Events Reference

What every event and attribute in Analytics means, written in plain English. Your decoder ring for the event and attribute pickers.

Analytics names things the way a system names them — lead.created, participant.sc_type, journey.sc_execution_status. One name always means exactly one thing, which is what makes the numbers reliable, but it does mean the pickers need translating.

That's this page. Keep it open next to the query builder.

The picker is the truth, not this page.

The event and attribute pickers only ever show what your organisation has actually produced. If you've never used campaigns, journey.started won't appear. If you've never stored a city attribute on a lead, lead.city won't appear.

So an event missing from your picker isn't broken — it just hasn't happened yet. And a page like this one can only tell you what a name means, never whether you have it.

How to read a name

Event names describe something that happened, in the order thing → what happened to it:

lead.created            a lead was created
lead.status.updated     a lead's status changed
message.receipt.read    a message was read

Attribute names are always area.name. The part before the dot says which area of the product the detail comes from:

lead.sc_status          the lead's status
message.sc_event_sub_type   what kind of message it was
journey.sc_name         the name of the campaign or automation involved

The sc_ in an attribute name simply marks it as a SalesChat-defined field. Attributes you send never have it — yours appear as lead.city, lead.tier, lead.policy_number.

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Events

Leads

Event	What it means	Typical use
lead.created	A new lead was created.	New-lead volume over time, by source, campaign or any attribute you store
lead.assigned	A lead was assigned to an agent — the first time, or on every reassignment.	Workload distribution, how leads get routed, how often leads change hands
lead.status.updated	A lead moved between active, inactive and expired. Carries both the old and the new value.	Churn and expiry, how long leads stay active
lead.attribute.set	A lead's stage or disposition was set — the SalesChat-managed pipeline fields.	Pipeline movement: how many leads reached Interested, Qualified, Won
lead.attribute.updated	One of your own attributes on a lead changed — city, budget, policy_number. Carries every key that changed in that write.	Tracking data quality and CRM sync; spotting which fields get filled in and when
user.attribute.updated	The same, for an attribute on an agent rather than a lead.	Rare; agent-profile changes

lead.attribute.updated does not fire when an attribute is deleted. Removing an attribute is currently invisible to Analytics.

Reports built on these: new leads and where they come from · new vs returning · new lead to a real conversation

Messages

Event	What it means	Typical use
message	Every message in a lead's conversation, whoever sent it — the lead, an agent, or an automation. Your highest-volume event by far.	Conversation volume, who is doing the talking, template usage, reply rates
user.message.sent	A message sent by an agent, recorded against the agent rather than the lead.	Agent productivity — use this whenever you want to count agents, not conversations
message.receipt.sent	WhatsApp accepted the message for delivery.	Delivery funnel
message.receipt.delivered	The message reached the lead's phone.	Delivery funnel
message.receipt.read	The lead opened the message.	Read rates by template, campaign or time of day

Don't add message and user.message.sent together.

When an agent sends a message, both events are recorded — one about the conversation, one about the agent. Counting both means counting that message twice. Pick the one that matches your question:

• "How many messages went out?" → message, filtered to participant.sc_type = user

• "How many agents sent something?" → user.message.sent, counted as unique

Reports built on these: who is actually doing the talking · buttons vs typing · delivery health · which template earns its place · messages that never went out

Conversations (sessions)

A session is one continuous conversation with a lead, from the first message to the point it's closed or times out.

Event	What it means	Typical use
lead.session.started	A conversation opened.	Conversation volume, inbound demand by hour or day
lead.session.queued	The conversation went into the queue waiting for an agent.	How much of your inbound has to wait for a human
lead.session.ended	The conversation closed. Carries how long it lasted and why it ended.	Handling time, resolution vs timeout

Reports built on these: how long are our conversations · how much inbound waits for a human · how bad does it get (p90)

Campaigns, automations and inbound rules

Internally, all three are called a journey — one name for "something that ran on its own and did something to a lead". journey.sc_type tells you which kind you're looking at: campaign, automation or inbound.

