AI Tools & MarTech Practical insights
Calculate the real cost of AI marketing credits
Calculate AI marketing costs per accepted result by tracking subscriptions, credits, retries, unused allowances and the human work needed to finish.
AI credits are billing units, not a shared measure of productivity. A credit in one product may represent a different action from a credit elsewhere. Compare spending at the level of a finished marketing task, using actual usage records and the current terms for each account.
Map the billing event
For every recurring workflow, record which action consumes credits: a generated asset, completed agent action or another vendor-defined event. Check treatment of failed attempts, retries, included allowances, expiry and overages. HubSpot’s current agents page uses the name Agent Builder; product names and commercial packaging should be checked against the current account rather than an older Breeze comparison. [1]
Keep a task-level ledger
Assign a task identifier to each request and connect all related attempts to it. Record consumption, accepted output and review minutes. For example, one approved product email might require an initial draft, two revisions and a failed export. Counting only the final generation hides resources needed to reach acceptance. Separate experimentation from recurring production so learning costs remain visible.
Use a transparent cost calculation
Calculate total task cost as allocated subscription cost plus incremental usage charges plus human completion cost. Then divide the relevant period’s cost by accepted deliverables. In an illustrative month, €240 of allocated cost for 40 accepted assets equals €6 per accepted asset. This is arithmetic, not a quoted vendor price or an industry benchmark. Avoid charging included credits twice.
Test the busy-month scenario
Estimate what happens when demand doubles, approval takes longer or an allowance expires. Confirm who receives alerts and can cap spending. Keep the ledger’s assumptions beside the forecast. The useful purchasing question is whether the workflow remains affordable at realistic volume, including its review burden, rather than whether a large credit bundle sounds generous.
Sources and evidence
Sources checked on 4 October 2026. Proposed workflows and hypothetical examples are editorial analysis.