AI use cases and applications
Business Metrics for Generative AI
Model accuracy alone doesn't show value. Business metrics tie a generative AI application to outcomes and ROI, and the right metric depends on the use case.
| Metric | What it tells you | Typical use case |
|---|---|---|
| User satisfaction | How users rate the generated content or recommendations | Customer support, e-commerce sites |
| Average revenue per user (ARPU) | Revenue generated per user | Personalized recommendations and upselling |
| Cross-domain performance | How well the model handles different domains or tasks | Assistants used across departments |
| Conversion rate | Share of users who complete a desired action, such as a purchase | Marketing content, product recommendations |
| Efficiency | Time, cost, or resources saved | Automating document or content work |
The full notes captured only the first slide (user satisfaction). The other metrics follow the AWS course.
For customer support, the best measure of success is customer satisfaction, not revenue metrics.