Helping drivers improve their driving skills and become safer drivers is a problematic topic. Most drivers have a lacking self-assessment ability and consider themselves above average driving skills. This is believed to be related to the lack of continuous feedback after getting the driver’s license. This has led to initiatives to find alternative ways of coaching drivers toward better self-assessment and thereby toward safer driving. Chatbots and conversational interfaces has received increasing attention over the years and could be technologies that can solve these challenges. However, a major challenge to chatbots is that they are mostly implemented in a “one-size-fits-all” approach, and while personalization of the chatbot could solve that challenge, it ishard to achieve. In this study, personalized chatbot conversations that aim to coach drivers are examined. The aim is to create a guide that can help designers and practitioners with design decisions that needs to be considered when creating coaching chatbot conversations. The study was performed as a Wizard of Oz study, where attributes for personalization as well as coaching considerations were tested with users in two iterations to iteratively develop the guide. The findings of the study include the guide itself with its guidelines (see appendix 4), as well as insights on considerations required chatbot personalization and coaching. Regarding personalization, chatbot personality and level of control were identified as two attributes that were fit for adaptation. These can lead to social benefits as well as more tailored services to the users. For coaching, the use of follow-ups, feedback and the chatbot’s attitude are identified as necessary considerations when designing coaching chatbot conversations.