HowWeFeel

HowWeFeel

Personal Project

Personal Project

Designing for Distress: Intelligent Guidance for HowWeFeel

Transforming a chaotic list of notes into an empathy-driven dashboard for self-awareness.

Transforming a chaotic list of notes into an empathy-driven dashboard for self-awareness.

Transforming a chaotic list of notes into an empathy-driven dashboard for self-awareness.

Product Designer | 2 Weeks

Conceptual Feature Design (Survey-Informed)

Conceptual Feature Design (Survey-Informed)

Product Strategy, Information Architecture, Visual Design

Product Strategy, Information Architecture, Visual Design

Methodology & Constraints

This case study documents a strategic design exploration informed by qualitative survey data from existing users. The focus of this sprint was on problem diagnosis, information architecture, and high-fidelity visual execution.

This case study documents a strategic design exploration informed by qualitative survey data from existing users. The focus of this sprint was on problem diagnosis, information architecture, and high-fidelity visual execution.

This case study documents a strategic design exploration informed by qualitative survey data from existing users. The focus of this sprint was on problem diagnosis, information architecture, and high-fidelity visual execution.

Note: Due to project constraints, this specific iteration has not yet undergone usability testing. The design decisions below represent hypotheses based on UX heuristics and user mental models.

The Problem: "Help Me Find My Signal in the Noise"

The Problem: "Help Me Find My Signal in the Noise"

The Problem: "Help Me Find My Signal in the Noise"

"I would long press the suggestion, and a heart pop up would show up. I select the heart pop up, and the suggestion gets saved. It would then be visible on my homepage as "Saved suggestions". These suggestions can also pop up when I'm going through tough emotions as a gentle nudge? Maybe that would make me angry, but it's an idea."

The project was initiated based on qualitative data from a user survey. One power user articulated a clear pain point: as they engaged more with the app, their list of personal "takeaways" became long and unmanageable.


The "Library" Mental Model Feedback revealed that users view their saved takeaways not just as a list, but as a growing "library... lined up for my worst days."


The Scalability Challenge This insight highlighted a critical scalability risk. While a new user might only have 3 takeaways, a power user could easily accumulate dozens. My analysis suggested that a simple list would eventually fail this user; in a moment of distress, they shouldn't have to scroll through 50 old notes to find the one they need right now. They require prioritization and awareness, not just storage.


Why a Simple List Wasn't Enough

Why a Simple List Wasn't Enough

The "Clustering" Hypothesis To address the user's request for "categorization," I first explored a simple ranked list. However, I identified a potential usability flaw in this approach: Clustering.


If a user had 15 takeaways about "Work Stress" and only 3 about "Family," a simple ranked list would bury the "Family" insights at the bottom. This design would inadvertently hide critical information from the user.


The Design Goal Based on this analysis, I determined that the final solution needed to provide a "Doctor's Diagnosis"—an immediate, high-level overview of all the user's problem areas—before asking them to dive into the details.

The Your Focus Dashboard

The Your Focus Dashboard

Tab-Based Architecture To solve the clustering problem, I moved from a list view to a Tab-Based System.

Tab-Based Architecture To solve the clustering problem, I moved from a list view to a Tab-Based System.

Tab-Based Architecture To solve the clustering problem, I moved from a list view to a Tab-Based System.

The tabs aim to provide immediate awareness. They categorize the AI-identified themes (e.g., "Work," "Self-Doubt") into clear, distinct buckets, allowing the user to scan their "diagnosis" at a glance.

Progressive Disclosure Within each tab, I implemented a "Show More" pattern that hides the full list by default, showing only the top 3 insights.

Progressive Disclosure Within each tab, I implemented a "Show More" pattern that hides the full list by default, showing only the top 3 insights.

Progressive Disclosure Within each tab, I implemented a "Show More" pattern that hides the full list by default, showing only the top 3 insights.

This structure is designed to reduce cognitive load. It aims to respect the user's cognitive limits in a moment of distress, preventing them from being overwhelmed by a "wall of text" while ensuring they retain full control to dive deeper when ready.

Analyze then Soothe

Introducing two new sections—the AI-driven Your Focus and the user-curated My Favorites—required a deliberate layout strategy. I prioritized Your Focus at the top, followed by My Favorites


This layout is based on a hypothesized "Guidance First, Comfort Second" workflow. My assumption is that in a moment of distress, a user first seeks to understand the problem (Guidance). Once they have clarity, they look to retreat to safety (Comfort). This hierarchy is intended to guide them through that natural emotional curve.

Visual Design & Micro-Copy

Visual Design & Micro-Copy

I broke the app's established pattern of abstract geometric shapes, using a Heart icon and a warmer background tone. This is intended to visually distinguish the section as a personal "sanctuary"—a safe space distinct from the functional library.


I chose the name "My Favorites" to imply user ownership and agency, contrasted with "Your Focus," which implies app-led coaching.

Next Steps & Validation Plan

Next Steps & Validation Plan

Because this design relies on strategic assumptions about user behavior in distress, the immediate next step would be validation. If this were a live project, I would prioritize:

  • Usability Testing the Tabs: Run unmoderated tests to ensure users understand that the tabs represent different themes and not just filters.

  • Validating the "Show More" Friction: Measure if the "Show More" button creates too much friction or if users appreciate the cleaner initial view.

  • A/B Testing the Hierarchy: Test the placement of Your Focus vs. My Favorites to see which order performs better for users in different emotional states.