I helped reposition a struggling fintech product by identifying the right user persona and redesigning the experience to make stock trading feel as accessible as a Netflix subscription — achieving a strong product-market fit.
Stock trading platforms often feel complex and intimidating for first-time users. How might we make investing approachable, intuitive, and even fun — like subscribing to your favorite streaming service?
I started with in-depth design research to identify root issues in user-product fit. I then transitioned into interaction design, prototyping a new, simplified trading model. The full team included motion designers, content strategists, and UI designers.
Using a structured Double Diamond process, I investigated why the original product failed to resonate. Focused user research was conducted on financial behaviors. I concept-tested a radically simplified interaction model. I designed a conversational flow that mirrored familiar digital experiences.
Due to the confidential nature of the project, access to users was limited. We had to define a conversational AI experience before large language models (LLMs) were widely available, requiring a lot of manual scripting and prediction logic.
We introduced a subscription-based access model offering monthly investment tips powered by a trading algorithm. A conversational UI was designed which guided users through trading in a friendly, simplified dialogue — reducing friction, jargon, and complexity.
The redesigned product achieved product-market fit with the new persona. Early adopters reported increased confidence and enjoyment in using the app. The conversational model laid groundwork for future AI-powered engagement.
Integrate modern LLM technology to power a more dynamic and intelligent conversational UI. To expand the subscription model with more personalized insights and nudges.