Personal Comfort Systems (PCS) provide individual occupants local heating and cooling to meet their comfort needs without affecting others in the same space. It saves energy by relaxing ambient temperature requirements for the HVAC system. Aside from these benefits, PCS offers a wealth of data that can describe how individuals interact with heating/cooling devices in their own environment. Recently developed Internet-connected PCS chairs have unlocked this opportunity by generating continuous streams of heating and cooling usage data, along with occupancy status and environmental measurements via embedded sensors. The data allow individuals' comfort and behavior to be learned, and can inform centralized systems to provide ‘just the right’ amount of conditioning to meet occupant needs. In summer 2016, we carried out a study with PCS chairs involving 37 occupants in an office building in California. During the study period, we collected >5 million chair usage data-points and 4500 occupant survey responses, as well as continuous measurements of environmental and HVAC system conditions. The data analysis shows that (1) local temperatures experienced by individual occupants vary quite widely across different parts of the building, even within the same thermal zone; (2) occupants often have different thermal preferences even under the same thermal conditions; (3) PCS control behavior can dynamically describe individuals' thermal preferences; (4) PCS chairs produce much higher comfort satisfaction (96%) than typically achieved in buildings. We conclude that PCS not only provide personalized comfort solutions but also offer individualized feedback that can improve comfort analytics and control decisions in buildings.