Our unique research approach determines which emotional motivators are most powerfully associated with audience behavior and customer value and the degree to which connecting to those motivators influences behavior, both in absolute terms and relative to more commonly measured drivers of behavior.

Designed to be representative of the United States population in terms of demographics, our Predictive Motivations® provide arts and cultural organizations with high confidence insights that deliver not just statistically significant results but actionable strategies to attain sustainable growth.

Data reliability has been validated in multiple ways. First, more than two million surveys have been conducted and behavioral data has been appended extensively, including CRM and aggregated behavioral data. Modeled relationships among motivations and behaviors have been validated across large sample sizes, over periods of contiguous years, across 30+ industries and 500+ distinct brands. Second, Predictive Motivations have been activated upon extensively by numerous blue chip companies through the implementation of strategies and tactics informed by the research such as advertising, integrated marketing, and customer experience innovation. Measured by a lift in predicted behaviors and associated revenues, results have been consistent and significant, including evidence that emotionally connected customers are 52% more valuable, on average, than those who are merely highly satisfied.

Our research utilizes a mixed methods approach that incorporates quantitative and qualitative techniques such as lexical analysis, ethnography, surveys, in-depth interviews, behavioral analysis, statistical modeling, big data aggregation, and predictive analytics. In addition, large sample sizes mitigate error rates and empirical models are used to identify unusual variance in results (such as due to biased respondents). Importantly, our experience in matching reported intentions to actual behaviors has refuted the risk of unreliable data and models.