed |
| Company / domain | Organization + Company Properties | Use organizationId for company-level grouping |
Dataset Size API Calls (approx.)
| LiveChat field | Help Scout field | Notes |
|---|---|---|
| 10,000 chats × 8 msgs avg | ~80,000 writes | Single script, local staging |
| 50,000 chats × 8 msgs avg | ~400,000 writes | Staging DB, checkpoint/resume, run over 2–3 days |
| 100,000 chats × 10 msgs avg | ~1,000,000 writes | Full ETL with orchestration, parallel extraction, sequential loading |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Chat Transcripts (Message Bodies) | medium | Full message bodies can be migrated via API or Import2, but the data model translation from events to threads and the 100-thread cap introduce structural risk for long conversations. |
| Contacts / Customer Records | medium | Customers with email addresses map cleanly, but anonymous visitors identified only by LiveChat's generated visitor IDs have no direct equivalent in Help Scout and require fallback handling. |
| Attachments | medium | Attachments are supported by both the API and Import2 approaches, but must be individually downloaded from LiveChat and re-uploaded to Help Scout, adding complexity and transfer time. |
| Tags | low | Tags have a direct 1:1 mapping between the two platforms and only require normalization to lowercase for consistency in Help Scout. |
| Custom Fields / Chat Properties | high | Help Scout's hard limit of 10 custom fields per inbox means LiveChat's custom chat properties and pre-chat survey fields will likely exceed capacity, forcing data loss or consolidation. |
| Chat Ratings | high | Help Scout has limited import support for satisfaction ratings, so LiveChat chat ratings must be stored as tags or conversation notes, losing their structured and reportable nature. |
| Agents / Users | low | Agents must be manually pre-created in Help Scout before migration, but the mapping itself is straightforward once accounts exist. |
| Groups / Mailboxes | low | LiveChat Groups map directly to Help Scout Mailboxes, which must be created before import but present no structural data loss risk. |
| Canned Responses / Saved Replies | high | There is no automated migration path for canned responses; all must be manually recreated as Help Scout Saved Replies, which is error-prone and time-consuming for large libraries. |
| Automations and Routing Rules | high | LiveChat's auto-greetings, proactive triggers, URL-based routing, and department routing have no import mechanism and must be entirely rebuilt as Help Scout workflows with reduced feature parity. |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
Data Model Terminology Collision
LiveChat's "thread" represents a conversation session containing many messages, while Help Scout's "thread" represents a single message, requiring a complete structural flattening during migration.
100-Thread Conversation Cap
Help Scout enforces a maximum of 100 threads per conversation, returning HTTP 412 on thread 101, so LiveChat chats with more than 100 events must be split into multiple conversations or consolidated before loading.
Write Rate Limit Doubling
Help Scout counts each write API request as 2x toward the rate limit, effectively halving throughput and requiring careful throttling and retry logic in any automated migration script.
Anonymous Visitor Handling
LiveChat visitors without an email address are identified by a generated visitor ID, but Help Scout requires customer records with email associations, so anonymous chats need a fallback identification strategy.
Custom Fields and Properties Limits
Help Scout allows only 10 custom fields per inbox and 50 customer/company properties globally, so LiveChat's custom chat properties and pre-chat survey fields may exceed available slots and require consolidation or omission.
Automation and Workflow Rebuild
LiveChat's auto-greetings, chat routing rules, canned responses, and department-based routing have no import path and must be manually recreated as Help Scout workflows, saved replies, and Beacon configurations.
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
Can I migrate LiveChat data to Help Scout using CSV only?
Not with full fidelity. LiveChat's CSV export includes metadata only — not message bodies or full transcripts. Help Scout has no native CSV import for conversations. For full transcript migration, use Help Scout's in-product importer (Import2), the Mailbox API v2, or a managed migration service.
How do I prevent Help Scout from sending email notifications during migration?
Set imported: true on every conversation and thread you create via the API. This flag prevents Help Scout from reopening closed conversations, firing workflows, and sending customer notifications.
What data can't be migrated from LiveChat to Help Scout?
Visitor monitoring data, real-time analytics, goal tracking, auto-greetings, routing rules, and canned responses cannot be migrated via API. Canned responses must be rebuilt as Help Scout Saved Replies manually. Automations and workflows must be recreated from scratch.
How long does a LiveChat to Help Scout migration take?
A 10,000-chat migration takes roughly 9–10 hours of API execution time due to Help Scout's write rate limits (writes count 2x, with a burst cap of 12 per 5 seconds). Including planning, testing, and validation, expect 3–7 business days end-to-end.
Does Help Scout have a limit on how many messages a conversation can have?
Yes. Help Scout limits each conversation to 100 threads (messages). If a LiveChat chat has more than 100 messages, you must split it into multiple Help Scout conversations or concatenate messages to stay under the limit.