At the 2021 Turbo Choice Modeling Event, Peitz and Lerner introduced Bespoke CBC, where respondents choose which attributes matter to them, and only those appear in their CBC tasks. This personalization improved engagement, reduced dropout, and increased predictive validity�but was hard to program. We�ve developed a simple coding method that removes this barrier. Our next steps include empirically testing Bespoke CBC against other CBC types, examining attribute non-attendance, and assessing robustness when respondents misidentify key attributes.