Emotewell

Empowering Your Journey to Emotional Wellbeing

Emotewell is a mental health companion app designed specifically for home-based individuals managing severe mental health conditions. It provides personalized early warning systems to detect signs of mental health deterioration and delivers timely, tailored interventions. With features like AI-driven journaling, mindfulness exercises, and seamless integration with your support network, Emotewell empowers you to manage your mental well-being proactively during therapy sessions.

Emotewell is a mental health companion app designed specifically for home-based individuals managing severe mental health conditions. It provides personalized early warning systems to detect signs of mental health deterioration and delivers timely, tailored interventions. With features like AI-driven journaling, mindfulness exercises, and seamless integration with your support network, Emotewell empowers you to manage your mental well-being proactively during therapy sessions.

Emotewell is a mental health companion app designed specifically for home-based individuals managing severe mental health conditions. It provides personalized early warning systems to detect signs of mental health deterioration and delivers timely, tailored interventions. With features like AI-driven journaling, mindfulness exercises, and seamless integration with your support network, Emotewell empowers you to manage your mental well-being proactively during therapy sessions.

Role

Product Designer

Product Designer

Product Designer

Team

Team

Product Manager

Product Designer

Developers

Product Manager

Product Designer

Developers

Product Manager

Product Designer

Developers

Tools

Tools

Figma

FigJam

Google Workplace

Figma

FigJam

Google Workplace

Figma

FigJam

Google Workplace

Duration

Duration

04/2024-08/2024

04/2024-08/2024

04/2024-08/2024

Overview

Overview

Overview

Emotewell, an AI-powered journaling platform founded in 2021, aims to improve mental well-being through research-backed techniques. Despite its promising foundation, the platform struggled to achieve product-market fit, with low user engagement and no revenue generation. As the lead product designer, I reimagined Emotewell to better serve users’ needs and establish a sustainable business model.

Emotewell, an AI-powered journaling platform founded in 2021, aims to improve mental well-being through research-backed techniques. Despite its promising foundation, the platform struggled to achieve product-market fit, with low user engagement and no revenue generation. As the lead product designer, I reimagined Emotewell to better serve users’ needs and establish a sustainable business model.

Problem Statement

Problem Statement

Problem Statement

Emotewell's Challenge

Limited User Base: Only 500 users since launch.

Low Engagement: No power users or long-term engagement.

No Revenue: Zero paying users.

Platform Constraints: Web-based only, lacking mobile accessibility.

Limited User Base: Only 500 users since launch.

Low Engagement: No power users or long-term engagement.

No Revenue: Zero paying users.

Platform Constraints: Web-based only, lacking mobile accessibility.

Key Question: How might we redesign Emotewell to effectively meet the needs of severe mental health patients, achieve product-market fit, and establish a sustainable business model?

Key Question: How might we redesign Emotewell to effectively meet the needs of severe mental health patients, achieve product-market fit, and establish a sustainable business model?

“As the founder of Emotewell, it's been difficult to watch the product struggle for so long, but we hope to find a solution that will finally address the issues and help us deliver the value we've always envisioned.”
- Chloe Yuan

“As the founder of Emotewell, it's been difficult to watch the product struggle for so long, but we hope to find a solution that will finally address the issues and help us deliver the value we've always envisioned.”
- Chloe Yuan

“As the founder of Emotewell, it's been difficult to watch the product struggle for so long, but we hope to find a solution that will finally address the issues and help us deliver the value we've always envisioned.”
- Chloe Yuan

Understand

Understand

Understand

Customer-Centric Approach

Customer-Centric Approach

Customer-Centric Approach

We examined the mental health landscape through the customer journey lens, identifying user needs at each stage: Awareness, Consideration, and Action.

We examined the mental health landscape through the customer journey lens, identifying user needs at each stage: Awareness, Consideration, and Action.

We examined the mental health landscape through the customer journey lens, identifying user needs at each stage: Awareness, Consideration, and Action.

