Leveraging years of research in the chronic health experience space, the strategy team at Mad*Pow has developed a Chronic Health Experience map that can be utilized by anyone to brainstorm health solutions. Each Health journey is unique and to design effectively for health, consider key moments that lead to active information seeking or action. These are typically episodic and/or triggered by dissatisfaction. See more and download the map. Here's a webinar on how to use the map
Partnering with sleep experts to envision an app that supports better sleep habits. Leveraging the COM-B model for behavior change, we created an intervention strategy rooted in evidence and scientific research. Supported design team in laying the foundation of a product that would break away from the traditional business model of this Fortune 300 company.
Co-creating MPACT, a generative tool to create project-specific, behavior-based personas that significantly reduces time spent building personas. Our team utilized hundreds of hours of prior research to determine the most relevant personality traits that affect how people manage their health and personal finance, leading to persona-building kits specific to these industries. Download a free version here. See more and download.
Crafting a revolutionary employee benefits management platform that transforms the traditional marketplace leading to differentiation, and new revenue streams. Redefined how a fragmented health ecosystem could be consolidated to create lower costs, better health outcomes, and maximum utilization of benefits, all with the smart use of data and behavioral science. Enabled socialization of concept to executives to influence the next decade of strategic focus for this Fortune 500 company.
Leading a group in a week-long design sprint with stakeholders of a national health insurance association. Met the goal of reimagining key pieces of the customer journey while solving for regulatory, technical and other complex feasibility hurdles along the way.
Developed and executed a blended quantitative and qualitative research method to aid with development of AI-driven diabetes management personal assistant. Built understanding of personalization needed with demographic, condition progression, lifestyle choices and personality type considerations.
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