Freshchat to Groove migration requires translating conversation-message streams into ticket-reply threads via API. No native path exists — plan for schema transformation, message grouping, rate-limit management, and attachment re-hosting.
Migrating from Freshchat to Groove requires a complete schema translation project: there is no native migration path, no vendor-provided connector, and Freshchat is not listed as a supported source in Groove's documented Import2 integration. The fundamental data model mismatch is the core engineering challenge — Freshchat is conversation-centric, storing support interactions as a continuous stream of individual messages within a conversation object, while Groove is ticket-centric, organizing communications as threaded replies on a discrete ticket. Every record must be extracted from Freshchat's REST API v2, structurally transformed to match Groove's data model, and loaded through Groove's REST v1 or GraphQL v2 API. Rich message types native to Freshchat — bot interactions, carousel cards, quick-reply buttons, WhatsApp templates — have no equivalent in Groove and must be flattened to plain text or dropped entirely.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
Key structural mismatch
A single Freshchat conversation may contain dozens of messages from users, agents, bots, and system events. In Groove, this must become a single ticket with ordered replies. Bot interactions, carousel cards, quick-reply buttons, and other rich message parts have no equivalent in Groove's ticket model — they must be flattened to plain text or dropped.
Status mapping caveat
Groove's current help docs describe Open/Snoozed/Closed operational states, while the legacy REST v1 API exposes unread, opened, pending, closed, and spam as valid state values. These are two different status systems depending on which API version you target. Test your exact target account behavior before hard-coding status transforms — create a test ticket via API and verify the returned state values match your mapping.
Extraction bottleneck
There is no bulk "list all conversations" endpoint in Freshchat's public API. You must either: (a) iterate through users and call /v2/users/{user_id}/conversations for each, or (b) use the Reports API (POST /reports/raw with event Chat-Transcript) to get conversation IDs in bulk, then fetch details per conversation. The Reports API is limited to 24-hour windows for transcript data and 1-month windows for other event types, meaning a 1-year backfill requires at minimum 365 sequential API calls just for conversation discovery.
Groove API caveat
Groove's REST v1 API is no longer in active development — no new features or endpoints will be added. The GraphQL API (v2) is the recommended path forward, but its Inbox endpoints are still being built. Check the Groove developer documentation for current endpoint availability before starting development. Plan for the possibility that you may need to mix REST v1 (for tickets and messages) with GraphQL v2 (for contacts and companies).
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 Groove can hold your support model
Walk your current workflow through Groove: 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 → Groove 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.
Freshchat → Groove specifics
- Simplicity over complexity
- Teams that primarily need email-based support with light chat find Freshchat's omnichannel feature set — bot builders, WhatsApp template management, IntelliAssign routing — to be unnecessary overhead. Groove's intentionally constrained feature set reduces configuration burden.
- Cost reduction
- A 10-agent team on Freshchat Enterprise ($79/agent/month) pays $790/month before bot session add-ons. The same team on Groove Plus ($32/user/month) pays $320/month — a 59% reduction.
- Consolidation away from Freshworks
- Teams leaving the Freshworks ecosystem entirely no longer benefit from Freshchat's tight integration with Freshsales or Freshdesk, making it a standalone cost without ecosystem value.
- Preference for email-first support
- Groove's shared inbox model mirrors email workflows. Teams whose support volume is 70%+ email find Groove's paradigm more natural than Freshchat's chat-first interface.
- System messages
- (auto-assignment notifications, IntelliAssign events)
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
Freshchat → Groove specifics
- Complexity
- Medium (deceptively simple — the transformation work is significant)
- Conversation discovery
- 10,000 user-level queries (or ~365 Reports API calls for a 1-year window)
- Message extraction
- 10,000 conversations × ~1 page of messages each = 10,000 calls (more if conversations exceed 50 messages)
- At Freshchat's 100-calls/minute rate limit
- ~200 minutes (3.3 hours) for message extraction alone, assuming no 429 retries
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 → Groove 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 → Groove 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 Groove 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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Flatten message streams into ticket replies
Each Freshchat message becomes a Groove reply. Concatenate all message_parts [].text.content values into a single reply body. Drop or annotate rich parts (carousels, quick replies) as descriptive text.
JSON to CSV Converter Flatten nested API responses into a reviewable sheet -
Resolve actor types
Map actor_type: "user" → customer reply, actor_type: "agent" → agent reply, actor_type: "bot" → note or drop, message_type: "private" → internal note.
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Download and stage attachments
Freshchat file URLs are pre-signed S3 links that expire (typically within hours to days depending on the signing configuration). Download all attachments during extraction and store locally or in cloud storage before loading into Groove. Verify that file MIME types are supported by Groove — standard image formats (JPEG, PNG, GIF), PDFs, and common document types are accepted, but test any unusual file types against Groove's upload endpoint.
