Support integration guide
LiveChat + UbiGrowth workflows
LiveChat is a live chat platform for real-time website conversations and lead qualification. This guide covers the records that matter, how the connection should be scoped, and what the first bounded workflow should be.
Introduction
Make LiveChat part of the workflow, not another silo.
Validate connector availability for your workspace
This guide covers how a team designs a support workflow around LiveChat with UbiGrowth: which records stay authoritative, how the connection should be scoped, what the first bounded workflow should be, and how to tell whether it worked.
The records that matter are Chat, Thread, Event, Customer, Agent, Group, and Tag. LiveChat sessions are anonymous until the visitor provides details, so most chats identify only by session. Joining a chat to a customer record requires the pre-chat form or an authenticated widget.
LiveChat is not currently on UbiVibe's verified connector list. This page is an implementation design reference: use it to specify the workflow, then validate whether the connection is available and correctly scoped for your workspace before you make it a dependency. The verified UbiVibe connections today are Salesforce, HubSpot, Gmail, Google Drive, Slack, and GitHub.
Grow is the usual destination for this connection, because the value shows up as outreach, reply handling, scheduling, and pipeline execution against the connected records.
Why teams evaluate this connection
Integrations create value when they remove operating friction.
The first design decision is not which API endpoint to call; it is which system owns the record, what event should trigger work, who owns the exception path, and what successful completion means.
Support integrations are usually justified with deflection metrics, which is the wrong starting point. The expensive part of a ticket is not the reply; it is the time an agent spends assembling context from LiveChat, the CRM, the product, and the issue tracker before they can write anything useful.
The second cost is escalation. A ticket handed to another team without account context, history, and reproduction detail comes back as a question, and the customer waits through a round trip that added nothing.
You're likely here because
- Agents assemble customer context from several systems before replying
- Escalations arrive at other teams missing the detail they need
- Support tooling improvements never clear the engineering backlog
Record model
What a LiveChat integration actually reads and writes.
Integration design starts from the objects the system really exposes, not from a generic connector diagram. These are LiveChat's.
Identity and matching
LiveChat sessions are anonymous until the visitor provides details, so most chats identify only by session. Joining a chat to a customer record requires the pre-chat form or an authenticated widget.
Start here
Read Chats tagged with a sales signal that ended without a next step and route them with the page the visitor was on.
What this will not do
It will not replace an async support channel. Chat is synchronous; unresolved conversations need somewhere durable to continue.
The constraint to plan around
Chat transcripts are retained per plan and archived chats are paginated by date, so historical analysis needs the transcripts captured as they close.
Build notes
What you actually have to reason about in LiveChat.
The fields that carry meaning, how the connection authenticates, and whether the event surface can be trusted. This is the part that decides whether the integration works in month three.
| Field | Why it matters |
|---|---|
| chat id / thread id | a chat can span threads across sessions |
| visitor identity | anonymous unless a pre-chat form or authenticated widget supplied it |
| events[] | messages, system events, and file shares in one ordered stream |
| tags[] | the categorisation used for routing and reporting |
| ended_at | closure, after which the transcript archives on a retention schedule |
Authentication
Personal access token or OAuth per licence, with agent versus owner scopes deciding reach. The licence id scopes everything.
Events and delivery
A real-time websocket API plus webhooks for chat lifecycle events. Real-time matters here because a chat is synchronous and post-hoc handling misses the moment.
Workflow
How the LiveChat workflow runs.
The operating sequence, from reading the source system through to the result landing back where it belongs.
Step 01
Pick up the ticket with context
The account, purchase, and prior-conversation context for a LiveChat ticket is assembled before the agent starts writing.
Step 02
Triage against real priority
Tickets are grouped by issue type, account context, and age so the queue reflects what matters rather than arrival order.
Step 03
Draft with the human in the loop
A response is drafted from the assembled context and reviewed by the agent, who remains responsible for what the customer receives.
Step 04
Escalate with the history attached
Escalations carry account context, history, and reproduction detail into the receiving system, removing the clarification round trip.
Design decisions
The support decisions this connection forces.
Each of these has to be settled before the LiveChat workflow is allowed to write anything.
Step 01
Define the escalation contract
Decide what an escalation leaving LiveChat must include — account context, history, reproduction detail — so the receiving team does not have to ask.
Step 02
Keep the customer-facing boundary explicit
Context assembly, triage, and drafting can be automated well before automated replies are appropriate. Treat those as separate decisions.
Implementation path
How to implement the LiveChat workflow.
- 01
Pick one high-volume issue type and map exactly which context an agent needs to resolve it.
- 02
Connect LiveChat and the systems holding that context, at scopes limited to support use.
- 03
Build a triage or context surface in Launch and test it against recent real tickets rather than samples.
- 04
Once sales-signal chats route, add page-context analysis so the pages that generate qualified chats can be identified and repeated.
Governance
Controls that matter.
Control 01
Customer-facing replies stay under human review; the workflow assembles and drafts rather than autonomously answering.
Control 02
Access exposes the customer context the workflow needs, not the whole account surface.
Control 03
Billing, refund, and account-change actions require explicit human authorization.
Failure modes
How a LiveChat integration breaks in production.
Not generic integration advice. These follow from how this system actually behaves, which is why they look nothing like the list on the next guide over.
Symptom 01
An automated message interrupts an agent mid-conversation.
Cause
The integration sent into an active chat without checking agent presence.
Fix
Check for an active agent before sending, and prefer posting after the chat ends.
Symptom 02
Chats cannot be attributed to customers.
Cause
Sessions are anonymous without a pre-chat form or authenticated widget.
