In statistics, SOV typically refers to the “sum of squares due to lack of fit” or “sum of squares of residuals.” This is a statistical term used in regression analysis to quantify the amount of variation in the data that is not explained by the regression model. It is calculated as the sum of the squared differences between the observed values and the predicted values of the regression model. The SOV is then compared to the “sum of squares due to regression” to determine the overall fit of the model. In marketing, however, SOV typically refers to “Share of Voice,” which measures a brand’s visibility and reach in a given market, as explained in this article.