Retail meat managers have many pricing tools to encourage product purchase, including the feature price, syndicate price, and the percent discount. Given seasonal demands and a large, diverse set of meat cuts, meat managers may form strategic pricing groups when choosing the feature-price, syndicate-price, and percent-discount levels. This research inductively determines these groups using a principal-components method and examines the role feature pricing plays in determining the volume sold and syndicate price. Seemingly unrelated regression (SUR) models are used to simultaneously estimate the impacts of featuring strategy decisions among cluster groups.