App reviews can provide valuable information about user needs but analyzing them manually is challenging due to their large quantity and noisy nature. To overcome this problem, a variety of app review mining techniques have been proposed. So far, however, research in this area has paid little attention to the software engineering use cases of the mining techniques. This limits the understanding of their usefulness, applications and desired future developments. We address this problem by elaborating a reference model relating app review mining techniques to specific software engineering activities. In this paper, we present a unified description of software engineering use cases for mining app reviews and define a reference architecture realizing these use cases through a combination of natural language processing and data mining techniques. The use cases provide a novel systematic exposition of the envisioned applications and benefits of app review mining for software engineers. The reference architecture synthesises the diversity of research to realise these benefits and provide a general framework guiding the development and evaluation of future research and tools.