Chapter 1: The Taste That’s Missing
The project began with a challenge from Nourishly, a food-tech company on a mission to make cooking feel intuitive, soulful, and stress-free. Their current app had plenty of recipes, detailed filters, and even shopping list integrations — but user engagement was low. People weren’t coming back.
That’s when the product team asked:
“What if we stopped designing for calories and macros... and started designing for moods and moments?”
That question sparked the beginning of Meal Moodboard — a Pinterest-style experience that helped users discover recipes based on feelings, cravings, weather, or occasions.
what
Over 40% of consumers browse food apps without a clear idea of what they want. Most existing platforms are functional but uninspiring. We saw an opportunity to reimagine this process — making meal planning less about what’s available and more about how you feel.
how
A visual-first, emotion-led recipe discovery and meal planning experience that enables users to explore meals by mood (e.g., comforting, refreshing, lazy night), stack filters like weather, time of day, or dietary preferences, and save vibe-based moodboards for future cooking inspiration.
why
Through a highly personalized onboarding quiz, dynamic mood-based discovery, Pinterest-style visuals, and AI-powered voice search, Meal Moodboard helps users find what they didn't know they craved.
21.4K
weekly active moodboard users
15.2%
weekly
revisit rate
4.8/5
average rating in post-launch surveys
3.4
moodboards saved per user per week
32.7K
total downloads in the first 6 weeks
Project Scope
“I didn’t expect an app to actually match how I feel. This felt like a friend suggesting something.”
— Eric, 29
“After a long day, I don’t want to think — I want something warm that feels right. This app just knew. It’s like self-care in recipe form.”
— Sarah, 39
“It’s like Spotify Wrapped, but for how I eat when I’m emotional — I love it.”
— Tasha, 20
“I usually give up halfway when I search for recipes. This made it fun and oddly calming.”
— Jai, 27
We kicked off with the Hero Flow — how a user discovers a meal based on how they feel. Each touchpoint was mapped to mood, weather, occasion, and craving.
Emotion and Mood Shape Food Choices Users instinctively choose meals based on feelings, context, and mood, not just ingredients or diets.
Visual & Sensory Discovery is Crucial Aesthetic, vibe-based exploration engages users far more than traditional recipe lists.
Time, Energy, and Simplicity Drive Decisions Quick planning options and low-effort meals are essential, especially for busy or fatigued users.
Dynamic Mood-Based Filtering Feels Natural Stackable, mood-first filters (like “Cozy + Quick” or “Light + Post-Yoga”) align with how users think and choose meals.
Sarah – The Emotional Eater
A working mom who craves meals that comfort and energize depending on her day.
Sarah – The Emotional Eater
A working mom who craves meals that comfort and energize depending on her day.
Leo – The Foodie Mood-Surfer
An art director who chooses meals based on mood, music, and occasion. Loves sharing moodboards.
Ananya – The Wellness Minimalist
A tech consultant who wants meals that feel light, healthy, and calming after screen-heavy workdays.
Method: Open Card Sorting Tool: FigJam Participants: 14 users (mixed ages 20–45, casual home cooks and food lovers) Duration: 30–40 minutes per participant
Ananya – The Wellness Minimalist (Persona 3)
Profile: 31, software engineer, lives solo
Goals: Energy maintenance, low-prep, clean eating
Leo – The Vibe-Surfer Foodie (Persona 2)
Profile: 29, art director
Goals: Cooking for pleasure, emotional expression through food, prefers aesthetic meals
Sarah – The Emotional Eater Mom (Persona 1)
Profile: 38, full-time working mother of two.
Goals: Quick, comforting meals that are kid-friendly and emotionally grounding.
We spoke to 20 users
Total Participants: 20 (diverse in age, lifestyle, cuisine preference)
Locations: Australia, India, USA (Remote testing, timezone-aware)
My Role
Led UX research
Developed Visual Design, Wireframes, Prototypes.
Duration
Our MVP launched across mobile and web over the course of 6 months, in collaboration with engineering, research, and design system teams.
“Redesigning Recipe Discovery with Emotion”
— Nourishly - Meal Moodboard
We began by investigating why people struggle with recipe planning. We came up with some important questions that can lead to identify the problem space.
Research Questions
1. How do users decide what to eat when they’re not craving something specific?
2. What emotional, contextual, or environmental cues influence meal choices?
3. How do current recipe discovery tools support or hinder this journey?
4. Can mood-based filtering enhance user satisfaction and decision speed?
Chapter 2: Problem Space Indentification (UX Research)
Competitive Analysis
We compared 8 apps across emotional inspiration, filtering depth, and personalization. Pinterest led in inspiration, while Yummly, NYT Cooking, and Whisk offered structured flows — but none combined emotion + utility.
Mood Journaling Exercise
Duration: 3 days
Method: Daily logs captured via WhatsApp check-ins or mobile journaling prompts.
Focus: Mood before eating, cravings, weather context, time of day, food choice, and rationale.
Card Sorting for Mood-Based Meal Filters
Research Goal:
To understand how users categorize emotional and contextual “moods” related to meals — in order to shape the information architecture (IA) and filter taxonomy for the Meal Moodboard app.
User Definition
We created three core personas based on research:
I created a user journey map to better understand the user needs
Key Insights
Chapter 3: Designing The Solution
Wireframes
We developed mobile-first wireframes followed by responsive web layouts. Key elements included:
1. Moodboard Home: Choose a vibe — “Comforting,” “Adventurous,” “Lazy evening,” etc.
2. Smart Stacks: Combine filters like Rainy + Solo Dinner + Spicy
3. Voice Input: “What should I eat when I’m sad but still want protein?”
4. "Why this recipe?" tags: Contextual nudges like “Perfect after a breakup” or “Best shared with friends”
5. Save by Mood: Instead of folders, users could save meals to “Crave Later” boards like “Rainy Nights” or “Quick Wins”
Prototype
Launched as a cross-platform MVP (mobile + web) integrated with existing CMS and catalog systems. Collaborated with two other teams: Search & NLP for voice input, and Personalization for dynamic mood curation.
Key Features
Mood-based discovery
Daily “Vibe Meals”
Save to moodboards (e.g. “Monsoon Magic”)
Voice search (“What should I eat when I feel lazy but spicy?”)
Occasion bundles (“Movie Night Meals”, “Feel-Better Soups”)
Chapter 4: User Testing
The team ran moderated and remote tests with 20 participants, focusing on:
-
First impressions
-
Mood-matching accuracy
-
Save rate vs traditional filtering
-
Emotional engagement
Impact
Customer Retention
Upcoming Updates
🧑🤝🧑 Collaborative moodboards
🗓️ Mood-based meal planning calendar
🧘 Wellness tracking through food + emotion
🎤 Full voice-only meal planner mode
Chapter 5: Reflections
Meal Moodboard helped us prove that food apps can be more than utility tools — they can be emotional companions.
We didn’t just help people cook.
We helped them feel understood.
Maitri Bariya
Home
About
Work
Creations