Event	What it means	Typical use
journey.started	A campaign or automation run began.	How often automations fire; campaign launches
journey.ended	That run finished.	Run duration, completion
journey.execution	One attempt against one lead — the workhorse event. Carries whether it succeeded and, if not, why.	Automation reliability, failure reasons, how many leads an automation actually reached

journey.execution counts runs, not leads. If an automation fires three times for the same lead, that's three executions. To count leads, use the Unique measurement.

Reports built on these: is this automation reliable · how many leads did this campaign reach · which campaign converts best · the full campaign-to-pipeline funnel

AI agent events

If your organisation uses the SalesChat AI agent, you'll also see events beginning ai.. They behave like any other event here — countable in Trends, usable as a funnel step, filterable and breakable-down.

Agent Studio has a purpose-built surface for reading them, explained in AI Analytics. That page tells you what a Verdict or a Goal means; this one tells you what the names are so you can build your own reports.

Event	One row per…	Carries
ai.started	AI conversation, when it begins	Which agent, and what triggered it
ai.ended	AI conversation, when it finishes	The verdict, how it ended, how long it took, goals hit
ai.turn	Turn within a conversation	Tokens, latency, tool calls made in that turn
ai.tool_call	Tool call. Your highest-volume AI event by far.	Which tool, whether it worked, and why not
ai.goal	Conversation × goal — one row for each goal, for each conversation	That goal's name, whether it was met, and its score

Grain is the thing that goes wrong here. These five events count different objects, and a report built at the wrong one is wrong without looking wrong.

ai.ended counts conversations. ai.turn counts turns. ai.tool_call counts calls. ai.goal counts conversation-and-goal pairs, so a conversation with three goals contributes three rows — and "how many goals were met" is a different number from "how many conversations met all their goals".

Pick the event that counts the object your question is about, then filter.

About the conversation — recorded on ai.ended

Attribute	What it is	Values
ai.sc_verdict	What happened to the conversation. See AI Analytics for what each one means.	See the mapping below
ai.sc_end_reason	How the run finished	completed, stopped, handoff
ai.sc_ended_by_type	Who ended it, as distinct from how	ai, human, system
ai.sc_handoff_reason	Why it went to a person. Absent when it didn't.	completion, out_of_scope, escalation, timeout
ai.sc_duration_secs	How long the conversation lasted, in seconds. A number — averageable.	Any number
ai.sc_agent_name	Which agent handled it	Your agent names
ai.sc_trigger_source	What started the run	journey (a campaign, automation or inbound rule), user (a person), playground (testing)
ai.sc_category	What the conversation was about	Your own category labels
ai.sc_goal_achieved	Whether the conversation met its goals — one value for the whole run	true, false
ai.sc_num_goal_achieved	How many goals it met, for the whole run	Any number
ai.sc_message_count_lead / ai.sc_message_count_agent	Messages each side sent. Distinct from turn count — one turn can carry several lead messages.	Any number
ai.sc_resolution_kind	Whether a resolution was confirmed or inferred. Only meaningful when the verdict is a resolution.	confirmed, assumed
ai.sc_qualification_kind	The same, for qualification and disqualification	confirmed, assumed
ai.sc_verdict_reason	Present only when the verdict was not plainly derived	system_failure, backfill

The verdict values are not spelled the way Agent Studio displays them. Build filters with the left column:

Value in the picker	Shown in Agent Studio as
resolution	Resolution
procedure_handoff	Procedural handoff
qualification	Qualified
disqualification	Disqualified
escalated	Escalated
spam	Spam
abandoned	Abandoned
abandoned_no_outcome	No outcome
pending	Pending — a rare bookkeeping value on older sessions

Per goal — recorded on ai.goal

Attribute	What it is	Values
ai.sc_goal_name	Which goal this row is about	Your goal names
ai.sc_goal_met	Whether this goal was met in this conversation	true, false
ai.sc_goal_outcome	The judge's verdict on this goal	Whatever your goals produce — read the values in the picker
ai.sc_goal_score	The judge's score. A number.	Any number

ai.sc_goal_met and ai.sc_goal_achieved look interchangeable and are not. The first is per goal (on ai.goal); the second is per conversation (on ai.ended). Breaking down by ai.sc_goal_name only works on the per-goal event — the run-level rollup has no goal name to group by.

