Lifestyle analysis with IoT data acquired from coffee roaster for service development

This paper presents the lifestyle analyses of users via the appliance logs of our IoT coffee roasting service combined with a questionnaire survey on their lifestyles. We found that there is a difference in lifestyle trends between subscribed and non-subscribed users of the service. We also found that users showing a certain lifestyle have specific usage patterns of the roaster. In addition, we confirmed differences between the lifestyles of some users who quit the service and those who did not. Finally, we defined a service continuity index and discussed examples of measures to enhance service continuity by lifestyle analysis.