Frequently Asked Questions

Behavioralize is a behavioral science consultancy helping pharma, biotech, and life sciences organizations understand and change real-world decision-making. Working across Medical Affairs, Insights, Marketing, and Sales, the work applies cognitive and decision science to identify the misperceptions, decision drivers, and contextual barriers shaping how healthcare providers and patients actually behave. Engagements span more than 16 therapeutic areas, from oncology and rare disease to immunology and infectious disease.

Traditional market research explains what people say or do. Behavioralize focuses on why decisions break down and what must change for behavior to shift. The work uncovers cognitive biases, emotional drivers, habit structures, and contextual barriers that conventional surveys and focus groups are not designed to capture — and delivers a clear map of what to change, where to focus, and how to measure impact.

What distinguishes Behavioralize is methodological depth and genuine academic pedigree. The firm was founded and is led by Jason Riis, a former Wharton and HBS professor with a PhD in cognitive psychology and a postdoc under the late Daniel Kahneman, one of the founders of behavioral science. Every team member holds an advanced degree in behavioral science. The work is grounded in peer-reviewed cognitive and decision science — not behavioral science insight layered on standard research. Behavioralize is known for reconstruction interviewing, Experience Sampling Methodology (ESM), systematic behavioral diagnosis, and a strategic partnership model in which it functions as a thinking partner at the strategy level, not just a research executor.

Behavioral consulting is most valuable when the challenge is behavior change rather than awareness — when adoption lags, messaging fails in the field despite testing well, or HCPs agree with a product's value but do not prescribe it. It is especially useful in launch strategy, where behavioral risks like misperceived risk-benefit profiles, entrenched prescribing habits, and identity-driven resistance are diagnosable before launch but rarely surfaced by conventional research.

Behavioralize approaches behavior change through a diagnostic lens — identifying the specific cognitive, emotional, and contextual forces causing a behavior gap before designing any intervention. Rather than applying general behavioral principles, the work starts by understanding exactly why a behavior is or is not happening, then builds strategy around the actual mechanisms in play. The result is interventions that are more precise and more likely to produce real-world change.

The Misperceptions and Inactions framework is Behavioralize's core diagnostic lens. Misperceptions are systematic gaps between reality and how people understand it — including inaccurate risk assessments, flawed mental models, or miscalibrated beliefs about a therapy. Inactions are failures to act despite intent, driven by habit, cognitive load, or contextual friction. Identifying which force is operating allows teams to design interventions that target the actual cause of the behavior gap.

Decision-Driven Analytics (DDA) is Behavioralize's approach to designing research backward from the decisions that matter most. Rather than moving from a research question toward insight, DDA starts with the concrete decisions a client must make — which segments to prioritize, which barriers to address, which messages to invest in — and designs research to reduce ambiguity around those specific choices. The result is research that is actionable by construction.

Behavioralize uses a range of proprietary and established behavioral research methods selected for the specific decision context. Core methods include reconstruction interviewing, which surfaces real HCP decision-making through memory-based techniques; Experience Sampling Methodology (ESM), which captures behavior in real time; and behavioral segmentation, which groups HCPs or patients by decision patterns and psychological drivers. Quantitative and qualitative approaches are often combined, with AI used to scale collection and pattern detection.

Reconstruction interviewing accesses actual HCP decision-making through memory-based techniques rather than abstract self-report. Rather than asking physicians how they generally approach treatment decisions, it walks them through specific past clinical encounters — surfacing the real cognitive sequence, contextual pressures, and decision shortcuts that shaped what happened. The result is insight grounded in what clinicians actually do, not what they say they do.

Experience Sampling Methodology (ESM) captures HCP cognition and behavior in real time — at or near the moment decisions are being made — rather than through retrospective recall. Participants are prompted at relevant moments in their clinical day to record thoughts, context, and decision states as they occur. This produces behavioral data far less subject to memory distortion, rationalization, or social desirability bias than traditional methods.

Behavioral segmentation groups healthcare providers or patients based on the decision patterns, psychological drivers, mental models, and contextual constraints that actually predict behavior — not just specialty, geography, or stated attitudes. Two physicians with identical profiles may respond very differently to the same message if their decision heuristics and barrier profiles differ. Behavioral segmentation identifies those differences to enable more precise targeting and differentiated messaging.