Per turn — recorded on ai.turn

Attribute	What it is	Values
ai.sc_turn_number	Which turn this was, counting from the start	Any number
ai.sc_input_tokens / ai.sc_output_tokens	Tokens in and out. Your cost signal.	Any number
ai.sc_latency_ms	How long the turn took, in milliseconds	Any number
ai.sc_tool_calls_count	Tool calls made in this turn	Any number
ai.sc_had_tool_failure	Whether any tool failed during this turn	true, false
ai.sc_tool_failures_count	How many failed in this turn	Any number

Per tool call — recorded on ai.tool_call

Attribute	What it is	Values
ai.sc_tool_name	Which tool was called	Your tool names
ai.sc_tool_type	What kind of tool	staged, read, mcp, kb (knowledge base), hook
ai.sc_result_status	Whether the call worked	ok, tool_error, dry_run, aborted
ai.sc_failure_domain	Whose fault it was. Kept separate from the reason on purpose: a model producing bad arguments is a different problem from a tool being down, and one combined "failure rate" hides both.	model, tool, infra
ai.sc_failure_reason	Why it failed	timeout, auth, rate_limited, unavailable, upstream_error, not_found, invalid_args, aborted, other
ai.sc_tool_latency_ms	How long the call took	Any number
ai.sc_checkpoint	Where in the run the call happened	turn, run_close

Counting tool failures: pick your grain deliberately. These three questions give three different numbers, and only one of them is usually what someone means:

• How many calls failed? → ai.tool_call, filter ai.sc_result_status is tool_error

• How many turns had a failure? → ai.turn, filter ai.sc_had_tool_failure is true

• How many leads were affected? → the same query, measurement Unique leads (see counting leads once)

Failures cluster, so the first number is reliably larger than the second. Counting conversations with a failure is not available yet: ai.sc_had_tool_failure is recorded on turns, not on ai.ended, and Unique leads de-duplicates by lead rather than by conversation.

What isn't offered, and why

Raw identifiers — the run id, the goal id — are deliberately absent from the pickers. Nobody breaks a chart down by a UUID, and a report grouped by one produces a bar per conversation. Use the names instead: ai.sc_agent_name, ai.sc_goal_name, ai.sc_tool_name.

For what the verdicts, goals, qualification and categories actually mean — and how to read them without drawing the wrong conclusion — see AI Analytics.

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Attributes

Attributes are what you filter and break down by. They fall into groups by the part of the product they come from.

Not every attribute is on every event — an attribute is only recorded when it's actually relevant to what happened. A message event knows about the channel and the sender; a lead.created event doesn't.

Rather than memorise this: pick your event first, and the attribute picker will only offer you attributes that event actually carries.

About the lead — lead.*

Recorded on every event about a lead.

Attribute	What it is	Values
lead.sc_status	Where the lead stands right now	active, inactive, expired
lead.sc_is_new	Whether the lead was created within 24 hours of this event — new lead vs returning	true, false
lead.sc_is_mock	Whether this is an internal or test lead. The Exclude internal and test leads switch uses this.	true, false
lead.sc_campaign	A campaign label, only if you set one. Store an attribute named sc_campaign on the lead and it lands here.	Whatever you send
lead.<your key>	Every attribute you store on a lead — lead.city, lead.tier, lead.product_interest	Whatever you send

On lead.attribute.set events you also get the pipeline fields:

