Supporter data is the engine driving nonprofit fundraising efforts, empowering organizations to identify key donor groups and formulate messages that resonate with their intended audiences. But this supporter data can…
Most arts nonprofits face a similar challenge: modify their programming and marketing efforts in order to manage aging audiences, technological disruptions, and changes in cultural consumption. Lyric Opera of Chicago is no different. From creating a new state-of-the-art website and investing in content creation, Lyric Opera has taken steps to improve their online presence and build loyalty among their core audience. For their next act, they wanted to take it a step further and expand their audience with the power and precision of data science. That’s when they turned to Civis Analytics with what might seem like a simple question:
How can Lyric Opera find and acquire new ticket holders?
First, Lyric Opera needed to better understand their ticket buyers before they could find and acquire new patrons. To accomplish this, Lyric Opera enlisted Civis to help identify the demographics and behavioral characteristics of current ticket buyers using data science.
Using Civis’ proprietary matching algorithms, we could match their list of current ticket buyers to the Civis national database of 220+ million Americans and uncover some surprising predictors of potential ticket buyers. While a typical ticket buyer is more likely to be a woman, 50 years or older, and from a high-income household than an average Chicagoan, the single most powerful predictor was the likelihood of voting in an election.
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.
Executing a true data-driven effort, Lyric Opera ran two campaigns—one based on the Civis targets and another based on prospects they could have sourced through a traditional market segmentation. Through the individualized approach, the targets we identified converted to ticket buyers at 3.7 times the rate of the other prospects.
Taking the findings one step further, we mapped the likely ticket buyers to provide a better look at where they live. Lyric Opera can now make better-informed decisions should they want to place out-of-home advertisements—meeting their target buyers where they are!