Data Format Converter Reshape the export into the format Groove's importer expects
Freshchat → Groove specifics
- Group rapid sequential messages
- Messages from the same sender within a configurable time window (recommended: 120 seconds) should be combined into a single reply. In testing, this typically reduces reply count per ticket by 30–50% for chat-heavy conversations.
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 Groove sandbox that reconciles cleanly and has been reviewed by real agents.
Keep these open
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Stand up a Groove 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 Groove'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 Groove, 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 Groove'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.
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Contact Groove support
for a data reset on your production account. Response time varies; plan for 1–3 business days.
Freshchat → Groove specifics
- Best option
- Use a separate test Groove account for all trial runs (strongly recommended — eliminates rollback risk entirely)
- API deletion
- Delete tickets one by one via DELETE /v1/tickets/{number}. At ~5 requests/second, deleting 10,000 tickets takes approximately 33 minutes.
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 Groove 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 Groove, 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.
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Rebuild automations
Freshchat assignment rules, auto-resolve rules, and bot flows do not migrate. Recreate equivalent rules in Groove's automation builder. Common mappings: IntelliAssign → Groove round-robin assignment; auto-resolve after X hours → Groove auto-close rules.
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Configure Groove integrations
Connect Slack, Shopify, Stripe, Salesforce, or other tools your team relies on. Verify webhooks are pointing to Groove, not Freshchat.
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Update customer-facing widgets
Swap the Freshchat widget JavaScript snippet for Groove's support widget on your website. Update any mobile SDK references.
Freshchat → Groove specifics
- Train your team
- Groove's interface differs from Freshchat. Key differences agents should understand: folders replace channels/topics, tags replace conversation properties, and internal notes replace private messages.
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 Freshchat Endpoint
| Freshchat field | Groove field | Notes |
|---|---|---|
| User | /v2/users | Map email, name, phone. Custom properties → customer custom fields or tags |
| Agent | /v2/agents | Must be manually created in Groove first; map by email |
| Conversation | /v2/conversations/{id} | One conversation = one ticket |
| Message (normal, actor_type=user) | /v2/conversations/{id}/messages | Flatten message_parts to text |
| Message (normal, actor_type=agent) | /v2/conversations/{id}/messages | Flatten message_parts to text |
| Message (private) | /v2/conversations/{id}/messages | |
| Message (system) | /v2/conversations/{id}/messages | No direct equivalent |
| Group | /v2/groups | |
| Channel (Topic) | /v2/channels | Depends on Groove structure |
| Conversation Property | /conversations/fields | Limited by Groove's field types |
| CSAT Rating | /csat/{id} | No confirmed programmatic CSAT import in Groove's current API |
| File/Image attachment | Message parts | Download from S3 URL, re-upload to Groove |
Freshchat Groove
| Freshchat field | Groove field | Notes |
|---|---|---|
| user.email | customer.email | Direct map, lowercase + dedupe |
| user.first_name + user.last_name | customer.name | Concatenate |
| user.phone | customer.phone | Direct map |
| user.properties [] | Tags or custom fields | Iterate and map |
| conversation.status | ticket.state | Value map (see above) |
| conversation.properties.priority | Tag or custom field | Groove's POST /v1/tickets does not accept a priority parameter; use tags (e.g., priority:high) |
| conversation.assigned_agent_id | ticket.assignee | Resolve agent email → Groove agent ID |
| conversation.channel_id | ticket.mailbox or tag | Resolve channel name → Groove mailbox |
| message.message_parts [].text.content | Reply body | Concatenate all text parts |
| message.message_parts [].file | Attachment | Download URL, re-upload |
| message.created_time | Reply timestamp | Direct map |
Freshchat Groove
| Freshchat field | Groove field | Notes |
|---|---|---|
| user.id | customer custom field (legacy_freshchat_user_id) | Direct copy for traceability |
| user.email | customer.email | Lowercase + dedupe across restore_id duplicates |
| first_name + last_name | customer.name | Concatenate with space separator |
| conversation.id | Ticket tag or custom field (legacy_freshchat_conversation_id) | Direct copy for traceability |
| conversation.status | ticket.state | Mapped per status matrix above |
| conversation.assigned_agent_id | ticket.assignee | Agent lookup by email; fallback to unassigned |
| channel_id / channel name | Mailbox or tag | Routing choice per your Groove structure |
| message.actor_type | Reply vs. note | user → customer reply, agent → agent reply, system/bot → note or drop |
| message.message_parts [].text.content | message.body | Concatenate parts, group by 120-second time window |
| message.created_time | message.sent_at or body prefix | Preserve chronology; test API timestamp acceptance |
| Attachments | Attachments on message | Download during extraction, re-upload during load (split if >25/message) |
| conversation.properties.cf_* | Tags or custom fields | Map per property; only available in Freshsales Suite accounts |
| CSAT rating | Tag (e.g., csat:4) | No native CSAT import in Groove API |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Conversations | high | Each Freshchat conversation must be transformed from a flat message stream into a Groove ticket with threaded replies, and any message ordering errors, dropped messages, or bot-message contamination will corrupt the resulting ticket history. |
