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Dimensions describe your entities. Use dimensions to segment your metrics into subgroups. For example, by adding a country dimension to a User entity, you can split results into subgroups based on the country of the user.
If the dimension table has a column with type timestamp, Confidence uses the dimension value from the time right before the user got exposed to the treatment.

Configuration

SQL Query

You need to enter the SQL that selects your dimensions. After you’ve entered your SQL, you can click Run Query. Confidence then executes your query with a limit to check that everything is in order and displays a few sample rows.

Entity

You need to specify which entity the dimensions belong to. You can split the result of metrics for this entity into subgroups based on the dimensions.

Dimensions

A dimension is a value that you can use to categorize an entity. Confidence supports static dimensions and dimensions that change over time. A typical example is splitting a “User” entity into segments based on a “Country” which is a static dimension, or “Used feature X the week before the experiment” which is a time-changing dimension. For time-changing dimensions, it’s important to use dimension values before the user got exposed to the treatment. This way, the treatment doesn’t influence the dimension value itself, which could invalidate the exploration. Confidence separates between static and time-changing dimensions by looking for a time-stamp column in the dimension table schema. Confidence considers all dimensions in a dimension table with a timestamp column as time-changing dimensions.
Confidence uses the dimension value from the time right before the user got exposed to the treatment. This way, it’s ensured that the dimension value is not influenced by the treatment itself.
For time-changing dimension, you need to specify what time window before exposure to use to fetch the dimension value. If there are multiple values in this window, Confidence uses the latest value.

NULL Values

Sometimes, there might be no value in the dimension table for all users that are exposed to an experiment. Add a NULL-value mapping to the dimension field to make the lack of value render in a meaningful way in the exploration page. You can configure the NULL-value mapping by entering a replacement in the Replace null with setting for a dimension.