Existing affirmation apps, despite their popularity, often fall short of meeting the needs of mindfulness-aware individuals. They provide generic affirmations, lacking the personal touch that is essential for users seeking reassurance.
Affie is a unique affirmations app that stands out by personalizing users’ daily affirmations with AI. This AI integration involves a short questionnaire, which allows users to enjoy a tailored affirmation each time they need one. This ensures that the affirmations are relevant, effectively assisting users achieve their mindfulness goals.
Competitive research was performed on existing apps to investigate the current patterns for an app of this kind. Four different apps were studied to ensure an understanding of their current onboarding and sign-up processes, along with exploring the elements on their homepage and other tabs.
The research process also involved empathizing with users through one-on-one remote interviews. These helped to understand their points of view and gather data from seasoned users on similar apps, ensuring the reliability of our app.
Five participants were interviewed. Some of the most important questions asked were:
Do you have any specific emotions or feelings as you seek affirmations?
Where are you when you need affirmations?
How long do you dedicate to your practices?
What do you expect to gain when you're looking for an affirmation?
From this research, I learned that users desire a product that helps them improve their negative feelings, allows them to gain confidence and motivation, and doesn't take much of their time. A product they can use from home, but also from wherever they happen to be when they need it. Users need a product that makes them feel seen and heard, but that doesn't require much effort on their part.
A MoSCoW map was handy for determining the priorities of the product. What did users want the most? What do they absolutely not want? What is the most meaningful way we can help? What can be achieved during the project's allotted time? These questions are essential to remember when prioritizing to ensure an MVP can be successfully launched.
After setting the priorities, it was time to add a face to the feedback and insights, as if they had become one person. Personifying this user's interests, goals, and even pain points makes it even easier to empathize with them.
Carlos and Megan seem nice! How can we support them on their passions while helping them in their quest for affirmations?
This user flow demonstrates the user journey towards a personalized affirmation. Once these steps are clear and concise, we can give our app some personality.
The sketch above represents the home screen view, a few affirmations within a category, and a selected affirmation inside that category.
This set of sketches represents a very early version of the questionnaire before any iterations and feedback were taken into consideration. It's always fun to go back and see how much the final product has evolved from its early stages and how much of it made it through.


High Fidelity
A few extra screens!

Various icons and original components were implemented to give this app a consistent and visually appealing look. The icons and components in this UI kit were created with users in mind. These are the bits that will act as a door between humans and software, allowing interaction with the AI questionnaire and other features.
Of all the parts of this process, the one I’ve enjoyed the most so far has been designing high-fidelity mockups. Translating a pencil sketch into higher fidelity takes more than just personal effort. It takes teamwork and willingness to give and receive feedback from peers and mentors to improve your work.
Five people were interviewed remotely to test the app’s different flows on a Figma Prototype: Sign Up, AI Affirmation Prompt and Questionnaire - Happy, AI Affirmation Prompt and Questionnaire - Unhappy (Regenerate), History, Categories, Mood Log, and Account.
However, we will focus on the app's main task (AI Affirmation Prompt and Questionnaire — Happy) for case study purposes.
