To date, little attention has been paid to the temporal nature of campaigns as they respond to events or react to the different stages of a political election -- what we define as strategic temporality. This article seeks to remedy this lack of research by examining campaign Facebook and Twitter messaging shifts during the 2016 U.S. Presidential general election. We used supervised machine-learning techniques to predict the types of messages that campaigns employed via social media and analyzed time-series data to identify messaging shifts over the course of the general election. We also examined how social media platforms and candidates' party affiliation shape campaign messaging. Results suggest differences exist in the types of campaign messages produced on different platforms during the general election. As election day drew closer, campaigns generated more calls-to-action and informative messages on both Facebook and Twitter. This trend existed in advocacy campaign messages as well, but only on Twitter. Both advocacy and attack tweets were posted more frequently around Presidential and Vice-Presidential debate dates.