Freshchat stores conversations as message streams; HappyFox uses tickets. Migration requires API extraction, message-to-reply transformation, and batch loading under HappyFox's strict rate limits with a 10-minute lockout on breaches.
There is no native migration path from Freshchat to HappyFox. Freshchat uses a conversation-centric data model where each interaction is a flat stream of individual messages, while HappyFox uses a ticket-centric model requiring a subject, description, and structured staff/contact updates. Migrating between the two requires extracting data via Freshchat's REST API (v2), transforming conversation message streams into ticket-compatible payloads, and loading them into HappyFox via its REST API (v1.1). Custom engineering work is needed to handle message flattening, sender classification, attachment re-uploads, rate limit management, and the rebuild of bot interactions, CSAT data, and automations which cannot be migrated programmatically.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
TL;DR: Freshchat to HappyFox Migration
Freshchat is a conversation-first messaging platform; HappyFox is a ticket-first help desk. There is no native migration path between them. You must extract data through the Freshchat REST API (v2), transform conversations into ticket-compatible payloads, and load them into HappyFox via its REST API (v1.1). The hardest part is not the data volume — it is the structural mismatch. Each Freshchat conversation contains a stream of individual messages that must be flattened into a single HappyFox ticket with ordered staff and contact updates. HappyFox accepts bulk ticket creation at up to 100 tickets per request, but enforces a global rate limit of 300 POST requests per minute with a 10-minute lockout on 429 errors. At a conservative throttle of 200 POST/min, a mid-size dataset of 25,000 conversations averaging 8 messages each yields roughly 200,000 total API calls — expect 3–7 calendar days of continuous runtime for the load phase alone, plus 2–5 days each for extraction, transformation, and validation. Bot interactions, CSAT data, automations, and smart assignments cannot be migrated programmatically and must be rebuilt. Last updated: June 2025. API behaviors verified against Freshchat API v2 and HappyFox API v1.1 as of this date.
Terminology check
Accounts, Leads, Opportunities, and Activities are not native objects in Freshchat's core chat API. The documented APIs focus on users, conversations, messages, groups, channels, reports, and conversation properties, with some property behavior available only for accounts bundled with Freshsales Suite. If you depend on CRM-side data from the wider Freshworks stack, run that as a separate migration lane. (developers.freshchat.com)
Freshchat extraction rate
Freshchat does not publish explicit rate limits. In practice, sustained extraction at 2–3 requests/second with 0.3–0.5s sleeps between paginated calls is generally safe on Growth and Pro plans. Monitor the X-RateLimit-Remaining header and back off dynamically if it drops below 10.
Critical: Freshchat message_parts vs HappyFox update body
Freshchat messages use a message_parts array where each part can be text, image, file, or a structured element (buttons, carousels). HappyFox expects plain text or HTML in update bodies. You must write a transformer that converts each message_part type into HTML. Bot-generated structured elements (quick replies, carousels) will lose their interactive formatting — flatten them to text descriptions. Example: a quick-reply part {"type": "quick_reply", "content": {"text": "Choose one:", "options": ["Billing", "Technical"]}} should become <p>Choose one: [Billing] [Technical]</p>.
HappyFox's 10-minute lockout is the single biggest operational risk
Unlike most APIs that use sliding windows, HappyFox blocks all API access for a full 10 minutes after a 429 response. A single burst of over-aggressive writes will halt your entire migration pipeline. Build in conservative throttling — target 200 POST/min maximum to leave headroom.
Timestamp preservation is the most commonly overlooked issue in messaging-to-ticket migrations
If historical date accuracy matters for SLA reporting or compliance, confirm HappyFox's backdating capabilities with their support team before committing to the migration. Some teams have reported that HappyFox support can perform server-side timestamp adjustments as a one-time accommodation — confirm this for your account.
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 Freshchat
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 HappyFox can hold your support model
Walk your current workflow through HappyFox: 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 Freshchat → HappyFox 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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Archive only
Conversations older than your retention policy (consider a read-only export to S3 or a data warehouse instead of loading into HappyFox)
Freshchat → HappyFox specifics
- Ticket-centric workflow needs
- Teams that outgrow live-chat-only workflows and need structured ticket management with categories, SLAs, and formal status tracking.
