Measure

In depth

Measures form 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 let you answer critical questions: How much did we sell? How many customers visited? What’s our average order value?

In practice, a measure typically involves:

• Summation (e.g. Total revenue)

• Averaging (e.g. Average order value)

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

• Min/max calculations (e.g. Lowest response time)

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

Pro tip

Give measures clear, descriptive names. Instead of “Value1,” use “Revenue per Employee” or “Net Profit”. Clear names make your dashboards and reports more intuitive. Browse hundreds of metrics at MetricHQ.

Why it 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 lost trust in your 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. A “Average order value” measure as Total sales ÷ Units sold.

Next, you slice these measures by the “Product category” dimension in a dashboard. Now you see which categories drive the most revenue and which need attention.

Product-specific notes

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