Todelli AI Advisor – Nutrition Intelligence + Commerce Integration
I led the end-to-end service and product design for Todelli’s AI Nutrition Advisor, creating a new contextual nutrition-intelligence experience linked directly to commerce.
Approach
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Defined the core user scenarios, mapped the end-to-end journeys, and shaped how the AI advisor progressively comes to life within the existing platform and later as a standalone agent. I conducted research, validated behavioural insights, and translated them into a personas and user scenarios, plus an initial concept protoype that was further tested with the target audience. The result was clear user driven feedback for a scalable personalised nutrition and shopping solution.
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Macro Trends Supporting the Proposition
Shift toward organic, clean-label, plant-based diets
Studies across 2020–2024 show:
Significant rise in positive sentiment and consumption of organic foods, expanding from niche to mainstream.
Post-COVID populations demonstrate higher interest in food safety, nutritional value, and ethical sourcing.
Demand for clean-label, plant-based alternatives, and functional foods continues to grow year-on-year.
Growing desire for transparency & contextual nutrition guidance
Consumers increasingly want:
Ingredient clarity
Sustainability and ethical production information
Personalisation based on goals (energy, gut health, hormones, longevity)
Commerce gap
No major nutrition platform currently:
Provides contextual nutritional advice at the moment of product discovery, AND
Links that advice to shoppable products / personalised baskets / recommendations.
This unmet need creates a commercial opport
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Information Overload
Organic, plant-based and functional foods come with complex claims. Users struggle to understand:
What’s good for their body
How to evaluate quality and processing
What aligns with their goals (gut, hormones, energy, inflammation, weight)
Fragmented Tools
Current solutions are either:
Diet apps (calorie trackers, food journaling)
One-dimensional wellness tools (gut or hormone focus)
E-commerce stores lacking nutrition guidance
Nutritionists who are expensive or inaccessible
No solution connects:
Real-time nutritional context with personal advice and purchasing.Loss of Consumer Trust
Packaging claims are confusing; many wellness brands overpromise.
Users want a trusted, evidence-based advisor, not another marketing engine. -
A conversational AI agent that delivers:
Contextual Product Intelligence
When browsing food items, users receive:
Ingredient clarity
Health impact explanations
Sustainability and ethical insights
Nutritional comparisons
“What this means for you” advice
Personalised Guidance
The agent can answer:
“Is this good for my gut?”
“What can help balance hormones?”
“Compare this kombucha to that probiotic drink.”
“Create a weekly plant-based, iron-rich plan.”
Commerce Integration
Seamlessly connects recommendations to:
Todelli marketplace products
Personalised bundles
Smart substitutions
Automated shopping lists
Phased Product Evolution
Phase 1 — Embedded Advisor
Integrated into existing Todelli app/website, supporting browsing.Phase 2 — Proactive Scenarios + User Journeys
Advisor initiates help based on user context (e.g., scanning a product, searching for recipes).Phase 3 — Standalone AI Agent
Independent, conversational experience: talk, write, ask anything nutrition-related.
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Objectives
Validate user desirability
Validate willingness to pay
Identify top use cases
Proven ability to drive higher conversion
Measure trust and perceived value of AI guidance
Testing Components
Interactive Prototype Testing
With 20 nutrition-passionistas (completed)Live Experiment Inside Todelli Platform
Limited AI advisor access to 10–20% of users.A/B Tests
AI vs no AI on:Product understanding
Conversion to purchase
Time spent
Basket size
Qualitative Interviews
Understanding emotional trust factors & psychological value. (Complete
Success Metrics (KPIs)
+15% product discovery-to-purchase conversion
+25% engagement time
40%+ willingness to pay for subscription features
60%+ trust score in AI explanations
Top 3 high-value user scenarios identified
Outcome of Phase 1:
Green-light for robust development & investor pitch with validated metrics.
Target Audience
Primary: “Nutrition-Passionistas”
Age 25–54
Strong interest in clean eating, plant-based lifestyles, organic produce, sustainability
High digital adoption
Willing to pay for quality products
Seek personalisation, learning, and convenience
Secondary: “Wellness-Motivated Mainstream Consumers”
Occasional organic buyers
Curious about functional foods
Need help navigating claims and brands
Personas & User scenarios were developed in remote co-creative workshops along with the rest of the team post research.
Visual concepts and prototyping
I used Figma and UX Co-pilot to bring the concept to life and create a quick prototype (for core user scenarios) that was tested with our target audience. Based on the insights we amended the following:
Shift from open-ended chat to:
Quick-select buttons
Pre-filled prompts
Why
Users who tested the early chat prototypes said:
“I’m not sure I would always know what to ask.”
“Sometimes this can feel like work.”
AI responses became
More structured
Shorter
With clear headings (“For your energy goals…”)
Bullet-based rather than paragraph-based
Why
During testing, users often skimmed the replies and miss key info.
Clarity directly impacted trust and perceived intelligence.
