The project
DishRanks flips restaurant discovery: instead of asking which place is good, it tells you which dish to order. The web app is live at dishranks.app and combines photo-first browsing with lightweight social proof from real diners.
Project goal
Help diners decide what to order in under a minute, and give restaurants honest, dish-level feedback that drives menu decisions.
The problem
Restaurant-level reviews don't help when half the menu is mediocre.
Photos on existing platforms are inconsistent, dim, and rarely current.
First-time visitors waste 10+ minutes scrolling reviews to pick a dish.
Restaurants lack feedback on which specific dishes are loved or skipped.
The solution
01Dish-first browsing with a ranked, photo-led feed per restaurant.
02A 10-second review flow that captures score, photo, and one short note.
03Smart sorting by 'must-try', 'safe pick', and 'skip' badges.
04A restaurant dashboard showing dish-level trends over time.
Research & discovery
- Surveyed 180 diners about how they choose what to order.
- The most common answer, by a wide margin: 'whatever the table next to us ordered.'
- Diners trusted photos far more than star ratings.
- Tested 4 review-entry flows; the 10-second flow had far and away the highest completion.
Personas
Tom, 28
Curious diner
Goals
- · Try the best dish first time
- · Avoid disappointment
- · Share finds easily
Pain points
- · Endless menus
- · Generic reviews
- · Stale photos
Lina, 34
Restaurant owner
Goals
- · See what's working on the menu
- · Hear honest feedback
- · Promote signature dishes
Pain points
- · No dish-level data
- · Slow feedback loop
- · Anonymous criticism
