How to Deliver a Better FemTech Experience: UX Considerations
The FemTech revolution has not only revolutionised women’s healthcare but has also shed light on the importance of a user-centric approach to cater to its diverse user base. Despite this, there is relatively little information available on best practices for how to evaluate or design for enhanced FemTech user experience.
In this one-hour webinar, Shada Azodi and Martin Porcheron, from Bold Insight—a User Experience and Human Factors research agency with offices in London and Chicago—will discuss key UX research principles and strategies that can be employed to optimise FemTech products, ensuring improved usability, accessibility, and overall satisfaction for users. They’ll use examples stemming from first-hand experience and industry guidelines to solidify best practices, empowering the FemTech sector to proactively respond to unmet needs, foster positive user experiences, and stay ahead of the curve.
Research Director · Bold Insight
Shada is passionate about medical technology and has end-to-end experience in developing digital solutions and solving complex problems in acute/sub-acute care settings. She has been involved in every aspect of development from ideation to UX/UI design/testing, regulatory submissions, and pre/post commercialisation phase. Shada enjoys interacting with people to better understand how the devices they interact with impact their lives, and how to optimise these tools to create better experiences.
In addition, Shada has a strong clinical background in women’s health (OB/GYN) ultrasound and has firsthand experience of its unique challenges and requirements. She supports FemTech companies in improving the usability and accessibility of their products, leveraging her expertise in both clinical practice and the industry.
Senior UX Researcher · Bold Insight
Martin has ten years of experience conducting user research with portable and novel technologies across multiple settings, including homes, health and public settings. He has completed projects on how to improve the experience of using voice-based technologies for people with low-language proficiency in the past few years and has recently been working on the integration and evaluation of new Machine Learning technologies in various parts of the UK health service. Martin holds a PhD in multidisciplinary Computer Science from the University of Nottingham, where he remains a Visiting Researcher. His PhD focused on how people talk and bring their technology use into their everyday conversations with others.