Attribute	What it is	Values
lead.sc_stage	The stage the lead was moved to	Your own stage vocabulary
lead.sc_disposition	The disposition the lead was given	Your own disposition vocabulary

And on the events that describe a change, the before-and-after:

Attribute	On which event	Values
lead.sc_previous_status / lead.sc_new_status	lead.status.updated	active, inactive, expired
lead.sc_assignment_source	lead.assigned — how the assignment was made	api, user, support
lead.sc_source	lead.status.updated, lead.attribute.updated — who made the change	api, user, support, system

About the message — message.*

Attribute	What it is	Values
message.sc_event_sub_type	What kind of message it was	m.text, m.image, m.video, m.audio, m.file, m.location, sc.template, m.notice, sc.notice, m.emote
message.sc_is_template	Whether it was sent from a template	true, false
message.sc_reply_kind	How the lead replied — by tapping a button or list option, or by typing	interactive, free_flow
message.sc_success	Whether the message actually went out. false means it was blocked before reaching WhatsApp — working hours, moderation, a filtered word or an expired conversation window.	true, false
message.sc_event_type	Whether the message was visible in the chat or sent silently	m.room.message, sc.room.message.silent

Who and where — participant.* and room.*

Attribute	What it is	Values
participant.sc_type	Who sent it. One of the most useful attributes in the whole system.	lead (the customer), user (a human agent), app (a campaign, automation or bot)
room.sc_channel	Which channel the conversation is on	whatsapp, email, call, play, website

The template used — template.*

Attribute	What it is	Values
template.sc_name	The template's name	Your template names
template.sc_template_type	Whether it's a WhatsApp-approved template or an internal quick reply	waba, quick reply
template.sc_waba_template_category	The category Meta approved it under	marketing, utility, authentication, account_update, issue_resolution

The campaign or automation — journey.*

Attribute	What it is	Values
journey.sc_name	The name of the campaign, automation or inbound rule	Your own names
journey.sc_type	Which kind it was	campaign, automation, inbound
journey.sc_execution_status	Whether that attempt worked	success, fail
journey.sc_execution_failure_type	Why it failed. Absent when it succeeded.	GOVERNANCE_FAILED, MESSAGE_GOVERNANCE_FAILED, ACTIVE_CHATROOM_CONFLICT, SKIPPED, ACTION_FAILED, INTERNAL_ERROR

Not every failure is a fault. The two governance values mean the automation deliberately held back — a send limit or a governance rule stopped it — and SKIPPED usually means the lead was already in an AI conversation. Those are the system working as configured. ACTION_FAILED and INTERNAL_ERROR are the ones worth chasing.

journey.* is also carried on message events, so you can attribute messages back to the campaign or automation that produced them.

The conversation — session.*

Attribute	What it is	Values
session.sc_type	Who started it	inbound (the lead), outbound (you)
session.sc_duration_secs	How long it lasted, in seconds. A number — you can average it.	Any number
session.sc_end_reason	Why it closed — closed by the lead, by the agent, or timed out	See the picker

How the lead was routed — assignment_handler.*

Attribute	What it is	Values
assignment_handler.sc_name	The assignment rule that routed the lead to an agent. Absent when no rule was involved.	Your rule names

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Filter operators

Operator	What it does
is / is not	Exact match on a single value
is one of / is not one of	Match against a list — whatsapp or website
contains	Partial text match, useful for names like diwali_
>, <, ≥, ≤	Number comparisons, for attributes like session.sc_duration_secs
is set / is not set	Whether the attribute was recorded at all. Use this rather than comparing to an empty value.

"is not" excludes the blanks too.

journey.sc_type is not campaign matches only events that have a journey type and it isn't campaign. Events with no journey at all are not matched. If you want those as well, use is not set as a second condition.

Filters apply either to the whole report or to one row of it — Filters explains the difference, and splitting by two things at once is a worked case.

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