In this work, we present an approach for optimizing targets for natural feature-based pose tracking such as used in Augmented Reality applications. Our contribution is an approach for locally optimizing a given tracking target instead of applying global optimizations, such as proposed in the literature. The local optimization together with visualized trackability rating leads to a tool to create high quality tracking targets.