Even though access to Bayesian methods is growing rapidly, the analytic expectation in many consulting contexts remains frequentist by default. In areas where the frequentist approach is entrenched there are two forces working against the adoption of Bayesian methods in the minds of domain experts. First, domain experts may prefer already published analytic strategies to allow “apples-to-apples” comparisons with current work. Domain experts are wary if novelty in results is partially attributed to domain innovation and partially due to the “new” Bayesian analysis. Second, domain experts worry that their audience (including journal reviewers, sponsors, and other stakeholders) will be less familiar with the interpretation of Bayesian inference, which will muddy waters of written communication and thus dampen impact. The suggestion to use Bayesian methods can hang uneasily unless the statistician’s case for Bayesian methods overcomes these valid concerns. In this talk we will discuss how technical ability, communication, and trust facilitate moving collaborative projects towards Bayesian analysis using bioinformatic and behavioral economic case studies.