- Pricing model
- HappyFox offers unlimited-agent plans (Enterprise and Enterprise Plus tiers) — attractive for large teams where per-agent pricing compounds quickly.
- Simpler tooling
- Teams that find Freshworks' fragmented product suite (Freshchat, Freshdesk, Freshsales) overlapping and expensive, and want a single help desk.
- Multi-brand segmentation
- HappyFox provides strict multi-brand and multi-tenant categorization, which benefits managed service providers and agencies.
- Knowledge base consolidation
- HappyFox bundles a built-in knowledge base with hierarchical sections, articles, and a customer-facing support center.
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 Freshchat 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 Freshchat 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 Freshchat 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
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 Freshchat → HappyFox 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 Freshchat → HappyFox 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 HappyFox 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.
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Convert message_parts
to HTML: text parts stay as-is, image parts become <img> tags with local file references, file parts become attachment references
Data Format Converter Reshape the export into the format HappyFox's importer expects -
Map conversation properties
to HappyFox custom field IDs (pre-create fields and build a lookup table)
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Map agent UUIDs
to HappyFox staff integer IDs (match by email)
Freshchat → HappyFox specifics
- Sort messages
- by created_time ascending within each conversation
- Classify each message
- by actor_type: user messages become contact replies, agent messages become staff updates, system/bot messages become private notes or are excluded
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 HappyFox sandbox that reconciles cleanly and has been reviewed by real agents.
Keep these open
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Stand up a HappyFox 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 HappyFox'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 HappyFox, 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 Freshchat 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 HappyFox'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 Freshchat 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 Freshchat 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.
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 Freshchat and HappyFox 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 HappyFox, 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 Freshchat 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.
Object Object
| Freshchat field | HappyFox field | Notes |
|---|---|---|
| User | Contact | Map email, first_name, last_name, phone, created_time |
| Agent | Staff | Match by email; create manually if needed (no bulk staff create API) |
| Conversation | Ticket | First message → ticket description; subsequent → updates |
| Message (user) | Contact reply | Appended as reply on the ticket |
| Message (agent) | Staff update | Appended via /staff_update/ endpoint |
| Message (bot/system) | Private note or excluded | Decide upfront; most teams exclude bot-only content |
| Group | Category | Create categories in HappyFox first; map by name |
| Conversation property | Ticket custom field | Create fields in HappyFox first; match by type |
| Label | Tag | Direct mapping; create tags in HappyFox |
| Attachment | Ticket attachment | Download from Freshchat, upload via multipart/form-data |
| CSAT response | No direct equivalent | Store as a private note or custom field value |
Freshchat HappyFox
| Freshchat field | HappyFox field | Notes |
|---|---|---|
| conversation_id | Custom field (cf_freshchat_id) | Store for traceability |
| status | status | Map to HappyFox status IDs via GET /api/1.1/json/statuses/ |
| assigned_agent_id | assignee | Look up staff ID by email |
| created_time | created_at or custom field | See timestamp section below |
| user.email | Primary contact identifier | |
| user.first_name + last_name | name | Concatenate |
| group_id | category | Map via pre-created category lookup |
| messages [].message_parts | Update body | Flatten message_parts into HTML body |
| messages [].actor_type | — | Determines if contact reply, staff update, or private note |
| conversation_properties | custom_fields | Match by field name; transform values |
| labels [] | tags | Name match |
Freshdesk KB Object KB Object
| Freshchat field | HappyFox field | Notes |
|---|---|---|
| Category | Section | Top-level grouping |
| Folder | Sub-section | Nested within a section |
| Article | Article | HTML body, title, status |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Conversations / Tickets | high | The fundamental structural mismatch between Freshchat's message-stream conversations and HappyFox's ticket-with-updates model requires complex transformation logic and careful message ordering to avoid data corruption. |
