Ava, an AI-powered emotional support app, was created to address the critical need for accessible and empathetic mental health support. My role as the UX/ Product Designer was to transform this vision into a user-centric iOS app that resonates with users on an emotional level. Through in-depth user research, strategic design thinking, and continuous iteration, the team crafted a product that offers human-like interactions, innovative mood tracking, and a seamless onboarding experience. The result is an app that not only boosts user satisfaction and adoption rate, but also it stands out in the competitive market.
But I wanted to go beyond a simple conversion. My goal was to create an app that stood out—delivering a seamless, engaging, and memorable user experience. The key question was: How could I design an app that not only resonates deeply with users but also capture users' attention and make a lasting impact in a competitive market?
When AI is involved, the user experience goes beyond just the interface and navigation; how the AI responds becomes central to shaping the entire experience. Even with a well-designed app, a robotic AI can make the experience feel disconnected. My goal was to make the AI feel empathetic and engaging, ensuring users felt truly understood and supported.
The solution was a user-friendly iOS app that featured human-like chat interactions, innovative mood-tracking using visuals, and a minimal onboarding process. The app provided an empathetic and supportive space for users to explore their emotions, with features designed to be both engaging and intuitive. The design was carefully crafted to balance the strengths of the AI with the need for transparency and user trust.
I approached the problem by first deeply understanding the Ava (chatbot)'s capabilities and limitations.
This means that not only it is important to design a user-friendly interface, but the quality of the interaction between the chatbot and users is crucial.
To integrate Ava effectively into the user experience, it was essential to understand its strengths, limitations, and unique features.
I conducted comprehensive user research, testing the existing web app MVP and gathering insights through surveys and interviews. This research revealed critical user needs:
Based on user insights, I developed a hypothesis focusing on two key areas: creating humanized, context-aware chat interactions and integrating mood tracking with emotional progress visualization. These elements would provide Ava with its unique value proposition, making it stand out in the competitive landscape of emotional support apps.
To test this hypothesis, I prioritized MVP features to ensure that we focused on the most critical elements to deliver a functional and appealing product to our users. The MVP includes all the must-haves, which are features that were determined to be low effort with high impact and are non-negotiable. I also included the should-haves to further enhance the user experience for the differentiation purposes.
Through a highly iterative design process, I tested and refined features with 183 real users through 4 rounds of testings. This approach allowed me to continuously improve the app, ensuring that each design choice—from chat pauses to mood-tracking prompts—was validated by user feedback, leading to a more empathetic and effective product.
Understanding that users wanted a more natural interaction with the AI, I collaborated closely with the engineering team to enhance Ava’s conversational abilities.
While some of these aspects can be enhanced by AI/ML engineering and I’ve been in close collaboration with development team to make it happen. I introduced features like appropriate pauses and feedback mechanism that made Ava’s responses feel more human and context-aware, resulting in 88% of users reporting that they felt heard and understood during their interactions and we saw 20% Increase in user interaction time.
To support users' emotional journeys and provide clear progress visualization, it was technically necessary to capture users moods at the beginning and end of each chat. Recognizing that users often struggled to articulate their feelings, I hypothesized that visual elements could help them express emotions more comfortably and clearly. Initial tests showed 60% of users found this approach engaging, though some felt constrained by the layout. I refined the layout and the copy to make it clear that typing was also an option, enhancing user choice and interaction. This solution leveraged the power of visual communication to provide a more vivid and personalized emotional experience.
To build trust while addressing users' privacy concerns, I designed an onboarding process that required minimal information. Allowing users to start a conversation without creating an account lowered psychological and effort-related barriers, aligning with industry standards to boost user satisfaction and adoption rates. Below is the initial onboarding flow;
While his approach was well-received, as it alleviated initial privacy concerns; however, the first iterations revealed some technical constraints that needed to be addressed. To address these, we integrated phone number verification, a common security measure, into the flow. The added step was carefully designed to maintain a seamless user experience, with clear communication on why this information was needed.
Below is an updated onboarding flow showing the addition of the phone number verification step:
As I’ve already highlighted the impact of each iteration, let's consider the overall outcomes of our efforts over the past year. We successfully transformed a web app into a refined iOS application, with nearly 15 versions launched on TestFlight. The strategic approach to product development has led to high user satisfaction scores, increased user adoption rates, and a System Usability Scale (SUS) score of 82%.
The journey ahead involves more testing on TestFlight with a comprehensive test plan ready for execution. Our focus will be on gathering more data and enhancing the integration of features. Key areas for improvement include:
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