A current-period view of your AI margins.
This example shows how customer revenue and attributed AI usage become a focused profitability report. Every value below is sample data, not a customer result.
Know the overall margin—and the accounts changing it.
Aggregate performance is the starting point. Customer-level attribution shows whether growth is healthy or being subsidised by a few expensive accounts.
The accounts that deserve attention first.
Sort by AI gross margin to separate healthy growth from customers whose usage, plan, or product path needs intervention.
| Customer | Plan | Revenue | AI cost | AI gross profit | AI gross margin | Status |
|---|---|---|---|---|---|---|
| Northstar | Scale | €199 | €42 | €157 | 78.9% | Healthy |
| Acme Ltd | Growth | €49 | €38 | €11 | 22.4% | At risk |
| Beta Labs | Starter | €29 | €34 | −€5 | −17.2% | Unprofitable |
Turn the report into a short operating list.
Keep each next step attached to the customer and usage evidence behind it so the operating decision stays clear.
Review Beta Labs now
AI cost exceeds subscription revenue. Inspect document-analysis usage and decide whether to cap, reprice, or optimise it.
Review Acme at 25%
Use 25% AI gross margin as an operating floor and revisit the account when its current-period margin approaches it.
Protect the Scale pattern
Northstar combines high usage with healthy margin. Use that account as evidence when refining the next pricing plan.
Illustrative sample only. Actual calculations depend on the AI usage and revenue you attribute to each customer.
Know which customers are profitable.
No credit card. Attribute real AI usage and find the accounts putting your margin at risk.