Food Recommendations From People You Trust
Design a restaurant discovery experience built around recommendations from known people and clearly explained social context.
The brief
Understand the problem
Background
Public ratings flatten different tastes into one score. A recommendation from someone whose preferences are understood can be more useful, but social signals should not expose private activity or become a popularity contest.
User context
Mei is choosing a quiet place for a client lunch. She trusts two colleagues on food quality and another on accessibility, but their recommendations are spread across old messages.
Product problem
The product must show who recommended a place, why it fits, and how current the information is without implying that every saved visit is a public endorsement.
Objective
Create a trusted-network restaurant search and recommendation detail flow.
What to design
Define the experience
Required experience
- Search with occasion and dietary needs
- Trusted recommendation context
- Save and share a considered recommendation
Screens and states
- Personalized discovery
- Restaurant recommendation detail
- Recommendation composer
Core user flow
Follow the critical path
- 01
Mei searches for a quiet accessible lunch
- 02
She sees matches recommended by colleagues
- 03
She reviews each person's note and visit date
- 04
She saves a shortlist and asks one follow-up question
Product rules
Requirements and constraints
Requirements
- Separate public facts from personal opinions
- Show the relationship and recency behind a recommendation
- Let users control who sees their recommendations
- Support dietary and accessibility filters
Constraints
- A small network may produce few results
- Restaurant details can become outdated
- Private saves must never appear as recommendations
Reality check
States worth considering
Ready-to-use content
Mock data
Use this content to test hierarchy and realistic data states. You can expand it when the concept needs more depth.
Trusted notes
- Lina visited 3 weeks ago: Quiet at noon and good step-free access
- Dev visited 5 months ago: Strong vegetarian menu, book ahead
- Restaurant record updated yesterday: Outdoor seating closed
Finish line
What to deliver
- Three to four mobile screens
- A recommendation card that distinguishes fact, opinion, and recency
If you want more
Optional extensions
Optional direction
Visual resources
Use these as a starting constraint if you want one. They are not part of the required solution.