This course provides a hands-on introduction to TURF (Total Unduplicated Reach and Frequency) analysis using Displayr. TURF is a portfolio-selection technique for finding the combination of products, flavors, or messages that reaches the largest possible audience with the least overlap in appeal — a common need in product line planning, message testing, and media selection, where simply picking the individually most popular items can actually leave reach on the table.

Using a real worked example throughout — a bubble gum manufacturer deciding which four flavors to sell from eleven candidates — learners will prepare and import binary "liked/chosen" data, set up and run a TURF analysis in Displayr, and work through its full range of inputs and constraints. From there, the course covers how to read and compare close portfolio results, build the two standard TURF visualizations (the Incrementality Plot and the Upset Plot), and turn the findings into a clear, defensible recommendation for stakeholders.