In the context of stationary point processes measurements are usually made from a time point chosen at random or from an occurrence chosen at random. That is, either the stationary distribution P or its Palm distribution P° is the ruling probability measure. In this paper an approach is presented to bridge the gap between these distributions. We consider probability measures which give exactly the same events zero probability as P°, having simple relations withP. Relations betweenPand P° are derived with these intermediate measures as bridges. With the resulting Radon‐Nikodym densities several well‐known results can be proved easily. New results are derived. As a corollary of cross ergodic theorems a conditional version of the well‐known inversion formula is proved. Several approximations of P° are considered, for instance the local characterization ofPoas a limit of conditional probability measuresP°N The total variation distance betweenP°and P1can be expressed in terms of the P‐distribution function of the forward re