| Contacts | low | Freshchat users map relatively cleanly to HappyFox contacts, and both platforms expose straightforward REST endpoints for user/contact creation. |
| Agents / Staff | low | Agent records can be mapped to HappyFox staff profiles with standard field mapping, though role and permission configurations must be set up manually. |
| Message Threading | high | Each individual Freshchat message must be classified as either a contact reply or staff update and written to the correct HappyFox endpoint in chronological order, with no native threading support in the target system. |
| Custom Fields | medium | Freshchat conversation properties must be mapped to HappyFox ticket custom fields, but field types and validation rules may differ and require manual pre-creation in HappyFox before loading. |
| Tags / Labels | low | Freshchat labels map directly to HappyFox tags with minimal transformation, though tags must be pre-created or auto-created in HappyFox during import. |
| Attachments | medium | Attachments require individual download from Freshchat and re-upload as multipart/form-data to HappyFox, adding significant API call overhead and potential failure points for large files. |
| CSAT / Satisfaction Data | high | CSAT survey responses and satisfaction ratings cannot be migrated programmatically as HappyFox does not expose an API endpoint for importing historical satisfaction data. |
| Bot Interactions | high | Freshchat bot conversations, flow configurations, and bot-generated messages have no equivalent import mechanism in HappyFox and must be either discarded or archived externally. |
| Organizations / Contact Groups | medium | Organizations are not native to Freshchat's core API (they come from Freshsales Suite), so mapping them to HappyFox contact groups requires pulling data from a separate source system. |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
Conversation-to-Ticket Structural Mismatch
Each Freshchat conversation is a flat stream of messages that must be decomposed and rewritten as a single HappyFox ticket with an initial description plus ordered staff updates and contact replies, requiring sender classification for every message.
Rate Limits and Throughput
HappyFox enforces a global rate limit of 300 POST requests per minute with a 10-minute lockout on 429 errors, meaning a mid-size migration of 25,000 conversations can require multiple days of continuous runtime for the load phase alone.
Attachment Re-upload Handling
Attachments must be downloaded from Freshchat individually and re-uploaded to HappyFox as multipart/form-data POSTs, each counting against the rate limit and requiring separate API calls per file.
Non-Migratable Platform Features
Bot interactions, CSAT survey data, automation rules, and smart assignment configurations have no API-accessible equivalents in HappyFox and must be manually rebuilt in the target system.
Historical Data Export Limitations
Freshchat's native CSV export is constrained to 24-hour windows and cannot access data older than 15 months, making API-based extraction the only viable path for complete historical migration.
Routing and Taxonomy Remapping
Freshchat's routing model of channels, groups, and topics must be manually mapped to HappyFox's category-based structure, with no direct equivalence between the two organizational hierarchies.
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
Can I migrate Freshchat conversations to HappyFox using CSV export?
Not effectively. Freshchat's CSV export flattens entire chat transcripts into a single text field, losing message-level timestamps, sender attribution, and threading. The Chat-Transcript report is limited to 24-hour windows with a 15-month lookback cap. HappyFox has no native CSV import for tickets. For anything beyond small archival needs, use the API-based approach.
What are HappyFox's API rate limits for migration?
HappyFox allows 500 GET requests per minute and 300 POST requests per minute. Exceeding these triggers a 429 error with a 10-minute lockout — all API access is blocked for 10 minutes. Target 200 POST/min maximum during migration to avoid hitting this limit.
How long does a Freshchat to HappyFox migration take?
For mid-size datasets (10,000–50,000 conversations), plan for 5–15 business days. The primary bottleneck is the per-message API calls required to recreate conversation threading in HappyFox, combined with HappyFox's rate limits. Small datasets under 5,000 conversations can complete in 3–5 days.
Can I preserve original timestamps when migrating to HappyFox?
HappyFox's standard ticket creation API sets the created_at field to the time of the API call. There is no documented public API parameter to backdate ticket creation. Store the original Freshchat timestamp in a custom field, and contact HappyFox support to discuss backdating options.
What Freshchat data cannot be migrated to HappyFox?
Bot conversation flows (interactive elements like carousels and quick replies), CSAT survey results (no import API), smart assignments, automation rules, and real-time analytics data cannot be migrated programmatically. These must be rebuilt manually or preserved as notes. CRM-side objects like Leads and Opportunities from Freshsales Suite are also not native to either platform's chat/ticket model.