Behavioralize approaches launch strategy by diagnosing behavioral barriers to adoption before they become commercial problems. Through a barrier, driver, and decision diagnostic, Behavioralize maps the decision landscape, identifies which mechanisms are in play, and specifies which interventions are most likely to produce the needed shift before launch, not after.

Behavioralize supports launch readiness by identifying the belief and behavior shifts that matter most and aligning Medical Affairs, Insights, Marketing, and Field teams around those priorities. Through behavioral diagnostics and cross-functional strategy work, teams build a shared, evidence-based understanding of how prescribing decisions are actually made — ensuring that evidence generation, messaging, education, and field execution are grounded in the same behavioral foundation.

Behavioralize approaches messaging by working backward from the behavioral outcome a message needs to produce. Rather than optimizing for liking or recall, the work identifies the cognitive and emotional barriers a message must address — misperceptions, risk calibration gaps, identity concerns, decision friction — and ensures that language, framing, and sequencing move HCPs toward the target clinical action. This applies across message development, message testing, and content strategy.

Behavioralize informs content strategy by identifying the cognitive and emotional dynamics that must be addressed before creative work scales — where HCP mental models create resistance, which emotional responses such as uncertainty or identity threat shape engagement, and how to sequence information to reduce cognitive overload. Applied early, this reduces the risk of creative executions that resonate aesthetically but fail behaviorally in the field.

Behavioralize helps Medical Affairs teams move beyond knowledge transfer to changing clinical reasoning and decision behavior. The work applies cognitive and decision science to understand how HCPs interpret evidence, organize risk information, and make real-world treatment decisions under time pressure. This includes improving scientific communication, designing medical education, and developing KOL and KEE engagement strategies grounded in how influence operates in clinical communities.

Traditional medical education increases knowledge without always changing clinical behavior. Behavioralize designs medical education that targets clinical reasoning and decision quality rather than information recall — using real-world case scenarios, surfacing the diagnostic shortcuts clinicians actually use, and reframing risk and patient eligibility to fit clinical workflows. This approach applies across congresses, situation rooms, advisory boards, and interactive workshops.

Behavioralize helps Medical Affairs teams design KOL and KEE engagement strategies grounded in how influence and social proof actually operate in clinical communities — how expert peers form beliefs and what motivates genuine engagement rather than surface participation. This means activating the right experts at the right moments, structuring interactions for peer-to-peer influence, and aligning KOL and KEE activity with the behavioral shifts that matter most for adoption.

Behavioralize helps field teams move beyond information delivery to guiding better clinical decisions. The work starts with behavioral HCP research — qualitative, quantitative, or mixed-methods — to uncover which beliefs and decision barriers drive prescribing or switching, and where field conversations stall. Behavioralize translates findings into field-ready assets and deploys them at sales meetings and workshops to help field teams embed behavioral science into daily practice.

Question-based selling uses targeted, diagnostically designed questions to surface what is actually holding an HCP back — rather than responding to surface objections with scripted rebuttals. HCP resistance usually reflects an underlying decision barrier — a misperception, unresolved risk concern, habit, or identity-based reluctance — that scripts cannot address. Behavioralize's question-based selling frameworks reveal the real cognitive source of hesitation and guide conversations toward meaningful clinical next steps.

Behavioralize integrates AI through a human-centered co-intelligence model that matches AI capability to tasks where it adds the most value while preserving human judgment where it matters most. AI is applied to scale qualitative data collection, detect patterns across large behavioral datasets, and power agentic insight-query tools. Human expertise remains central to research design, behavioral diagnosis, and strategic translation — areas where nuance and scientific rigor cannot be reliably automated.

Behavioralize uses agentic AI tools to let pharma teams query and reapply behavioral research findings long after the initial project readout — surfacing patterns relevant to new strategic challenges and connecting earlier findings to evolving commercial or medical decisions without re-running the original study. AI augments scientific judgment rather than replacing it, ensuring behavioral rigor is preserved in how findings are interpreted and applied over time.