Journey Stage

Journey Stage

User Needs

User Needs

Insights

Insights

Opportunity

Opportunity

Awareness

Awareness

Recognize mental health challenges; understand that help is available.

Recognize mental health challenges; understand that help is available.

Users often lack awareness of innovative mental health solutions beyond traditional therapy.

Users often lack awareness of innovative mental health solutions beyond traditional therapy.

Increase visibility of practical self-management tools and early intervention options.

Increase visibility of practical self-management tools and early intervention options.

Consideration

Consideration

Evaluate different solutions; seek accessible and practical support methods.

Evaluate different solutions; seek accessible and practical support methods.

Users consider factors like ease of use, personalization, and integration into daily life.

Users consider factors like ease of use, personalization, and integration into daily life.

Highlight the app's personalized features and ease of integration with existing routines.

Highlight the app's personalized features and ease of integration with existing routines.

Action

Action

Commit to using a solution; require support in maintaining consistent use.

Commit to using a solution; require support in maintaining consistent use.

Users struggle with motivation and consistency in practicing techniques.

Users struggle with motivation and consistency in practicing techniques.

Implement features that encourage regular engagement and provide immediate value.

Implement features that encourage regular engagement and provide immediate value.

User Segmentation

User Segmentation

User Segmentation

We developed a Problem Intensity Assessment Framework to categorize users based on:

We developed a Problem Intensity Assessment Framework to categorize users based on:

We developed a Problem Intensity Assessment Framework to categorize users based on:

Frequency: How often they experience mental health issues.

Urgency: The immediate need for intervention.

Duration: How long the issues persist.

Frequency: How often they experience mental health issues.

Urgency: The immediate need for intervention.

Duration: How long the issues persist.

Frequency: How often they experience mental health issues.

Urgency: The immediate need for intervention.

Duration: How long the issues persist.

Segment

Segment

Frequency

Frequency

Urgency

Urgency

Duration

Duration

Need for
Intervention

Need for
Intervention

Mild

Mild

Low

Low

Low

Low

Short

Short

None

None

Moderate

Moderate

Varies

Varies

Moderate

Moderate

Mid-term

Mid-term

High

High

Sever

Sever

High

High

High

High

long-term

long-term

Urgent

Urgent

Users with mild mental health issues do not perceive their condition as severe enough to warrant sustained intervention. The focus should be on severe cases.

Users with mild mental health issues do not perceive their condition as severe enough to warrant sustained intervention. The focus should be on severe cases.

Users with mild mental health issues do not perceive their condition as severe enough to warrant sustained intervention. The focus should be on severe cases.

Given the significant differences in lifestyles and needs between patients and non-patients, we recommend focusing on severe mental health patients.

Given the significant differences in lifestyles and needs between patients and non-patients, we recommend focusing on severe mental health patients.

Given the significant differences in lifestyles and needs between patients and non-patients, we recommend focusing on severe mental health patients.

Within the mental health patient segment, we need to further categorize patients due to varying lifestyles, treatment settings, and care needs. Our data reveals four distinct categories below:

Within the mental health patient segment, we need to further categorize patients due to varying lifestyles, treatment settings, and care needs. Our data reveals four distinct categories below:

Within the mental health patient segment, we need to further categorize patients due to varying lifestyles, treatment settings, and care needs. Our data reveals four distinct categories below:

Home-based (Telemedicine) segment leads with a 50% market share and the highest evaluation score (31/35).
Outpatient and Other segments have moderate market share and evaluation scores.
The inpatient segment has the smallest market share and lowest evaluation score.

Home-based (Telemedicine) segment leads with a 50% market share and the highest evaluation score (31/35).
Outpatient and Other segments have moderate market share and evaluation scores.
The inpatient segment has the smallest market share and lowest evaluation score.

Home-based (Telemedicine) segment leads with a 50% market share and the highest evaluation score (31/35).
Outpatient and Other segments have moderate market share and evaluation scores.
The inpatient segment has the smallest market share and lowest evaluation score.

