Mean absolute error (MAE)
A validation metric that measures the average size of errors between a model's predictions and actual outcomes, without regard to direction.
More Measurement terms
Adjusted R-squared
A version of R-squared that accounts for the number of variables in a model, penalizing unnecessary complexity; useful for spotting when a model has more variables than its data can support.
Campaign-level granularity
The ability to measure marketing performance at the individual campaign level, rather than only at the channel level.
Confidence score
An indicator of how reliable a model's recommendation or output is.
Geo-testing
An incrementality testing method that compares marketing results across different geographic regions.
Holdout test
An incrementality testing method that withholds ads from a control group to measure lift.