ltx-product-daily-report

name	ltx-product-daily-report
description	Generate LTX Studio product daily report with revenue, usage by segment (Enterprise, Pilot, Paying Non-Enterprise, Free), and DoD/DOW-avg comparisons. Use when: daily product standup, executive reporting, or when asked for 'yesterday's product numbers'.
tags	["reporting","daily-metrics","ltxstudio","product"]
compatibility	["bq CLI installed and authenticated","GCP project access (ltx-dwh-explore for query execution)"]
metadata	{"author":"dbeer","version":"2.0","created":"2026-03-13"}

LTX Product Daily Report

Overview

Daily snapshot of LTX Studio product health: revenue by segment, usage metrics (active users, generations, tokens, downloads), with day-over-day and day-of-week average comparisons.

Slack channel: #ltx-product-auto-report

Instructions

Step 1: Run the Query

bq --project_id=ltx-dwh-explore query --use_legacy_sql=false --format=pretty "$(cat queries/product_segment_metrics.sql)"

The query returns two result sets:

• Part 1 (lines 1-277): Segment metrics — usage + revenue per segment with DoD% and DOW-avg%
• Part 2 (lines 282+): Sales funnel — leads, meetings, opportunities, pipeline

Step 2: Format Output

Format per references/report-template.md. Key columns: segment, active_users, image_generations, video_generations, downloads, token_consumption, active_orgs, net_revenue, gross_revenue, plus *_dod_pct and *_dow_avg_pct comparison columns.

Step 3: Highlight Anomalies

Flag any metric with >50% DoD or DOW-avg deviation.

Context & References

Shared Knowledge (Read First)

• shared/product-context.md — LTX Studio overview, user types, business model

Query Files

• queries/product_segment_metrics.sql — Main product report query

Reference Materials

• references/report-template.md — Output formatting example

Constraints

DO NOT

• Run queries without --project_id=ltx-dwh-explore
• Forget time_granularity = 'day' filter on revenue table
• Count video generations without action_category = 'generations' filter
• Use is_enterprise_user flag — use org-based enterprise logic
• Skip partition pruning (use date(action_ts) >= ...)

DO

• Use date(action_ts) for partition pruning on usage table
• Validate Total row = sum of all segments (sanity check)
• Flag anomalies > 50% DoD or DOW-avg deviation
• Use SAFE_DIVIDE for all percentage calculations
• Report both press count AND output count for generations

Examples

User: "Product daily report for yesterday"
User: "How did product metrics look yesterday?"
User: "Run the product report"