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Query Examples

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llms.txt / llms-full.txt

Discovery

Find what events exist and how frequently they fire.

Top event types

* | last 30d | count by event_type | top 20

Returns the 20 most common event types by count over the last 30 days. Run this first in any new project.

Full event inventory

* | last 90d | count by event_type | sort event_type asc | limit 10000

Alphabetical list of all event types with counts. Use limit 10000 to avoid truncation on projects with many event types.

Events today

* | today | count by event_type | top 10

Quick check of what is firing right now.

Daily event count

<signup_event> | last 7d | count by day

One row per day with the count of the specified event. Default sort is by time ascending.

Weekly unique users

<signup_event> | last 12w | unique distinct_id by week

Unique users (stitched identity) who triggered the event, grouped by week.

Platform breakdown

* | last 30d | count by _platform

Total events split by web, android, ios. Add | top 10 if there are many values.

Filtered count with multiple conditions

<core_event> | where _platform = "web" AND _browser = "Chrome" | last 30d | count by day

AND logic within a single where. Multiple | where clauses are also AND-ed.

Funnels

Basic conversion funnel

funnel <signup_event> -> <activation_event> -> <purchase_event> | last 30d

Returns step number and user count for each step. Step 1 = entered funnel, step 2 = completed second event, etc. Measures drop-off between steps.

Funnel with platform breakout

funnel <signup_event> -> <activation_event> -> <purchase_event> | last 30d | by _platform

Same funnel, segmented by platform. Each platform gets its own set of step counts.

Funnel with completion window

funnel <signup_event> -> <first_value_event> -> <upgrade_event> | last 90d | window 7d

Only counts users who completed the funnel within 7 days. Default window is 30 days.

Retention

Weekly cohort retention

retention <signup_event> | last 90d

Groups users into weekly cohorts by their first <signup_event>. Shows how many return in weeks 1 through 12. Default granularity: week.

Retention with specific return event

retention <signup_event> returning <core_usage_event> | last 90d

Same cohort grouping, but only counts returns where the user did the specified event (not just any event).

Monthly retention

retention <signup_event> | last 6m | by month

Monthly cohorts instead of weekly. Returns 6 monthly cohorts with up to 6 periods each.

User analysis

Single user timeline

user "alice@acme.org" | last 90d | list

All events for this user in reverse chronological order. Matches on stitched distinct_id, so anonymous events from before identification are included.

User event breakdown

user "alice@acme.org" | last 30d | count by event_type

What event types did this user trigger, and how many times?

User directory listing

users | where email_domain = "acme.org" | list

List all user profiles from the acme.org domain. Returns user_id, email, email_domain, first_seen, last_seen, and custom properties.

User count by plan

users | count by user.plan | top 10

How many users on each plan? Requires plan to be set via identify().

B2B segmentation

Company activity

* | where user.email_domain = "acme.org" | last 30d | count by event_type

All events from users at acme.org, broken down by type. Requires email to be set via identify().

Top companies by active users

* | last 12w | count by user.email_domain | sort count desc | top 20

Which companies have the most event volume? Proxy for engagement.

Per-user activity within a company

<core_usage_event> | where user.email_domain = "acme.org" | last 12w | count by week, user.email

Weekly usage per user at a specific company. Useful for identifying champions and inactive seats.

Enterprise plan users over time

* | where user.plan = "enterprise" | last 12w | unique distinct_id by week

Weekly unique enterprise-plan users. Track growth or contraction of the enterprise segment.

Revenue and metrics

Weekly revenue

<purchase_event> | last 12w | sum event_properties.amount by week

Total revenue per week. Requires amount in event_properties on purchase events.

Conversion rate via formula

formula count(<purchase_event>) / count(<signup_event>) | last 30d

Single number: what fraction of signups convert to purchase? Output is a decimal (e.g. 0.12 = 12%).

Weekly conversion rate trend

formula count(<purchase_event>) / count(<signup_event>) | last 12w | by week

Same ratio as a weekly time series. Track whether conversion is improving.

Average order value

<purchase_event> | last 30d | avg event_properties.amount

Mean purchase amount. Use median for a distribution-resistant measure:

<purchase_event> | last 30d | median event_properties.amount

Sessions and paths

Daily session metrics

sessions | last 7d

Default output: session count, average duration (seconds), average events per session, grouped by day.

sessions | last 12w | count by week

Session count per week. Track engagement trends.

User paths from an event

paths from <signup_event> | last 30d

Most common event sequences after signup. Returns arrays of event types with user counts. Default depth: 5 steps, default limit: 20 paths.

Paths leading to conversion

paths to <purchase_event> | last 30d | depth 8

What do users do before purchasing? 8-step paths leading up to the purchase event.

Paths with more results

paths from <onboarding_start> | last 30d | depth 6 | limit 50

Increase depth and result count for broader exploration.