Product analytics
See revenue, AI costs and X mentions
Connect your data to understand revenue and AI costs. Monitor X mentions with just your website.
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AI unit economics guides for AI products
Learn how to measure revenue, track AI costs and read your results. Each guide explains the data you need and what it can tell you.
First principles
Practical questions every AI product eventually asks.
AI discovery
What does AI visibility actually measure?
Keep recommendations, citations, crawler requests, referral visits, and revenue as separate observed signals.
Decision guide
LLM observability vs AI profit analytics
Use traces to debug model behavior and customer economics to debug the business.
Track revenue and AI usage costs in one dashboard
Join customer payments and AI usage cost for the same people and period, and keep unmatched cost unallocated.
What is AI unit economics?
Define the unit, the revenue, the variable model cost, and the contribution profit.
How do I calculate AI contribution margin?
Keep the numerator, denominator, time window, and customer population aligned.
What is AI cost per user?
Price cached and uncached tokens, failures, retries, and streaming usage correctly.
Why is token cost not profit?
Cost needs observed revenue and a trustworthy identity link before it becomes customer profit.
Gross margin or AI contribution margin?
Use each metric for the decision it can actually support.
Which customers are losing money?
Join payer identity and model usage without spreading unknown cost across every account.
Server recipe
OpenAI Responses streaming cost by account
Measure final streamed usage by account without collecting prompts or responses.
Server recipe
Anthropic cache read and write cost by customer
Keep cache reads, five-minute writes, and one-hour writes separate by customer.
Methodology
How Grow or Die versions model prices
Audit the effective price, billing mode, and fail-closed boundary behind every cost.
Revenue recipe
Link a Stripe customer to AI usage without email joins
Join Stripe customer revenue to AI usage through a stable internal account—not email.
Revenue recipe
Link Lemon Squeezy revenue to AI usage
Connect store-scoped Lemon orders, refunds, and AI usage without guessing identity.
Practical methodology
OpenAI cost per Stripe customer: a SQL reconciliation recipe
Reconcile OpenAI usage and Stripe revenue by customer with tested SQL. Keep refunds, mixed currencies, duplicate joins and unknown costs explicit.
Practical methodology
Verify a Grow or Die native SDK installation
Verify browser visits, server AI usage, payer identity, and data boundaries with a practical Grow or Die SDK checklist. GA4 is optional, not a prerequisite.
Practical methodology
From AI citations to revenue: an evidence checklist
Separate AI citations, crawler requests, human referrals, and observed revenue with a practical evidence checklist and a reproducible reporting example.
Practical methodology
Budget AI free trials before scaling acquisition
Calculate the AI usage budget of a free-trial cohort with activation, conversion, paid contribution, and incomplete-cost boundaries made explicit.
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