Conclusion: Focusing on home-based severe mental health patients aligns with our goals to meet user needs and establish a sustainable business model.

Conclusion: Focusing on home-based severe mental health patients aligns with our goals to meet user needs and establish a sustainable business model.

Conclusion: Focusing on home-based severe mental health patients aligns with our goals to meet user needs and establish a sustainable business model.

Competitive Analysis

Competitive Analysis

Competitive Analysis

We conducted a competitive analysis to understand the market landscape.

We conducted a competitive analysis to understand the market landscape.

We conducted a competitive analysis to understand the market landscape.

Primary Competitors (Talkspace, Ginger, BetterHelp):

Technology-driven and Symptom Management Focus:

AI-Driven Personalization:

Corporate Mental Health Solutions:

Real-Time Support:

Primary Competitors (Talkspace, Ginger, BetterHelp):

Technology-driven and Symptom Management Focus:

AI-Driven Personalization:

Corporate Mental Health Solutions:

Real-Time Support:

Primary Competitors (Talkspace, Ginger, BetterHelp):

Technology-driven and Symptom Management Focus:

AI-Driven Personalization:

Corporate Mental Health Solutions:

Real-Time Support:

Strategic Recommendations:

Focus on AI-Driven Personalization and Data Insights

Expand Corporate Offerings

Leverage Real-Time Support

Wellness vs. Symptom Management

Strategic Recommendations:

Focus on AI-Driven Personalization and Data Insights

Expand Corporate Offerings

Leverage Real-Time Support

Wellness vs. Symptom Management

Strategic Recommendations:

Focus on AI-Driven Personalization and Data Insights

Expand Corporate Offerings

Leverage Real-Time Support

Wellness vs. Symptom Management

User Journey Map

User Journey Map

User Journey Map

We developed a user journey map based on the interviews to deepen our understanding.

We developed a user journey map based on the interviews to deepen our understanding.

We developed a user journey map based on the interviews to deepen our understanding.

Key insights included:

Inconsistent Practice:
Users forget or lack motivation to practice techniques.

Desire for Simplicity:
Need for bite-sized, easily digestible content.

Personalization:
Importance of tailored strategies and practical applications.

Limited Support Systems:
Hesitancy to engage with online communities or unfamiliar resources.

Key insights included:

Inconsistent Practice:
Users forget or lack motivation to practice techniques.

Desire for Simplicity:
Need for bite-sized, easily digestible content.

Personalization:
Importance of tailored strategies and practical applications.

Limited Support Systems:
Hesitancy to engage with online communities or unfamiliar resources.

Key insights included:

Inconsistent Practice:
Users forget or lack motivation to practice techniques.

Desire for Simplicity:
Need for bite-sized, easily digestible content.

Personalization:
Importance of tailored strategies and practical applications.

Limited Support Systems:
Hesitancy to engage with online communities or unfamiliar resources.

Define

Define

Define

User Needs

User Needs

User Needs

Based on our research and user insights, we identified the following user need statements:

Based on our research and user insights, we identified the following user need statements:

Based on our research and user insights, we identified the following user need statements:

"As a home-based mental health patient, I need simplified and accessible tools to manage my symptoms daily, so that I can improve my emotional well-being between therapy sessions."

Luke Tanis

"As a home-based mental health patient, I need simplified and accessible tools to manage my symptoms daily, so that I can improve my emotional well-being between therapy sessions."

Luke Tanis

"As a home-based mental health patient, I need simplified and accessible tools to manage my symptoms daily, so that I can improve my emotional well-being between therapy sessions."

Luke Tanis

"As a user struggling with motivation, I need personalized reminders and engaging content, so that I can consistently practice techniques that help me cope."

Alex Spurun

"As a user struggling with motivation, I need personalized reminders and engaging content, so that I can consistently practice techniques that help me cope."

Alex Spurun

"As a user struggling with motivation, I need personalized reminders and engaging content, so that I can consistently practice techniques that help me cope."

