The singular values squared of the random matrix product Y = GrG r−1 · · · G 1 (G 0 + A), where each G j is a rectangular standard complex Gaussian matrix while A is non-random, are shown to be a determinantal point process with correlation kernel given by a double contour integral. When all but finitely many eigenvalues of A * A are equal to bN , the kernel is shown to admit a well-defined hard edge scaling, in which case a critical value is established and a phase transition phenomenon is observed. More specifically, the limiting kernel in the subcritical regime of 0 < b < 1 is independent of b, and is in fact the same as that known for the case b = 0 due to Kuijlaars and Zhang. The critical regime of b = 1 allows for a double scaling limit by choosing b = (1 − τ / √ N ) −1 , and for this the critical kernel and outlier phenomenon are established. In the simplest case r = 0, which is closely related to nonintersecting squared Bessel paths, a distribution corresponding to the finite shifted mean LUE is proven to be the scaling limit in the supercritical regime of b > 1 with two distinct scaling rates. Similar results also hold true for the random matrix product TrT r−1 · · · T 1 (G 0 +A), with each T j being a truncated unitary matrix.