Eaty
A taste-matching food review app for Chinese New Yorkers.2025
Product Design (UX/UI)
Mobile App Prototype
Eaty is a food review community designed for Chinese New Yorkers to quickly find reviewers who share similar taste preferences — and discover restaurants that actually match what they like.
Product Design (UX/UI)
Mobile App Prototype
Eaty is a food review community designed for Chinese New Yorkers to quickly find reviewers who share similar taste preferences — and discover restaurants that actually match what they like.
Problem Statement
As a Chinese New Yorker, I’ve found it increasingly difficult to get reliable food recommendations from existing apps. Back in China, I often used Dianping and Xiaohongshu to decide where to eat. After moving to New York, I still rely heavily on Xiaohongshu for “Chinese-friendly” suggestions—then switch to Google Maps to confirm the address, distance, and ratings. But this two-app workflow is exhausting, and the content itself can be overwhelming: there are too many posts, too much hype, and many highly polished reviews that feel sponsored or influencer-driven. Often, food looks amazing online but turns out to be disappointing in real life.
More importantly, taste is personal—and cultural context matters. A comment like “not too spicy” might still be unbearably hot for someone else, and a review saying “not sweet” can still taste overly sweet to me. Many posts also stay vague, focusing on general impressions rather than specific flavor details. Meanwhile, most platforms still organize discovery by star ratings or cuisine type—not by taste profile. When I’m craving something specific (spicy, sour, not greasy, or comfort food), it’s frustrating that I can’t filter quickly and confidently based on what actually matches my taste.
More importantly, taste is personal—and cultural context matters. A comment like “not too spicy” might still be unbearably hot for someone else, and a review saying “not sweet” can still taste overly sweet to me. Many posts also stay vague, focusing on general impressions rather than specific flavor details. Meanwhile, most platforms still organize discovery by star ratings or cuisine type—not by taste profile. When I’m craving something specific (spicy, sour, not greasy, or comfort food), it’s frustrating that I can’t filter quickly and confidently based on what actually matches my taste.
Target users
Chinese New Yorkers who:
- rely on photo-driven discovery (often from Xiaohongshu), then double-check location/ratings on maps
-
want trustworthy, culturally relevant reviews
- need to decide fast (often within minutes), especially when hungry or meeting friends
Research
I conducted interviews with Chinese New Yorkers to understand how they discover restaurants on Xiaohongshu and verify decisions with Google Maps (location, distance, ratings). I then synthesized repeated quotes and behaviors into an empathy map (Says/Thinks/Does/Feels). Notes are color-coded to group recurring pain points into key themes, which informed the insights below.
Key insights
Information is scattered across appsChinese New Yorkers often discover restaurants on Xiaohongshu (photo-first posts), then switch to Google Maps to verify location, distance, and ratings. This back-and-forth creates friction and decision fatigue.
Trust is cultural and regional—and built through “people like me.”
For Chinese New Yorkers, “people like me” often means coming from the same hometown (province/city). Because regional flavors in China vary widely, what counts as “mild,” “salty,” or “authentic” can differ by region. When content feels influencer-driven, users rely even more on reviews from people who share both their hometown and similar taste preferences.
Taste language is subjective, so generic reviews don’t help decisions.
“Not spicy” or “not sweet” means different things across people, and many reviews stay vague.
Speed matters: decisions should happen within minutes.
Users want to avoid wasting money on bad meals and reduce decision fatigue—especially when eating with friends.
Personalization is missing in existing platforms.
Current apps sort by cuisine or star ratings, but don’t tailor results to individual taste preferences.
User Journey Map
Restaurant Search and Dining JourneyCompetitive Research
Design Goal
Help Chinese New Yorkers quickly find restaurants that match their taste—by reducing app-switching and highlighting reviews from people “like me.”
Solution in one sentence
Solution:
Eaty matches users by taste profile and hometown (province/city), then uses that match to rank posts and restaurants—so recommendations feel personal, fast, and culturally reliable.
Information Architecture
UI Overview
Key Features
How Eaty Builds Your Taste Profile
Hometown + “Similar Taste Region” (Trust & Matching)
Eaty shows a user’s Hometown (where they’re from) and lets them choose a Similar Taste Region (the regional flavors they identify with). This strengthens the “people like me” signal: users can trust reviews not only from the same hometown, but also from people who share similar regional taste preferences—especially important given how much flavors vary across provinces and cities in China.
It also supports users whose preferences don’t match their hometown (e.g., born in Dalian but prefers Hunan flavors).
It also supports users whose preferences don’t match their hometown (e.g., born in Dalian but prefers Hunan flavors).
Taste-Based Personalization (Taste Profile)
Users set a simple taste profile (spicy / sweet / salty / sour / umami + cuisine/dish preferences). Eaty then prioritizes posts and restaurants that align with those preferences.
Standardized Taste References (Comparable Preferences)
Users set a simple taste profile (spicy / sweet / salty / sour / umami + cuisine/dish preferences). Eaty then prioritizes posts and restaurants that align with those preferences.
Standardized Taste References (Comparable Preferences)
Taste labels like “mild” or “light sugar” are subjective. To make preferences easier to compare, Eaty uses familiar chain brands as taste anchors—for example, Haidilao as a spice-level reference and Heytea as a sweetness reference. This helps users quickly understand whether another person’s taste is similar to their own.
Flexible Browsing Modes
Discover, Your Way
Eaty supports three browsing modes so users can explore in the way that feels fastest.
Eaty supports three browsing modes so users can explore in the way that feels fastest.
Customizable Card Display
Display Options for Faster Scanning
To speed up decision-making, Eaty lets users customize what appears on each post card. In Options, users can toggle key signals—such as Taste Match (similarity %), Hometown, price, rating, and distance—depending on what they care about in the moment.
(The example shown is with all options enabled.)
Advanced Filters
Eaty provides additional filters—such as price, taste match (similarity %), hours, cuisine, and hygiene—so users can narrow results quickly without leaving the feed.
Active filters are surfaced as quick chips at the top, making it easy to adjust on the fly.
Active filters are surfaced as quick chips at the top, making it easy to adjust on the fly.
From Post to Restaurant
Taste Tagging on Posts & Dishes
Posts include lightweight taste tags (spiciness, sweetness, saltiness, sourness, umami). Users can tap on dish hotspots to preview taste levels—making it easier to predict flavor before visiting.
Quick access to restaurant info
Each post includes a restaurant info card at the bottom. With one tap, users can jump into the restaurant page to see key details and browse more posts from other users about the same place—connecting community stories with practical restaurant information in one flow.
Each post includes a restaurant info card at the bottom. With one tap, users can jump into the restaurant page to see key details and browse more posts from other users about the same place—connecting community stories with practical restaurant information in one flow.
Find Your People
Community (Taste-based groups)
Community includes Similar Taste, Following, and Groups.
In Groups, users can browse different taste-based communities and join the ones they relate to. After joining, they can view food posts shared by other members, making it easier to discover restaurants through people with a similar taste background.
Build Your Own Quick Filters
Search
Users can customize quick filter tags. These tags appear on the Search screen for one-tap filtering and faster results.
Revisit Your Favorites
Collections
Revisit saved posts and restaurants.
Revisit saved posts and restaurants.