CityFalcon is a Financial technology app that uses machine learning to find real-time, relevant and user filtered financial news personalised to their interests.
Project Details
The problem that needed to be fixed:
CityFalcon needed to talk to their users to find direct pain points with the current app. They also wanted proactive solutions on how to improve their app for their users.
This is how I used user research methods to help CityFalcon find their pain points and gave them active solutions to solve this problem.
Things to know:
15 participants were interviewed for this research.
the age range was from 22 to 50+ years old.
100% completion rate for each participant for the interviews and usability testing.
Interviews took 15-20mins for each participant.
here are the key findings and insights into the pain points discovered from the user interviews and usability testing.
The Outcome:
Conceptualized, defined and translated the four severity user pain points into project designs and implementation plans for the development team. CityFalcon has since gone on to compete with five different accelerator programs, featured in many main new outlets and had received funding from Crunchbase.