Embedded Files
Food Discovery App
Relishious - 2015
Client
Hibrise
Project
Mobile App Design
Type
New Product
Created
2015
Team
Size: 3
Concepts Used
UX Techniques
Requirements validation, Rapid wireframes, Information Architecture
Design Principles
Cognitive Load, Hick's Law, Pattern Matching, Progressive Disclosure
Contribution
Role:
Principle UX Designer
Contribution:
#mobileapp #uxdesign #uidesign #branding #marketing #principledesign #designnops #videodirection
Objective
To design a food discovery app
Challenge
To many players in the food app market
Approach
1
Requirement Validation
2
Competitive Analysis
3
Wireframe Prototyping
4
Visual Design
5
User Testing
6
Handover To Dev
Competitive Analysis - outcome
All competitors were focusing on restaurants and not food
There was no way to find list the popular food items in any category
No personalized diet related choices
Challenges
Photography of the actual dishes served
Most restarants dint cooperate for a photoshoot, we got only one chance to take a pic, just before the dish is served.
Consistant quality affected when the cooks change.
This could never be mitigated. But letting the customers know and the rating of the corresponding dishes had to be reset to be zero. A sudden drop in quality review would indicate the same.
Few Notable Problems & Solutions
a
Problem
Recommend dishes that suites the preference of customer while assuring them of maintaining privacy
Solution
Letting users save diet and food type preferences locally on device and not on the cloud.
b
Problem
Persuade customers to share dish reviews in an restaurant.
Solution
Keeping it short and simple by using an interface that uses short interactions and reduces the need to type (which is a difficult task)
c
Problem
Finding dishes that match multiple criteria, like classification of dishes, cooking methods, and personal preferences like taste, diet, health, budget, and distance.
Solution
A unique UI that lets users preview results as they search and apply filters was designed. It is powered by a complex algorithm that not only shows results based on users filters, but it also considers personal preferences, like health data (allergies, and diet restrictions) and displayed chronologically based on rating, recommendations and discounts too!
The customers would also be able to manual check the Ingredients and calories of each dish by clicking on the dish thumbnails.
Conclusion
Managed to create by maintaing the same base prompt but ...
We were only 80% sucessfull in maintaining the cossistant lok of the charactor
For the completeness of the product and also to test the maximum level of interaction possible in figma, a simple game was built.
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