Most tools track calories and macros, but overlook why we reach for certain foods—like stress, boredom, or burnout. This leaves users feeling judged, not supported. Without addressing the emotional side of eating, it’s hard to build habits that truly stick.

"Help users identify and reflect on the emotional responses connected to their eating habits, provide a platform for introspection and self-recognition, and equip them with tools to uncover patterns and meet their emotional and physical needs?"

To understand user pain points and untapped opportunities, I used a layered research strategy:

Current calorie-tracking applications lack meaningful integration of emotional awareness and reflection, leaving users without tools to understand how their emotions influence eating habits.

I conducted user interviews and usability tests to understand how people currently interact with food tracking tools — and where emotional awareness is overlooked.

01

Emotional eating is simply overlooked in traditional food logging systems.

02

Users struggle to identify emotional eating in real-time. While users often reflect on emotional triggers after the fact, few tools help them pause and check in before or during a decision, reducing opportunity for change.

03

Users want to feel guided, not judged.Participants expressed frustration with judgmental or overly clinical language in current apps. They valued prompts that felt emotionally intelligent, optional, and empathetic.

04

Correlating mood and meals builds trust.Users felt seen when emotional patterns were reflected back to them. Visual insights increased motivation to log consistently.

Insight: Users experience their strongest emotional awareness immediately before and after eating—critical windows for reflection and self-regulation that are often ignored by traditional tracking apps.

Embedding mood-tracking at these two emotional checkpoints allows us to:\n- Foster emotional literacy around food choices

• Deliver just-in-time nudges for mental regulation
• Highlight behavioral patterns over time, encouraging sustainable habits

I ran four rounds of unguided testing with early prototypes, where participants navigated the flow using only visual and contextual cues, with the assigned goal of completing the check-in flow.

Recordings were analyzed to identify friction points and improve clarity.

• 1 Expanded the primary data visualization to be central to the frame. Allowing users to see their progress towards their daily macro targets at a glance.
• 2 Aligned text elements to the concentric rings, colour coding them for easier reading, reduced cognitive load, and increased understanding.
• 3 Replaced fixed meal categories (e.g., "breakfast") with time-stamped entries to support flexible eating patterns. Moved meal logs below the daily summary and added at-a-glance macro breakdowns for quick insights.

• 1 Reduced the sheer volume of content on insight summary screen in favour of a progressive disclosure model. To increase understanding, and reduce cognitive load.
• 2 Introduced keyword highlighting in trend analysis to support instant, at-a-glance pattern recognition.
• 3 Reduced high-contrast visuals to create a cleaner, more focused viewing experience.

• 1 Removed redundant UI markers. Increasing whitespace, and clarity.
• 2 Included icons to represent all check-ins that occurred within the same day for quick accesses, and review, reducing the need to return to the mood-views log page.
• 3 Relocated temporal navigation to create more whitespace for mood summaries and redesigned the “current day” marker for clearer orientation and reduced confusion.

Users can check in with their emotions both before, and after they eat their meal, according to detected patterns, or preferences.

• 1 Emotional check-in flow has two primary pathways of reflection. One for ease of use, and speed, the other for detailed, exhaustive entry.
• 2 Quick check-ins offer users a set of keywords to choose from, helping them create a pattern of responses the system can analyze to surface insights about their emotional trends over time.
• 3 Check-in process results in immediate feedback, based on in app pattern recognition

Users can reflect on their patterns with ease inside the journal.

• 1 Shows a summary of users mood at the time of entry
• 2 Key words, help to act as tags, both for system sorting, and at a glance review
• 3 Associated meal entries are located at the bottom of each check-in summary, with their macro nutrient breakdown for quick assessment.

Post check-in insights are immediate, actionable, and clear.

• 1 Post check-in flow starts with a general summary, and trend analysis of user input to provide clarity on temporal patterns, based on reported nutrient intake, and mood.
• 2 Experience is optimized for clarity and progressive disclosure. Users are prompted to explore the data behind their insights in the event of further curiosity
• 3 Figure+ system is built to listen, look for patterns, then highlight connections, provide suggestions when relevant, and inform users on potentially linked factors across the interplay of their mood, and health.