Validate & Calibrate
To gain trust for your modeling results, it’s important to know how valid are the results and how you calibrate them further.
Post modeling: MAPE and R²
The mean absolute percentage error (MAPE), also known as mean absolute percentage deviation (MAPD), is a measure of the prediction accuracy of a forecasting method in statistics.
R² or R-Squared is a statistical measure in a regression model that determines the proportion of variance in the dependent variable that can be explained by the independent variable. So, R² shows how well the data fit the regression model (the goodness of fit).
The Sellforte platform offers both of these metrics to validate the results
Lift tests
The best way to calibrate the model by yourself is to do lift test studies. You can do these lift test in the major advertising platforms. A lift test means that an ad will be shown to f.e. 90 % of the target audience and 10 % will be shown a blank ad to see how the control group behaves in relation to the other group. Do lift studies in:
- Google ad platform
- Meta ad platform
- TikTok ad platform
- Smartly ad platform
