This article extends revenue management research into non-traditional hotel operating departments pertaining to convention hotel function space. This research evaluates utilization patterns of multiple convention hotel function spaces and identifies concurrent high-, medium- and low-utilization groupings of multiple convention spaces using k-means clustering. These high- and low-utilization function space pairings allow us to identify convention spaces to target for additional revenue management oversight. A Bayesian analysis of potential lift in revenue per available foot (RPAF) attributable to product bundling concludes the research linking hot and cold function spaces compatible with value based price packaging opportunities.