Alex Spurun

"As someone overwhelmed during crises, I need immediate and easy-to-use support, so that I can manage my emotions effectively when distressed."

Ruan Richard

"As someone overwhelmed during crises, I need immediate and easy-to-use support, so that I can manage my emotions effectively when distressed."

Ruan Richard

"As someone overwhelmed during crises, I need immediate and easy-to-use support, so that I can manage my emotions effectively when distressed."

Ruan Richard

"As a patient communicating with my therapist, I need accurate symptom tracking tools, so that I can provide clear updates and receive appropriate care."

Vicky Haltenate

"As a patient communicating with my therapist, I need accurate symptom tracking tools, so that I can provide clear updates and receive appropriate care."

Vicky Haltenate

"As a patient communicating with my therapist, I need accurate symptom tracking tools, so that I can provide clear updates and receive appropriate care."

Vicky Haltenate

Core Value Proposition

For home-based severe mental health patients who need personalized, accessible, and proactive support to enhance their emotional well-being between therapy sessions, our product, Emotewell, is a mental health companion app that combines AI-driven tools with evidence-based techniques to offer immediate interventions and preventive care.

For home-based severe mental health patients who need personalized, accessible, and proactive support to enhance their emotional well-being between therapy sessions, our product, Emotewell, is a mental health companion app that combines AI-driven tools with evidence-based techniques to offer immediate interventions and preventive care.

Ideation

With a clear understanding of user needs and market gaps, we moved into the Ideation phase to brainstorm solutions.

Brainstorming

Brainstorming

Brainstorming

Cross-Functional Collaboration: Included mental health professionals, developers, and stakeholders.

Cross-Functional Collaboration: Included mental health professionals, developers, and stakeholders.

Cross-Functional Collaboration: Included mental health professionals, developers, and stakeholders.

Concept Development

Concept Development

Concept Development

1 Adaptive AI Chatbot providing personalized coping strategies.

2 Early Warning System detecting signs of mental health deterioration.

3 Crisis Mode Interface simplifies the app during distress.

4 Symptom Tracker with Visualizations for progress monitoring.

5 Gamification Elements to motivate consistent practice.

Evaluating Ideas

We use the following Evaluation Criteria to pick up our ideas:

Alignment

Comprehen-sive

Comprehensive

Feasibility

Feasibility

Differentiation

Differentiation

Scalability

Scalability

We integrated Ideas 1, 2, 3, and 4 into our solution, as they directly address critical user needs and offer unique market value.

01

Symptom Tracker with Visualizations

Goal


Encourage daily symptom tracking to promote self-awareness and provide valuable data for personalized support.

01

Symptom Tracker with Visualizations

Goal


Encourage daily symptom tracking to promote self-awareness and provide valuable data for personalized support.

01

Symptom Tracker with Visualizations

Goal


Encourage daily symptom tracking to promote self-awareness and provide valuable data for personalized support.

02

Adaptive AI Chatbot

Goal


Encourage users to engage with the chatbot for personalized coping strategies.

02

Adaptive AI Chatbot

Goal


Encourage users to engage with the chatbot for personalized coping strategies.

02

Adaptive AI Chatbot

Goal


Encourage users to engage with the chatbot for personalized coping strategies.

03

Early Warning System

Goal


Encourage proactive management by alerting users to early signs of deterioration.

03

Early Warning System

Goal


Encourage proactive management by alerting users to early signs of deterioration.

03

Early Warning System

Goal


Encourage proactive management by alerting users to early signs of deterioration.

04

Crisis Mode Interface

Goal


Provide immediate support during high distress with minimal cognitive load.

04

Crisis Mode Interface

Goal


Provide immediate support during high distress with minimal cognitive load.

04

Crisis Mode Interface

Goal


Provide immediate support during high distress with minimal cognitive load.

