Rubby: Improving rosacea management

An application aimed at improving rosacea management through symptom tracking via AI.



Role UX/UI Designer (personal project)
Platform App MVP
Timeline March 2024 (2 weeks)
Tools Figma, FigJam, OptimalSort, Airtable, Maze, Chat GPT

The Idea

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.


  • There are many possible triggers, and they do not affect everyone equally.
  • Constantly monitoring rosacea triggers can lead to increased concern about the disease. If the solution is not well designed, it could become a source of stress.


  • Develop a mobile application to help people with rosacea identify triggers and track symptoms.
  • Create a user-friendly interface focused on ease of use, ensuring that users can record their symptoms effortlessly.
  • Direct the product towards symptom management and trigger identification, prioritizing a solution that simplifies the experience.


Researching the problem space

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.

Rubby Mind Map


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.

Survey Results

I obtained 87 responses from people with rosacea from around the world aged between 19 and 54 years old. The results show that:

  • 72% of respondents use some form of tracking or recording.
  • Over 50% make more than one recording per week, with nearly 40% of people making daily recordings.
  • The most common tracking topics, ranked from most to least common, include: redness levels, topical or cosmetic products, emotional state or stress, diet and beverages, environmental conditions, medication, and exercise.
  • The most used recording method is mobile note's app.


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:

  • The impact of living with rosacea
  • The importance or motivation to identify triggers
  • Opinions related to support networks
  • The relationship between patients and dermatology.


Research insights

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.

User Persona

To synthesize the information gathered during the interviews and research phase, I developed a persona profile based on demographic characteristics and rosacea-related behavior.

User Persona

User Journey

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.

User Journey

How Might We?

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.

  • How might we simplify the identification of specific rosacea triggers for each person?
  • How might we use data analysis to simplify the lives of people with rosacea and avoid information loss?
  • How might we create a dedicated digital tool that offers personalized and specific tracking for rosacea, providing deeper and more useful insights for each individual?
  • How might we facilitate the sharing of updated information with medical professionals to improve communication and collaboration in rosacea treatment?
  • How might we design Rubby to be a tool that not only helps people with rosacea better understand their condition but also feel more empowered to make decisions about their health?

How might we simplify the process of tracking rosacea triggers to alleviate stress from constant monitoring?

Defining The Idea

With the 'How Might We' questions listed, I began generating ideas. Devoting five minutes to generate solutions for each problem, upon reviewing the results, I noticed how a possible solution emerged in most responses. Directing the solution towards a NLP Chatbot.


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.

Ease of Use

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.

Pattern Recognition

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.

Enhanced Experience:

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.


Prioritizing Features

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.


Content Tree

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.


Sketching Flows and Understanding NLP Technology

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.