An introduction
Imagine an aftercare addiction app gaining popularity, but users are left scratching their heads. The data is there, but it’s confusing. Traditional charts are overwhelming, making it hard to understand how stress, sleep, or screen time actually affect their habits.
Users feel disconnected, less motivated to keep using the app, and unsure about what actions to take. The solution? Make the insights simpler, clearer, and more engaging.
Imagine an aftercare addiction app gaining popularity, but users are left scratching their heads. The data is there, but it’s confusing. Traditional charts are overwhelming, making it hard to understand how stress, sleep, or screen time actually affect their habits.
Users feel disconnected, less motivated to keep using the app, and unsure about what actions to take. The solution? Make the insights simpler, clearer, and more engaging.
Imagine an aftercare addiction app gaining popularity, but users are left scratching their heads. The data is there, but it’s confusing. Traditional charts are overwhelming, making it hard to understand how stress, sleep, or screen time actually affect their habits.
Users feel disconnected, less motivated to keep using the app, and unsure about what actions to take. The solution? Make the insights simpler, clearer, and more engaging.
Taking a peek into the background
MY ROLE
I was responsible for creating an intuitive solution that went beyond traditional charts and offered a personalized, interactive experience.
March 2024- May 2024
THE TEAM
I collaborated along side Dr. Julian Kruse, Manya Agawal, Ekanabasi Isok, Justas Karnickas and Stephanie Roth
TIMELINE
In this project, I was tasked with creating a mobile app feature to provide users with insights into their well-being, focusing on factors like stress, screen time, and mood.
The challenge was making this data engaging and actionable for users.
My goal was to design an intuitive solution that went beyond traditional charts and offered a personalized, interactive experience.
MY ROLE
I was responsible for creating an intuitive solution that went beyond traditional charts and offered a personalized, interactive experience.
March 2024- May 2024
THE TEAM
I collaborated along side Dr. Julian Kruse, Manya Agawal, Ekanabasi Isok, Justas Karnickas and Stephanie Roth
TIMELINE
Users found it hard to interpret the data and connect it to actionable improvements. Traditional data visualizations like generic charts and numbers failed to provide engaging insights into their well-being.
How might we explore a more interactive and intuitive way of presenting this information to better guide users in monitoring their triggers.
Users found it hard to interpret the data and connect it to actionable improvements. Traditional data visualizations like generic charts and numbers failed to provide engaging insights into their well-being.
How might we explore a more interactive and intuitive way of presenting this information to better guide users in monitoring their triggers.
Problem
Users who found the data overwhelming or hard to interpret were less likely to use the app consistently which could hurt retention, satisfaction and ultimately the app’s success.
The main takeaway was that users struggled with overly complex charts, which led to confusion and frustration.
Confusion from complex charts
🤦♀️
Users found the data hard to interpret so they will not be able to apply the information
Difficulty Interpreting data
😰
What I learned: Users want visually engaging formats that are easy to interpret at a glance but allow for deeper insights when needed. This shaped our decision to move away from traditional charts and explore more creative visualizations like bubbles.
To fully understand the issue, we conducted usability testing and gathered feedback from users.
The main takeaways were:
To fully understand the issue, we conducted usability testing and gathered feedback from users.
The main takeaways were:
To fully understand the issue, we conducted usability testing and gathered feedback from users.
The main takeaways were:
Digging deeper into the problem
A BREAKDOWN
"We needed something more, something that speaks to people, not just their data."
Users who found the data overwhelming or hard to interpret were less likely to use the app consistently which could hurt retention, satisfaction and ultimately he app’s success.
Low user engagement
The main takeaway was that users struggled with overly complex charts, which led to confusion and frustration.
Confusion from complex charts
Users found the data hard to interpret so they will not be able to apply the information
Difficulty interpreting data
"We needed something more, something that speaks to people, not just their data."
Users who found the data overwhelming or hard to interpret were less likely to use the app consistently which could hurt retention, satisfaction and ultimately he app’s success.
The main takeaway was that users struggled with overly complex charts, which led to confusion and frustration.
Confusion from complex charts
Users found the data hard to interpret so they will not be able to apply the information
Difficulty Interpreting data
"We needed something more, something that speaks to people, not just their data."
Exploration
We explored various charts like radar, spider and bubbles chart to track the users stress, sleep, mood, cravings, activity and screen time.
We decided to ditch traditional charts because they didn’t resonate with users. From a customer’s perspective, bubbles were much more engaging and easier to interpret.
From a business perspective, the bubbles also helped in retaining users by making the app more engaging and enjoyable to use.
We settled on using bubble visualization to represent various health metrics.
Each bubble varied in size, color, and position, indicating the importance and nature of metrics like stress or sleep. Users could tap on the bubbles to access deeper insights and receive personalized recommendations. This approach simplified the data while encouraging interaction and exploration.
We settled on using bubble visualization to represent various health metrics. Each bubble varied in size, color, and position, indicating the importance and nature of metrics like stress or sleep.
Users could tap on the bubbles to access deeper insights and receive personalized recommendations. This approach simplified the data while encouraging interaction and exploration.
We settled on using bubble visualization to represent various health metrics. Each bubble varied in size, color, and position, indicating the importance and nature of metrics like stress or sleep.
Users could tap on the bubbles to access deeper insights and receive personalized recommendations. This approach simplified the data while encouraging interaction and exploration.
Solution
User comes to the trends page showing insights.
User taps on trends on the navigation bar
User scrolls to see bubbles and taps
More insights is shown to the user
User journey
We considered users who might misinterpret the bubbles’ meanings. For instance, some users might confuse one health metric for another or struggle to understand the relationship between different factors. To address this, we provided in-app tutorials and ensured that tapping on a bubble delivered clear, detailed explanations.
We considered users who might misinterpret the bubbles’ meanings. For instance, some users might confuse one health metric for another or struggle to understand the relationship between different factors.
To address this, we provided in-app tutorials and ensured that tapping on a bubble delivered clear, detailed explanations.
We considered users who might misinterpret the bubbles’ meanings.
For instance, some users might confuse one health metric for another or struggle to understand the relationship between different factors.
To address this, we provided in-app tutorials and ensured that tapping on a bubble delivered clear, detailed explanations.
Edge Case
