Quick Summary / TLDR
➡️ Problem: Apps often lose new users before they even start. Onboarding feels tedious, impersonal, or confusing.
➡️ Role: I reimagined onboarding as a choice. Users could either chat with a friendly AI guide or set up manually at their own pace.
➡️ Solution: A warm, accessible onboarding experience that feels more like a conversation than a form while helping users start strong and stay engaged.
➡️ Impact: The concept received high marks and positive feedback for its clarity, accessibility, and thoughtful balance between innovation (artificial intelligence) and simplicity.
Keep reading to see how it all came together.
Intro / Background
FitNest Plan is a concept fitness app designed to help users stay active and motivated through personalized workouts, meal guidance, habit tracking, and social accountability. Developed as part of my UX Design capstone at UT Austin, the app’s vision grew from a key insight found in our exploratory research: People want personalized guidance from real humans, unlike the one-size-fits-all fitness apps on the market these days.
A key part of my focus was on the onboarding experience. It's a critical moment that determines whether users stay or leave. I wanted to design something that felt personal, supportive, and inclusive. The idea was to use conversational AI as a differentiator or USP. It would guide users through setup in a way that builds trust and confidence from day one.
This UX case study explores a key question:
How can onboarding feel welcoming and motivating instead of tedious and transactional?
How can onboarding feel welcoming and motivating instead of tedious and transactional?
The Problem
Up to 90% of users abandon apps during onboarding. Many fitness apps either collect too little information, making the experience generic. Or they ask too much at once, overwhelming users with form fields and steps that feel like digital paperwork. Both extremes create friction and disengagement. I wanted to change that and explore how conversational AI could make onboarding feel more human.
I hypothesized that simplifying the setup into two stages would improve completion and retention, while still collecting enough relevant data for personalization:
1️⃣ Basic info and account setup
2️⃣ Fitness, diet, and wellness preferences
2️⃣ Fitness, diet, and wellness preferences
The goal was to balance structure and simplicity. By allowing users to explore the app between two stages, we could demonstrate value early and build trust before asking for more personal health details.
The key challenges or pain points were:
❌ Tedious data entry: Too many screens and questions.
❌ Cognitive fatigue: Too much information too soon.
❌ Lack of trust: Users hesitate to share sensitive details before they see value.
❌ Cognitive fatigue: Too much information too soon.
❌ Lack of trust: Users hesitate to share sensitive details before they see value.
Research Goals + Methodologies
My research focused on understanding what motivates users to stay consistent — and what discourages them — both in fitness apps and real-world training.
Research methods used:
✅ Google survey: Collected feedback on first impressions and frustrations in popular fitness apps.
✅ Trainer interviews: Spoke with two local trainers to learn what questions they ask new clients and what keeps people motivated early on.
✅ Competitive analysis: Reviewed Strava®, MyFitnessPal®, and Nike Training Club® to identify patterns, usability gaps, and best practices.
✅ Trainer interviews: Spoke with two local trainers to learn what questions they ask new clients and what keeps people motivated early on.
✅ Competitive analysis: Reviewed Strava®, MyFitnessPal®, and Nike Training Club® to identify patterns, usability gaps, and best practices.
Key insights discovered:
✅ Users value simplicity and encouragement over lengthy data collection.
✅ Reducing visual and cognitive load builds trust and completion.
✅ Accessibility basics (e.g., color contrast, spacing, and legible typography) are essential.
✅ Reducing visual and cognitive load builds trust and completion.
✅ Accessibility basics (e.g., color contrast, spacing, and legible typography) are essential.
My Role
➡ Lead researcher / UX designer / Creative director
➡ Translated research findings into flows, interactions, and system behaviors
➡ Designed the information architecture, user flows, and high-fidelity wireframes
➡ Led screen templates and visual design direction (including grid, typography, and component library)
➡ Designed the FitNest logo and app icon
➡ Tools used: Google Forms, Google Docs, FigJam, Figma, PowerPoint, Google Meet
➡ Translated research findings into flows, interactions, and system behaviors
➡ Designed the information architecture, user flows, and high-fidelity wireframes
➡ Led screen templates and visual design direction (including grid, typography, and component library)
➡ Designed the FitNest logo and app icon
➡ Tools used: Google Forms, Google Docs, FigJam, Figma, PowerPoint, Google Meet
Beyond the onboarding flows, my contributions extended to the Account hub and screens, leading the research, and driving the competitive analysis framework.
A presentation animation showing the FitNest Plan onboarding experience. The user experience features a conversational AI approach that humanizes the setup process and drives completion. It's designed to reduce friction and build trust.
Above: To show how the final design came together, these screens illustrate my mid-fidelity wireframes for the onboarding flow. They were critical in building alignment on the design direction and solidifying the user narrative before the final high-fidelity polish.
We also designed and evaluated several AI voice bot interface concepts. Ultimately, we chose Concept #5, which features a visual of a real human talking. This approach was selected because it is expected to accelerate trust and provide a more natural and human-like interaction.
Below: These screenshots show my foundational work and planning. They capture the preliminary design phase, including sketches, initial notes, information architecture (IA), and user flow mapping. They establish the structural foundation for the user experience.
To ensure the design's success, I also began forward-thinking about implementation. This includes outlining a plan to test the onboarding flows and preparing the rationale to defend the chosen approach (specifically the pros and cons of an AI-guided vs. Manual setup).
This click-through prototype highlights the app’s visual design, flow, and key screens. Most interactions are guided for presentation purposes, with some elements intentionally limited or non-functional. Conversational content is placeholder text, as full dialogue scripts would typically be developed later by a UX Writer or Content Designer.
Challenges + Learnings
Working with a diverse team brought both creative opportunities and coordination challenges. Aligning design decisions, timelines, and priorities required flexibility and empathy. These were lessons that directly apply to real-world UX collaboration.
Balancing innovation with feasibility was another key takeaway. The conversational AI idea had strong potential to improve engagement, but also added technical complexity. This experience helped me understand how to balance creativity with what’s practical to build.
Most importantly, I learned that onboarding sets the emotional tone for the entire experience. A clear, supportive start builds trust and confidence. That’s where good UX begins.
Impact + Results
Instructor quotes pulled from our capstone feedback:
💬 "Loved the visual design! Great option to have both AI and manual."
💬 "Good animations in Nate's section."
💬 "Really nice, thoughtful design that feels pretty realistic. Really good design files. Well done!"
💬 "It feels real-world. I could see this app being fully developed."
💬 "Good animations in Nate's section."
💬 "Really nice, thoughtful design that feels pretty realistic. Really good design files. Well done!"
💬 "It feels real-world. I could see this app being fully developed."
Postface: As a capstone project, FitNest Plan wasn’t actually built, much less released publicly. However, it earned high marks and strong feedback for its clarity, visual polish, and thoughtful integration of conversational AI. It also scored high for addressing the initial problem statement and answering a real-world need.
If the app were developed further, I would conduct A/B and usability testing between the AI and manual flows to measure:
✅ Completion rates
✅ Drop-off points
✅ User sentiment and ease of use
✅ Drop-off points
✅ User sentiment and ease of use
These results would help validate whether conversational AI truly improves onboarding and long-term retention.
Interested? Let’s connect.
