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This project was a pre- startup incubation project spearheaded by an IIT alumni in India. A market study was done to test the business/product viability of the idea during Corona period. The solution aims to help parents find the right school for their kids (Aged between 5 to 10) online.
The most challenging part was to make a research plan, recruit remote participants for the interviews (during Corona) and then doing the thematic analysis after the interviews all alone.
I started the user research activities by making a plan which included stating the objective of the research, choosing the right methodology for research, creating interview scripts, selecting the criteria for recruiting the participants, timeline and constraints.
I combined qualitative and quantitative research methodologies to gain confidence in my exploratory research through interviews and validate the findings with surveys, hypothesis of the design solution and assess the task completion rates. These were done at various stages of the product conception.
Data gathered from combined user interviews, competitor analysis and surveys revealed following insights.
Parents with kids age between (5 to 12)
Recently got their kids admitted
Age between 35-45
Income group between 10 lacs to 40 lacs.
Qualitative Interviews: Educated stakeholders on design thinking to align with project goals.
Data triangulation: Collaborated with the product owner to collect data on dealer requirements and tech literacy.
Surveys: Developed and iterated on prototypes based on dealer feedback.
The MyTechXpert app successfully launched on iOS and Android, providing dealers with a digital tool to access detailed technical data, improving their efficiency and satisfaction.
I performed usability testing to find the issue within the design by creating tasks for the users and performed usability testing with 5 participants.
I measured Task Criticality, Task Impact, Frequency and used the three to find Issue Severity. Based on the severity the solutions were proposed at both Component/Pattern level and UX level as well.
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Based on the above findings I created all the Hypothesis that would help me overcome the above challenges and iterate on existing designs. This is a continuous process until I achieved a level of finesse and lower drop off rates and friction.
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After two rounds of iteration, user confidence increased significantly, resulting in a notable reduction in task completion time. Additionally, the task success rate improved by 80%.
