The identification of material parameters is a required process for industrial applications to characterize the used material models. This methods based on the comparison of experimental data points and a response curve via a chosen FEM simulation. While standard procedures to identify these parameters are often established by using the Gauss-Newton algorithm, improvements are still possible. Problems like simultaneous identification for multiple data sets and the disadvantages of a pure L 2-error function lead to new models. Additionally, often the shape of the simulation curve and its position in a certain corridor is more important. The choice of such a corridor can have multiple reasons like statistical deviations, side conditions based on theoretical identifications or prescribed values. To model such a corridor, a new error function has to be defined. This function is built via different parabolic function parts and is named “bi-parabolic target function”. The properties and possibilities of the new formulation, tested with rubber experimental data, are examined. After a symmetrical approach, the advantages of an asymmetrical approach will be presented. As a second part, the aspects of the distance calculation, which is used to measure differences between the simulation curve and experimental data points will be discussed. The common approach is a perpendicular axis distance which is based on the distinction of action and reaction values. A more natural approach is the perpendicular distance between the experimental data points and the simulation curve. An example identification will be discussed based on the distances.