Matching is a mysterious phenomenon which has recently been observed for several parametrised families of interval maps in the deterministic and random settings. It is the property that for each critical point the (random) orbits of the left and right limit merge after some finite number of steps, and that the (expected value of the) derivatives of both orbits are also equal at that time; this assures the stability of this phenomenon under small perturbations of the parameter. Since most of the dynamical behaviour of systems are encoded in the possible trajectories of the critical points, knowledge on when and how matching occurs can help in finding explicit expression for the natural invariant measure. Once such a measure is found, one is able to obtain essential information regarding the system, such as the frequency the orbits enter a specific region, the entropy, the Lyapunov exponents, mixing rates etc., and to make comparisons as the parameter varies. There are many theorems that asserts the existence of such invariant measures, but there are few results that give a recipe for an explicit formula, which is essential in describing the exact asymptotic behaviour. We propose a new methodology to construct such measures and to uncover their properties and behaviour under parametrised perturbations. Our aim is to give a systematic way of analysing such systems and to provide a new approach, with the help of matching, to relate non-isomorphic systems that exhibit similar matching phenomena and to extract information from one system to the other.