Measure

In depth

Measures are the backbone of data analysis and reporting. At their core, measures capture numeric insights about your business, such as total revenue, number of qualified leads, or average session duration. By aggregating raw data, measures answer critical questions like: How much did we sell? How many customers visited our site? What was our average order value?

In practice, a measure typically involves:

• Summing (e.g., total revenue)

• Averaging (e.g., average order value)

• Counting occurrences (e.g., number of new sign-ups)

• Calculating min/max values (e.g., lowest response time)

Unlike dimensions—attributes you group or filter by—measures quantify performance along those dimensions. For example, when you slice revenue (a measure) by region (a dimension), you uncover regional sales trends.

Pro tip

Make your dashboards and reports more intuitive by giving measures clear, descriptive names. For example, instead of “Value1,” use “Revenue per Employee” or “Net Profit”. Browse hundreds of metrics at MetricHQ.

Why Measures matters

Measures drive data-driven decisions. They turn raw numbers into insights that teams can act on. Without well-defined measures, you risk inconsistent calculations, misaligned reporting, and untrustworthy data.

Measures - In practice

Imagine you run an e-commerce store. You want to analyse sales performance by product category. You define:

1. A “Total sales” measure as the sum of order amounts.

2. A “Units sold” measure as the count of orders.

3. An “Average order value” measure as “Total sales” ÷ “Units sold”.

Next, you slice these measures by the “Product category” dimension in a dashboard, allowing you to quickly see which categories are driving the most revenue and which need attention.

Measures and PowerMetrics

In PowerMetrics, a measure is the singular and unique value assigned to a metric. For example, the count of leads or the sum of sales transactions.