Business Metrics

Documentation Index

Fetch the complete documentation index at: https://docs.cloudcapital.co/llms.txt

Use this file to discover all available pages before exploring further.

A business metric is an external dataset you bring into Cloud Capital — customer count, active users, revenue, transactions, or any other number that correlates with your cloud spend. When a metric is connected to a Cost Layer, Cloud Capital uses the historical relationship between that metric and your actual costs to project how spend will move as the metric changes. This is the step that makes your forecast forward-looking. Instead of extrapolating from a cost trend, Cloud Capital projects from the thing that actually drives the cost: how many customers you expect to serve, how fast your user base is growing, how much revenue your finance team is already forecasting. Those inputs already exist in your business plan. Connecting them to your Cost Layers means both Finance and Engineering are working from the same numbers — and Cloud Capital has the signal it needs to size commitments against your real future rather than just your recent past.

---

​

Your business metrics

The Business Metrics page shows all metrics you have defined, with a row for each one. Each metric card contains two rows:

• Actuals — historical values you have already observed
• Forecast — projected values going forward, aligned with your business plan

Cloud Capital will interpolate missing values in both rows to handle gaps in the dataset. If your forecast extends further than the values you have provided, costs for that Cost Layer will fall back to a flat projection after the final metric value.

---

​

Adding a business metric

Click + New Business Metric, enter a name for the metric, and press Enter. The new metric appears inline with editable cells. Fill in the cells with your data. You do not need a value in every cell — Cloud Capital handles gaps automatically. A few practical tips:

• Name it after what it measures, not what it predicts. “Paying Customers” is better than “Production Cost Driver”.
• Actuals first. The more historical overlap between metric values and actual cost data, the stronger the correlation Cloud Capital can calculate.
• Forecast values come from your business plan. Use the same growth assumptions Finance is already using for budgeting.

​

What makes a good metric

A good business metric moves in step with the cost it is being connected to. If your production infrastructure cost grows as you add customers, then customer count is a good metric for your production Cost Layer. The stronger and more consistent that historical relationship, the more useful the metric becomes. Good metrics to consider:

• Customer count or active users (for production / customer-serving infrastructure)
• Monthly recurring revenue or transactions (for billing or payment processing workloads)
• Internal users or seat count (for internal tooling or collaboration infrastructure)
• Data volume or events processed (for data pipeline or analytics cost layers)

​

What makes a poor metric

Not every number correlates with every cost. A metric that moves independently of the cost layer it is connected to will not produce a meaningful forecast — it will inject noise rather than signal. Signs a metric may be a poor fit:

• The cost layer includes infrastructure that scales with engineering effort, not business volume (consider Engineering Initiatives instead)
• The metric is flat or nearly flat historically while costs vary significantly
• The metric tracks a business outcome that lags the actual cost driver by months
• The app shows Insufficient Data — meaning fewer than 3 months of overlapping metric and cost history exist (see correlation feedback below)

---

​

Connecting a metric to a Cost Layer

Business metrics take effect when you assign them to a Cost Layer’s Projection Type. Open the Projection panel for the relevant Cost Layer, select Metric - Auto, and choose your metric from the Associated Business Metric dropdown.

​

Correlation feedback in the dropdown

When you open the Associated Business Metric dropdown, Cloud Capital shows a correlation assessment next to each metric based on the historical relationship between that metric and this Cost Layer’s actual spend. The labels indicate how reliably the metric tracks with cost: Only metrics with sufficient historical data can use the Auto methodology. Newly created metrics will show as Insufficient Data until at least 3 months of actuals are in place.

​

After selecting a metric

Once you select a metric, Cloud Capital shows you two things before you commit: Correlation description — A plain-language summary of the inferred relationship, for example: “For every 1 unit Users increases, costs increase by $7.83.” This is the coefficient Cloud Capital has derived from the historical overlap of your metric and cost data. If it matches your intuition about how this cost scales, the metric is a good fit. If it feels off, consider whether a different metric or methodology is more appropriate. Projection Preview — A chart showing how the selected methodology will affect your cost forecast over the next 6 months, compared to the current projection. The scenario table beneath it shows the Baseline (your previous projection), the Current selection, and the Selected methodology side by side, with the month-by-month delta so you can see exactly how the forecast shifts before saving.

---

​

Correlation methodology options

With a metric selected, you can choose how Cloud Capital uses it: Auto — Cloud Capital infers the cost impact from the historical data, deriving the coefficient automatically. This is the default and works best when you have at least 3 months of overlapping data. The correlation description tells you what coefficient was calculated. Direct: 1:1 — Cost is projected to move in exact proportion to the metric. If your metric grows 10%, costs are projected to grow 10%. Use this when you do not yet have enough historical data for Auto, or when you have a strong operational reason to expect a direct proportional relationship.

---

​

Related pages