Escalent launched BeSci x AI™ today, a proprietary, behavioral science (BeSci) model powered by AI that produces better behavior change strategies and takes human understanding at speed to the next level.
BeSci x AI helps businesses that are struggling to motivate behavior change. It’s a custom, AI-powered classification assistant that analyzes six dimensions of behavior—compared to other solutions that only analyze two dimensions—and pairs the powerful model with a philosophy Escalent calls “Human-Guided AI.”
“To win, brands need more than fast and slow thinking. Our model encompasses four additional dimensions that have been proven critical to inspiring behavioral change: psychological capability, physical capability, environmental opportunity, and social opportunity,” said Christopher Barnes, president of Escalent. “But to properly use the model, you need a human—an expert with deep industry knowledge who validates and enhances the research by advising brands how to turn findings into business impact.”
Using research documents such as interview guides, survey questionnaires, transcripts, summaries, and datasets, Escalent’s behavioral scientists use BeSci x AI to help clients:
“Consumers form hard-to-break habits. Ever try to get someone to eat healthier? Quit smoking? Follow doctor’s orders? Switch brands? It’s no small feat,” said Allie Dautrich, head of Escalent’s Behavioral Science practice. “If you’re in the business of motivating behavior change, you need to understand what drives it. Behavioral science is the key to unlocking that understanding, and Escalent just developed a one-two punch to get you there fast.”
The model also enables democratization and scaling, allowing Escalent to apply BeSci thinking to more projects and help clients working under quick-turn deadlines get deeper, more consistent and more reliable behavioral science insights. Multiple clients have already put the model to work for them, successfully dissecting motivators and inhibitors and designing solutions that produced better behavior change strategies.
Dautrich added, “When we first started building our model, AI’s accuracy was 60%. We spent months testing it by pitting it against our behavioral science experts, with both the model and human experts analyzing the same research data, including transcripts, open ends and reports as well as advertising and messaging materials. In 98% of cases, the AI-generated insights aligned with expert interpretations, confirming the model’s effective application of behavioral model classification with minimal deviation.”
