# Understanding metrics

A metric is a defined, aggregated field from your data.

**Metric = metric dimension(s) + aggregation method**

Using different aggregation methods on a selected dimension in your data can produce different types of Analyses.

For example:

**average order value**- using an average calculation as the Aggregation Method on the`order_value`

dimension**total revenue**- using a sum calculation as the Aggregation Method on the`order_value`

dimension

In the following example, the `order_value`

dimension has been chosen as the metric dimension to be analyzed. This dimension can be used to define different Metrics, using various aggregation methods.

Note that in this example, the AVG of *order_value* is the average order value, which is the KPI that is being analyzed by Sisu with this defined Metric IF “Average” is selected as the calculation type Aggregation Method. If “Sum” is selected as the Aggregation Method for the Analysis, Sisu will perform the analysis based on the total order value (“SUM of order_value).

With different combinations of Metric Dimension and Aggregation Methods, you can perform a variety of General Performance Analyses. When you add “comparison” to an Analysis, you can perform useful Time Comparison and Group Comparison Analyses.

## Metric types

Sisu supports multiple metric types:

**Sum***(numeric)*- sum of a single metric dimension*(e.g., total revenue)***Count***(numeric)*- count of the rows of a single metric dimension(e.g., number of orders)**Rate***(numeric)*- a metric dimension divided by a denominator dimension*(e.g., lead conversion rate)***Average***(numeric)*- average of a single metric dimension*(e.g., average order value)***Weighted average***(numeric)*- average of a metric dimension weighted by a weight dimension*(e.g., price per share)***Weighted sum***(numeric)*- sum of a metric dimension weighted by a weight dimension*(e.g., price per share)***Rate***(categoric)*- rate of a matching condition in a metric dimension*(e.g., churn rate)***Count***(categoric)*- count of a matching condition in a metric dimension*(e.g., number of churns)*

The following charts provide further details about each Metric type.

Average | Weighted Average | |
---|---|---|

Metric Calculation | sum(Metric dimension) / count(row) | sum(Metric dimension*weight dimension) / sum(weight dimension) |

Sample Equation | (30+90+40+120)/4 | ( 302 + 904 + 4012.5 + 1202 ) / (2+4+12.5+2) |

Sample Result | 65 | 56.6 |

Categorical Rate | |
---|---|

Metric Calculation | count(condition) / n |

Sample Equation | 3 recurring orders out of 4 |

Sample Result | 75% |

# How metrics are used

Sisu directly connects to data warehouses. A metric can be built one of two ways:

- On top of an
**existing table**in the data warehouse - Through a
**custom query**used to define metrics using the query editor. Any member of your organization can then investigate these metrics without needing to create or review the same SQL code every time.

With a metric defined, Sisu can run three types of analyses:

- General Performance Analysis
- Time Comparison Analysis
- Group Comparison Analysis