Design

Wireframe Sketch

Wireframe Sketch

Wireframe Sketch

We developed a straightforward user flow, integrating extensive data content into a seamless experience. The information architecture was carefully crafted to ensure easy navigation and content accessibility.

We developed a straightforward user flow, integrating extensive data content into a seamless experience. The information architecture was carefully crafted to ensure easy navigation and content accessibility.

We developed a straightforward user flow, integrating extensive data content into a seamless experience. The information architecture was carefully crafted to ensure easy navigation and content accessibility.

AI-Powered Journaling and Analysis

Simplified Journaling: Users log emotions with emotion words, distress levels, and context.

AI Chatbot Support: Provides personalized coping strategies.

Data Visualization: Helps users and therapists track progress.

Early Warning System

Trend Monitoring: Detects declines in mental health trends.

Proactive Alerts: Sends supportive notifications and suggests preventive actions.

Personalization and Integration

Customizable Prevention Routines: Sync with personal calendars.

Contextual Reminders: Based on user preferences and behavior.

Crisis Mode Interface

Simplified Design: Minimalistic interface during high distress.

Immediate Access: One-tap access to coping tools and emergency contacts.

Therapist Integration: Message therapist or friends to ask for help.

Prototype

Medium-fidelity

Medium-fidelity

Medium-fidelity

We developed a straightforward user flow, integrating extensive data content into a seamless experience. The information architecture was carefully crafted to ensure easy navigation and content accessibility.

We developed a straightforward user flow, integrating extensive data content into a seamless experience. The information architecture was carefully crafted to ensure easy navigation and content accessibility.

We developed a straightforward user flow, integrating extensive data content into a seamless experience. The information architecture was carefully crafted to ensure easy navigation and content accessibility.

Valuable Lessons

Valuable Lessons

Valuable Lessons

  1. User Interaction Flow

    Visualizing how users will move through the app


  2. Feature Relevance

    Assessing the placement and utility of features


  3. Design Feasibility

    Evaluating the practicality of implementing planned features

  1. User Interaction Flow

    Visualizing how users will move through the app


  2. Feature Relevance

    Assessing the placement and utility of features


  3. Design Feasibility

    Evaluating the practicality of implementing planned features

  1. User Interaction Flow

    Visualizing how users will move through the app


  2. Feature Relevance

    Assessing the placement and utility of features


  3. Design Feasibility

    Evaluating the practicality of implementing planned features

Iteration

Usability Testing

Usability Testing

We conducted thorough usability tests with our target audience, observing their interactions with the low-fidelity prototype. This phase was crucial in refining the app's usability and ensuring it meets and exceeds user expectations for functionality and experience.

We conducted thorough usability tests with our target audience, observing their interactions with the low-fidelity prototype. This phase was crucial in refining the app's usability and ensuring it meets and exceeds user expectations for functionality and experience.

We conducted thorough usability tests with our target audience, observing their interactions with the low-fidelity prototype. This phase was crucial in refining the app's usability and ensuring it meets and exceeds user expectations for functionality and experience.

What We Gained

What We Gained

What We Gained

  1. Clarity and Purpose

    The redesign clearly highlights the app’s dual focus on trail planning and air quality, quickly orienting new users.


  2. User Engagement

    By emphasizing interactive elements like the “Create a New Trail Plan” button and featuring top trails, the interface boosts user interaction.


  3. Optimized Design
    The updated layout removes clutter and negative messaging, enhancing visual appeal and promoting positive user interactions.

  1. Clarity and Purpose

    The redesign clearly highlights the app’s dual focus on trail planning and air quality, quickly orienting new users.


  2. User Engagement

    By emphasizing interactive elements like the “Create a New Trail Plan” button and featuring top trails, the interface boosts user interaction.


  3. Optimized Design
    The updated layout removes clutter and negative messaging, enhancing visual appeal and promoting positive user interactions.

  1. Clarity and Purpose

    The redesign clearly highlights the app’s dual focus on trail planning and air quality, quickly orienting new users.


