We propose novel tree-structured quantization approaches for points on Grassmann and Stiefel manifolds. Such manifold quantizers find application, e.g., for channel state information quantization in limited feedback multiple-input multiple-output wireless communications. The proposed quantizers allow to trade-off quantization distortion for complexity by pruning the width of the quantization tree. We compare the rate-distortion performance and quantization complexity of the proposed quantizers to existing single stage and recursive multi stage quantizers, showing that the proposed methods lie in-between these two extremes.