Unit Economics: Tying ML Costs to Business Value
Unit economics connect your ML spending to business outcomes. Instead of a total cloud bill, you see cost per prediction or per token. This helps product owners make pricing tradeoffs and engineers spot efficiency gains.
Unit economics tie your ML spending directly to business value, moving beyond a monolithic cloud bill. It frames costs in terms of business actions, like cost per transaction, per customer served, or per token generated. This allows product owners to understand feature cost drivers for smarter pricing and roadmap decisions, while engineers can spot efficiency gains. The biggest mistake is focusing only on resource metrics (cost per GPU) without connecting them to business metrics (cost per active user).
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