THE SOLUTION
Finding the model patron
With a solid understanding of their current ticket-holders, Lyric Opera could now use look-alike models to find their top prospects. Our algorithms take into account hundreds of dimensions at once—accounting for the important differences between arts donors and other nonprofit donors, and even the distinction between opera fanatics and museum-goers.
Based on those dimensions, the algorithms determined which features are most predictive of whether a person would purchase a ticket, calculating a prospect score for every Chicagoan. Lyric Opera could then prioritize the set of individuals who were most likely to buy a ticket.