A significant cardiovascular health risk is insufficient physical activity. The World Health Organization recommends 150 minutes of strenuous physical activity every week. Inadequate physical activity increases the risk of chronic diseases and other health conditions like cholesterol and obesity. This thesis researches the role of data monitoring as a persuasion strategy in monitoring a user’s progress in their journey to becoming more physically active and how it can be leveraged to decrease the risk of cardiovascular diseases. Specifically, the focus of the thesis is to determine the effectiveness of expert-generated tailored messages to motivate a user in their physical activity behaviour. We designed the content of the messages by adapting an existing ontology for tailoring motivational messages in the context of physical activity. Messages were then generated by experts through a scenario-based feedback generation process, where the scenarios were tailored to a user’s mood, self-efficacy and progress. The design of these tailored messages was tested against generic messages to determine which type of message was more motivating to the user. An experiment was conducted by recruiting crowd workers who were asked to rate the motivational levels of the two message types with respect to a given scenario. The results of the experiment supported the initial hypothesis that messages tailored to mood, self-efficacy and progress are more motivating than generic messages. Additionally, we have shown a systematic and reproducible way to obtain motivating messages. We have also provided a dataset of motivational messages that can be used during various stages of a user’s physical activity intervention, along with a set of scenarios representing different levels of a user’s state (mood, self-efficacy and progress).