> For the complete documentation index, see [llms.txt](https://docs.onelens.cloud/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.onelens.cloud/observe-visibility-and-insights/unit-economics.md).

# Unit Economics

Unit Economics turns your cloud, AI and SaaS cost into a cost per unit that means something to your business, such as cost per customer, per product or per feature.

<figure><img src="https://3963693991-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FiyNGpqVYfmDF6qt7Lzar%2Fuploads%2FkaSudG84w7FP8S3XSD28%2Fimage.png?alt=media&amp;token=432532a8-42f5-4770-801f-c330fd4c7e15" alt=""><figcaption></figcaption></figure>

Go to **Observe → Unit Economics**. The page has three tabs.

| Tab              | What you do there                                                                                                                                      |
| ---------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ |
| Datasets         | Bring in the business data used to share out cost: your customers or products, how they map to cloud accounts, and usage numbers such as database size |
| Unit Cost Engine | Build an allocation rule. You combine datasets and cost on a canvas, step by step, into one final report                                               |
| Analytics        | Explore a published report: cost per unit over time, grouped and filtered the way you need                                                             |

### How it fits together

If you work this out in a spreadsheet today, you probably have a few raw sheets, some working sheets built with lookups, and one final sheet you send. Unit Economics follows the same shape:

1. **Datasets** hold the raw inputs.
2. In the **Unit Cost Engine**, contributors (your datasets and cost sources) feed intermediate tables, and the intermediate tables feed one final report.
3. You **publish** the report on a schedule, then read it in **Analytics**, on dashboards, and in workflow alerts.

### Example: database cost per customer

Say you want to share your database bill across customers by how much database space each one uses.

| Where            | What you set up                                                                                                                                                                                                  |
| ---------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Datasets         | An entity that lists your customers, and a metric with each customer's database size per month                                                                                                                   |
| Unit Cost Engine | Contributors: the customer entity, the database size metric, and your cloud cost. One intermediate table works out each customer's share of total database size. The final report applies that share to the cost |
| Analytics        | Cost per customer by month, shown next to each customer's database size                                                                                                                                          |

### Use the results elsewhere

**Dashboards.** When you add a widget, pick the **Unit Economics** module to show a report next to Cost 360, Kubernetes and Anomaly widgets.

<figure><img src="https://3963693991-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FiyNGpqVYfmDF6qt7Lzar%2Fuploads%2FHHfucXnr3TgaScVwlUXh%2Fimage.png?alt=media&amp;token=378db415-e82b-46b8-91d9-3c2b92f76f3d" alt=""><figcaption></figcaption></figure>

**Workflows.** You can set alerts that export unit economics reports automatically and flag runs that fail.


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