An application aimed at improving rosacea management through symptom tracking via AI.
Role | UX/UI Designer (personal project) |
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Platform | App MVP | Timeline | March 2024 (2 weeks) |
Tools | Figma, FigJam, OptimalSort, Airtable, Maze, Chat GPT |
Despite running out of skincare products, numerous water changes, and a temperature that never dropped below 26ºC, I experienced minimal rosacea symptoms during my months of travel in Southeast Asia. A confluence of events that should have exacerbated my skin condition made me question everything I knew about it. This experience was what motivated me to create Rubby.
Rubby aims to ease the management of rosacea and provide useful resources to improve people's quality of life. Offering an interactive and personalized platform that enables users to identify rosacea triggers, document symptoms, and share information with healthcare providers.
Rosacea is a chronic inflammatory skin disease, according to Yale Medicine. It is a widespread disorder that affects roughly 5% of the global population. There is no cure, and symptoms, treatment efficacy, and triggers differ widely across individuals.
I started the project with extensive research on rosacea. To organize and connect all results, I decided to develop a mind map to assist me see all of the collected information in a clear and organized manner.
With the problem space defined, I began analyzing current solutions. I discovered just two applications specialized to rosacea management, which I was unable to investigate further because one is only available in Germany and the other is a subscription-based app for iOS devices. As a result, I expanded my research to include mHealth apps.
Before moving on with the project development and after reviewing the few existing digital solutions, I conducted a survey to learn more about possible users' tracking methods and data collection.
I obtained 87 responses from people with rosacea from around the world aged between 19 and 54 years old. The results show that:
Furthermore, I conducted a primary research through personal interviews to gain insight into the current frustrations, goals, needs, and motivations of potential users.
I contacted four people who participated in the survey and focused the interviews on four axes with the aim of capturing expressions and opinions regarding:
People with rosacea are advised to identify and avoid triggers. However, pinpointing specific triggers often presents a challenge.
Living with rosacea has an impact on both the physical and psychological well-being, and it can cause intense negative emotions. Becoming aware of these emotions enables empathetic design, particularly in situations where the user may be stressed, anxious, or exhausted.
While online communities that connect people with rosacea can have a positive impact, they can also have a negative impact due to comparisons with others, and they must be moderated to prevent the spread of misinformation, junk content, or the promotion of potentially harmful products.
Healthcare professionals strongly advise patients to keep rosacea diaries or journals, but this can be a difficult task. As a result, it is critical to provide a simple and efficient method of monitoring and tracking data.
The research methods helped me better understand the users and how they could use the Rubby. I turned this understanding into visualizations to empathize with the users and define the product.
To synthesize the information gathered during the interviews and research phase, I developed a persona profile based on demographic characteristics and rosacea-related behavior.
The following step was to create a user journey that would serve as a guide and show how Anna interacts with Rubby to achieve her goals, as well as identify any spots that would cause friction during her experience.
Retrieving information from research insights and with the journey and user persona defined, I created a series of 'How Might We' questions to define the problem and lay the groundwork for the ideation phase.
Users can interact with the chatbot in a conversational and guided manner, reducing mental load and providing information naturally without the need to fill out forms or enter data manually.
A chatbot provides a conversational interface that can be much more intuitive and easy to use. This could help reduce friction and make the tracking process more accessible.
Through the use of artificial intelligence, a chatbot can analyze user responses to identify patterns and trends in their tracking data.
With the use of AI, the chatbot can analyze collected data and provide personalized suggestions and advice based on detected patterns.
The chatbot can adapt to each user's preferences and conversation patterns. Additionally, it can learn from past interactions to improve future responses and suggestions.
While implementing an AI and natural language-based tool may have an initial high time and cost investment, a chatbot can handle large amounts of data and interactions in an automated manner, allowing for application scalability.
I used the MoSCoW method to define and prioritize essential functionalities, ensuring that Rubby meets users' critical needs. This approach helped me streamline the product definition process and provided a framework for potential future improvements.
With the main features defined and with a clear idea that the solution should focus around an AI chatbot, providing a space where users could record their symptoms, habits, and any relevant information through natural conversation, I moved on to defining the information architecture.
To establish user flows and determine content distribution, I sketched screens that respond to the three main tasks: Recording rosacea symptoms, reviewing skin progress over time, as well as enabling users to upload photos of their skin for analysis.
During this phase, I faced the challenge of determining how an NLP chatbot could collect and process the data exchanged in the chat, and how this information could be clearly displayed for users.