We introduce targeted property-based testing, an enhanced form of property-based testing that aims to make the input generation component of a property-based testing tool guided by a search strategy rather than being completely random. Thus, this testing technique combines the advantages of both search-based and property-based testing. We demonstrate the technique with the framework we have built, called Target, and show its effectiveness on three case studies. The first of them demonstrates how Target can employ simulated annealing to generate sensor network topologies that form configurations with high energy consumption. The second case study shows how the generation of routing trees for a wireless network equipped with directional antennas can be guided to fulfill different energy metrics. The third case study employs Target to test the noninterference property of information-flow control abstract machine designs, and compares it with a sophisticated hand-written generator for programs of these abstract machines.