Role
UX research, conversation design, product strategy
Methods
User activity tracking, engagement analysis, message/session analysis, post-intervention feedback, survey analysis, usability evaluation
Design decisions
The chatbot was designed as a low-friction support tool, not a replacement for care. The interaction model emphasized familiar prompts, meditation, affirmations, emotional pacing, and lightweight reflection so users could engage without pressure.
Solution + impact
The final experience showed that small, supportive conversational interactions could help users feel more positive during lockdown. 83.9% found it extremely useful, 86.7% felt more positive and cheerful, 61.3% found it easy to use, and 19 participants showed improved Kessler scale scores.
Case study
The Mental Wellness Chatbot explored how conversational interfaces could support emotional well-being during the COVID-19 lockdown.
The goal was not to replace therapy, but to create a light-touch support system through meditation prompts, positive affirmations, simple exercises, and reflective engagement.
My work focused on conversational UX, research analysis, user engagement tracking, and post-intervention evaluation. The study looked at user activity, messages, sessions, popular actions, feedback, and mental wellness indicators.
The key insight was that users valued small, familiar, emotionally supportive interactions. Meditation and positive affirmations were the most preferred tasks, showing that users were looking for comfort, encouragement, and structure during isolation.
The chatbot performed well as a low-friction support tool: 83.9% found it extremely useful, 86.7% felt more positive and cheerful, 61.3% found it easy to use, and 19 participants showed improved Kessler scale scores.
This project shaped my understanding of designing for vulnerable emotional contexts, where tone, pacing, boundaries, and trust matter as much as functionality.
Additional screens, artifacts, and process details.
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