Fix
Configure identification at the widget; it cannot be recovered afterwards.
Symptom 03
Historical transcripts are unavailable for analysis.
Cause
Retention is plan-bounded and archived chats age out.
Fix
Capture transcripts as chats close if long-run analysis matters.
What changes at scale
Real-time websocket connections scale with concurrent agents rather than with chat volume. Archive extraction should be scheduled rather than interactive.
Examples
What a working LiveChat workflow looks like.
Bounded scenarios rather than a feature list. Each one can be verified against work the team already does.
Conversation routing
With LiveChat connected, the account, purchase, and prior-conversation context relevant to a ticket is assembled before the agent starts, instead of across five open tabs.
Triage surface
A Launch-built queue view groups LiveChat tickets by issue type, account value, and age — the view the team actually needs, without waiting for engineering capacity.
Limitations and considerations
What to validate before you depend on this.
- Chat transcripts are retained per plan and archived chats are paginated by date, so historical analysis needs the transcripts captured as they close.
- Sending into an active chat puts text in front of a person mid-conversation. An automated message arriving while an agent is typing is visibly wrong to the customer.
- When conversations need to continue asynchronously. Chat is synchronous, and unresolved threads need a durable channel to move to.
- This is not an autonomous customer-facing agent. Replies should stay under human review, particularly where the account or issue carries real consequences.
- Context quality depends on the systems behind LiveChat. A stale CRM record produces a confident and wrong summary.
FAQ
LiveChat integration questions.
What records does a LiveChat integration actually work with?
The primary records are Chat, Thread, Event, Customer, Agent, Group, and Tag. LiveChat sessions are anonymous until the visitor provides details, so most chats identify only by session. Joining a chat to a customer record requires the pre-chat form or an authenticated widget.
What should the first LiveChat workflow be?
Read Chats tagged with a sales signal that ended without a next step and route them with the page the visitor was on.
What will a LiveChat integration not do?
It will not replace an async support channel. Chat is synchronous; unresolved conversations need somewhere durable to continue.
What is the main constraint to plan around?
Chat transcripts are retained per plan and archived chats are paginated by date, so historical analysis needs the transcripts captured as they close.
What changes about a LiveChat integration at scale?
Real-time websocket connections scale with concurrent agents rather than with chat volume. Archive extraction should be scheduled rather than interactive.
How does authentication work for LiveChat?
Personal access token or OAuth per licence, with agent versus owner scopes deciding reach. The licence id scopes everything.
Does LiveChat support webhooks, and can they be trusted?
A real-time websocket API plus webhooks for chat lifecycle events. Real-time matters here because a chat is synchronous and post-hoc handling misses the moment.
What is the risk of writing to LiveChat?
Sending into an active chat puts text in front of a person mid-conversation. An automated message arriving while an agent is typing is visibly wrong to the customer.
When is connecting LiveChat the wrong call?
When conversations need to continue asynchronously. Chat is synchronous, and unresolved threads need a durable channel to move to.
What should a LiveChat integration automate first?
Start with one bounded workflow that removes a measurable handoff, duplicate-entry step, reporting delay, or follow-up gap. Expand only after the first workflow is reliable.
Does UbiGrowth require LiveChat to be replaced?
No. The operating model is designed around connecting to systems that should remain authoritative and building workflows around them rather than forcing a wholesale replacement.
Is connector availability identical for every workspace?
No. Availability can depend on provider configuration, authentication, scopes, workspace setup, and deployment state. Validate the required connection before treating it as an operational dependency.
Does this replace LiveChat?
No. LiveChat stays the system of record for conversations. The workflow layer sits around it for context assembly, triage, and connected escalation.
Will it reply to customers automatically?
Not by default, and not until the workflow has been proven. Context assembly and drafting are separate decisions from automated sending.
How do escalations improve?
The escalation carries its trigger, account context, and history into the receiving system, which removes the clarification round trip that usually costs the customer another day.
How this access is governed
What ARIA is allowed to do in LiveChat, and who decides.
Connecting LiveChat is a permission decision, not just a setup step. These are the controls that decide what ARIA can reach, what it can change, what gets recorded, and how you take the access back.
Required permissions
ARIA works through the scopes the connection was granted, and no others. Authorization happens at the provider, so the permissions being requested are shown by the system itself before anything is connected.
What it can reach
Reachable systems are the intersection of what your organization approved in the connector registry and what the requesting identity is permitted to use. Identity resolves before execution, not after.
What it can do
Actions run through explicit execution paths with state, spend, and failure boundaries — a bounded worker path rather than an open-ended agent loop with a credential.
Credential handling
Credentials live in the governed connection layer and are resolved through canonical connection identity. They are not pasted into individual workflows, prompts, or generated artifacts.
Action logging
Execution carries state and traces: what triggered the work, which connection it used, and what came back — including an explicit failure when something did not run.
Approval and revocation
Consequential actions can be made to require a person to approve them. Access can be changed or revoked at the connection, and ARIA loses that reach without unpicking the work already completed.
Start with ARIA
Ask ARIA to run this integration.
Describe the outcome you need across this system. ARIA works out the scopes, data, and actions the job requires, and operates inside the access you grant — which you can change or revoke.
- ARIA acts only through the systems and permissions you connect.
- Connections use scoped credentials you can change or revoke.
- Actions are recorded, and consequential ones can require approval.
Start here
Turn the integration into a working business outcome.
Start with ARIA to describe the outcome, then continue into the product path that fits the workflow. Connector availability and required scopes should be validated for the specific workspace before production use.