Visualizing a Revolution in Restaurant Tech

FoodMood is a B2B SaaS platform launching in Lebanon, built to solve "menu paralysis" and "restaurant data blindness." This infographic analyzes the core components of their business plan, from the proprietary algorithm to the strategic growth and financial projections.

The Tri-Fold Crisis: Indecision, Blindness, and Generic Upselling

FoodMood's value proposition is built on solving three critical, intertwined inefficiencies in the dining industry.

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1. Customer Stress & Choice Overload

Diners face "menu paralysis" from excessive choice, leading to stress, regret, and low loyalty. This indecision costs restaurants valuable time and reduces order accuracy.

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2. Restaurant Data Blindness

Restaurants know *what* sells, but are blind to *why*. This lack of motivational data prevents true personalization.

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3. Ineffective Generic Upselling

Staff and static digital menus rely on generic prompts ("Add fries?"). This practice has a low conversion rate and fails to drive high-value, emotionally congruent purchases.

The FoodMood Workflow: 5 Steps from Scan to Sale

The core user journey, demonstrating the frictionless, personalized data capture and recommendation process.

1. Greeting & Start

FoodMood Welcome Screen

Customer scans the QR code and is greeted by "Moody" to begin the experience.

2. Restaurant Integration

Restaurant Welcome Screen

The app seamlessly integrates with the restaurant's identity (e.g., "I'm from babel").

3. Emotional & Functional Filtering (IP)

Mood and Dietary Selection Screen

The user selects mood (IP capture) and dietary needs (functional filter) to narrow the menu instantly.

4. Recommendation & Upsell

Recommendation Results Screen

Top dishes are presented with **emotional tags** (e.g., 95% Match) to drive conversion and ACV.

5. Closed-Loop Feedback

Customer Review Screen

Post-meal feedback provides **algorithm validation** (Proof of Congruence) for continuous improvement.

Inside the Algorithm: The Science of Psychological Nutrition

The core IP is the "Nutritional Psychology Mapping Algorithm" validated by expert Marielle Mansour. It maps ingredients to psychological states.

Mood Intensity Rationale (Nutritional Psychology) Example Food Recommendation
Stressed / Anxious High Support adrenal function and reduce inflammation. Grilled Chicken Breast with Leafy Greens
Stressed / Anxious High Provides slow-release carbs for lasting energy and calm. Sweet Potato Mash
Hopeful / Motivated High Omega-3s and protein fuel the brain and body. Grilled Salmon with Quinoa
Hopeful / Motivated High Rich in iron and B vitamins for sustained energy. Spinach

The Investment: $10,000 Seed Round

Capital Efficiency: Incurred Costs ($3,390)

The team has demonstrated exceptional efficiency, building a functional prototype with minimal capital.

Use of Funds ($10,000)

The seed capital is not for development, but for high-impact market entry and sales acceleration.

Financial Projections: 3-Year Growth

The financial model projects profitability by Month 6, driven by scalable B2B SaaS revenue and high-value data.

Future Potential: The FoodMood Ecosystem

The initial SaaS model is the foundation for a much larger, high-multiple ecosystem built on data licensing and a B2C platform.

Phase I: B2B SaaS (1-18 Months)

Establish market dominance in Lebanon. Prove ROI and profitability with 50-150 paying restaurants. Refine the algorithm and analytics dashboard.

Phase II: API Integration (18-36 Months)

License the algorithm via API to major delivery platforms (Toters, Talabat). Shift to a high-margin, low-COGS data licensing revenue model.

Phase III: B2C App (36+ Months)

Launch a standalone B2C application for personalized nutritional coaching, tracking emotional eating habits across all food providers (grocery, restaurants).