| Messages | high | Individual messages carry varying types (normal, private, system, bot) that must be mapped to Groove reply types (customer reply, agent reply, note), and bot or system messages with no Groove equivalent risk data loss if not explicitly handled. |
| Attachments | high | Freshchat stores files and images in an S3 bucket with a 25 MB per-file limit, while Groove caps attachments at 20 MB per file and 25 per message, requiring size validation, re-uploading via API, and handling of any files that exceed Groove's limits. |
| Contacts (Users) | medium | Freshchat users map to Groove customers, but anonymous users lacking email addresses will produce incomplete contact records, and custom user properties must be manually mapped to Groove's customer fields. |
| Agents | low | Active and deactivated agents can be extracted from Freshchat's API and re-created in Groove, though group memberships must be remapped to Groove's agent and mailbox structure before conversation assignment can be preserved. |
| Groups and Channels | medium | Freshchat's routing model of Groups and Channels (Topics) does not map directly to Groove's mailboxes, folders, and groups, requiring a deliberate structural mapping decision before any conversation or ticket migration begins. |
| Custom Fields | medium | Freshchat conversation properties use a 'cf_' prefix and are only available on accounts within the Freshsales Suite, so field availability, types, and picklist values must be audited and manually recreated in Groove before data load. |
| CSAT Ratings | high | Groove's current API documentation does not expose a programmatic CSAT import endpoint, meaning Freshchat's 1–5 satisfaction ratings cannot be natively migrated and must be stored as tags or custom fields, losing native satisfaction reporting fidelity. |
| WhatsApp and Bot Interactions | high | Outbound WhatsApp message templates and bot-handled conversations have no equivalent in Groove's data model and are candidates for exclusion from migration scope, representing a permanent data loss decision that must be made before migration begins. |
| Conversation Statuses | low | Freshchat statuses (new, assigned, resolved, reopened) map reasonably to Groove's ticket statuses (open, pending, closed), though the exact mapping logic should be confirmed against the target Groove API version in use. |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
Chat Stream to Ticket Conversion
A single Freshchat conversation containing dozens of messages from users, agents, bots, and system events must be collapsed into a single Groove ticket with ordered, threaded replies, requiring custom message grouping and ordering logic.
No Native Migration Path
Freshchat is not listed as a supported source in Groove's Import2 integration, and no vendor-endorsed direct migration tool exists, requiring all data movement to be engineered via custom API scripting or a third-party migration service.
Rich Message Type Flattening
Freshchat-native message types including bot interactions, carousel cards, quick-reply buttons, and WhatsApp message templates have no structural equivalent in Groove's ticket model and must be converted to plain text or excluded from migration.
API Rate Limit Throughput Constraints
Both Freshchat's REST API v2 and Groove's REST v1 and GraphQL v2 APIs impose rate limits that directly constrain migration throughput, requiring throttling logic and increasing total migration duration proportionally with dataset size.
CSAT and Custom Field Remapping
Freshchat's CSAT ratings (1–5 per conversation) and conversation properties (prefixed with 'cf_') have no direct programmatic import endpoints in Groove's current API, requiring fallback storage as tags or custom ticket fields.
Anonymous User and Contact Gaps
Freshchat users may lack email addresses if they engaged anonymously via web chat or WhatsApp, creating incomplete customer records in Groove that cannot be fully reconstructed without source-side enrichment before migration.
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
Does Groove have a native Freshchat importer?
No. Groove's documented migration path points customers to Import2 or the API, and Freshchat is not listed in Groove's documented Import2 source list. You must extract data via Freshchat's REST API v2, transform conversations into Groove's ticket format, and load through Groove's REST v1 or GraphQL v2 API — using custom scripts, third-party services, or a managed migration provider.
How long does a Freshchat to Groove migration take?
It depends on data volume and API rate limits. A small account with under 5,000 conversations can be migrated in 2–5 days including testing. Larger accounts with 20,000+ conversations, heavy attachments, and complex bot interactions may take 1–3 weeks due to rate limits and the per-conversation message extraction required by Freshchat's API.
How do you handle chat messages migrating into an email ticketing system?
Build a transformation layer that groups rapid, sequential chat messages from the same sender within a time window (e.g., 2 minutes) into a single consolidated HTML block before pushing to Groove. Without grouping, a 30-second chat exchange becomes five separate ticket replies, cluttering the Groove UI.
What data can't be migrated from Freshchat to Groove?
Bot flows, automation rules, IntelliAssign configurations, WhatsApp outbound message templates, CSAT survey settings (raw ratings can move, configuration cannot), and agent availability history cannot be migrated. Rich bot message parts like carousels and quick-reply buttons must be flattened to text or dropped.
What happens to Freshchat attachments during the migration?
Attachments must be downloaded during extraction because Freshchat serves files via pre-signed S3 URLs that expire. Store them locally or in cloud storage, then upload to Groove's API. Groove limits attachments to 25 per message and 20 MB per file, so large threads may need attachments split across multiple replies.