  2. User Engagement

    By emphasizing interactive elements like the “Create a New Trail Plan” button and featuring top trails, the interface boosts user interaction.


  3. Optimized Design
    The updated layout removes clutter and negative messaging, enhancing visual appeal and promoting positive user interactions.

Final Delivery

After an extensive journey through problem statement, research, ideation, prototype, user-testing, and visual design, we present the final delivery for Trail Angel:

After an extensive journey through problem statement, research, ideation, prototype, user-testing, and visual design, we present the final delivery for Trail Angel:

After an extensive journey through problem statement, research, ideation, prototype, user-testing, and visual design, we present the final delivery for Trail Angel:

Make Trail plan

Make Trail plan

Create personalized outdoor trail plans with integrated air quality considerations

Create personalized outdoor trail plans with integrated air quality considerations

Create personalized outdoor trail plans with integrated air quality considerations

Detour A Trail

Detour A Trail

Adjust routes on-the-go based on changing air quality conditions

Adjust routes on-the-go based on changing air quality conditions

Adjust routes on-the-go based on changing air quality conditions

Change A Trail Plan

Change A Trail Plan

Access predictive information about potential wildfire risks and air quality changes

Access predictive information about potential wildfire risks and air quality changes

Access predictive information about potential wildfire risks and air quality changes

Benefits

Health Protection

Health Protection

Real-time air quality data helps users avoid areas with poor air quality, reducing exposure to harmful pollutants.

Real-time air quality data helps users avoid areas with poor air quality, reducing exposure to harmful pollutants.

Real-time air quality data helps users avoid areas with poor air quality, reducing exposure to harmful pollutants.

Enhanced Safety

Alternative route suggestions ensure users can continue their activities safely when conditions change.

Alternative route suggestions ensure users can continue their activities safely when conditions change.

Peace of
Mind

Peace of Mind

Predictive tools and alerts allow users to enjoy outdoor activities without constant worry about air quality changes.

Predictive tools and alerts allow users to enjoy outdoor activities without constant worry about air quality changes.

Enhanced Safety

Alternative route suggestions ensure users can continue their activities safely when conditions change.

Peace of Mind

Predictive tools and alerts allow users to enjoy outdoor activities without constant worry about air quality changes.

Reflection and Future Steps

The development of Trail Angel highlighted the critical importance of user-centric design in addressing complex environmental challenges.

Key learnings include:

  • The power of precise market segmentation in tailoring features to user needs

  • The importance of integrating diverse data sources for comprehensive environmental monitoring

  • The potential of machine learning in enhancing predictive capabilities for outdoor safety


Future developments will focus on:

  • Enhancing the app's predictive capabilities through more advanced machine learning models

  • Expanding the network of compatible IoT devices for more granular air quality monitoring

  • Developing partnerships with outdoor recreation organizations to broaden the app's reach and impact

The development of Trail Angel highlighted the critical importance of user-centric design in addressing complex environmental challenges.

Key learnings include:

  • The power of precise market segmentation in tailoring features to user needs

  • The importance of integrating diverse data sources for comprehensive environmental monitoring

  • The potential of machine learning in enhancing predictive capabilities for outdoor safety


Future developments will focus on:

  • Enhancing the app's predictive capabilities through more advanced machine learning models

  • Expanding the network of compatible IoT devices for more granular air quality monitoring

  • Developing partnerships with outdoor recreation organizations to broaden the app's reach and impact

The development of Trail Angel highlighted the critical importance of user-centric design in addressing complex environmental challenges.

Key learnings include:

  • The power of precise market segmentation in tailoring features to user needs

  • The importance of integrating diverse data sources for comprehensive environmental monitoring

  • The potential of machine learning in enhancing predictive capabilities for outdoor safety


Future developments will focus on:

  • Enhancing the app's predictive capabilities through more advanced machine learning models

  • Expanding the network of compatible IoT devices for more granular air quality monitoring

  • Developing partnerships with outdoor recreation organizations to broaden the app's reach and impact