Project Overview
Context
UberEats Health Mode
Enhancing UberEats’s experience for fitness and diet users.
My Role
User Research, Wireframing, Visual & UX Design, User Tesitng, Documentation
Timeline
4 weeks
Problem
Project Type
Class Project
Team
UX Design, UX Research
This project is created at a Communication Design Studio class at Parsons School of Design. For the project, we were asked to choose a digital product and optimize its experience for an existing subgroup of users or a new target user group.
In our preliminary research, we discovered that:
Many diet and fitness users avoid delivery apps like UberEats because they often struggle to find dishes that meet their nutritional goals. How can we improve their user experience?
UberEats Health Mode, is a feature we designed for UberEats that optimizes the food delivery experience for fitness and diet users.
Solution
Our solution is UberEats Health Mode, a feature that addresses multiple pain points a fitness/diet user struggle with when using UberEats. Here is a quick view of the impact:
100%
accurate task completion in final navigation testing
90%
user conversion rate in final survey with 20 target users
95
Overall customer satisfaction score (CSAT)
Solution preview
This is a quick preview of our final solutions and features. Scroll down for design process.
Health Mode Filter
Pain Point
Diet users do not want see unhealthy options that can throw them off their diet.
Solution
A health mode that, once turned on, filters out the restaurants automatically based on the user’s personalized diet preference.
Prioritizing Dishes in Display
Pain Point
Diet user often care more about the specific dishes from a restaurant than the restaurant itself.
Solution
Instead of the old restaurant banner image, we replaced it with a scroll of top health dishes from the restaurant.
Calories and Macro Info
Pain Point
Diet users wants to know the calories and macro nutrient on each dish.
Solution
Calories and macro nutrient information displayed for every dish, with daily nutritional goal tracking.
Customized Diet Preference
Pain Point
Users want to stick to their personal health preferences with ease and convenience, even when using delivery apps
Solution
When activating the Health Mode feature, each user will complete a survey to generate a personalized diet preference, with the option to import data from other nutrition apps into UberEats
Streamlined Nutritional Tracking
Pain Point
Diet users want to keep track of their daily nutritional intake with delivery orders.
Solution
Users can monitor their calories and nutrition intake for each order, as well as to view these intake next to one’s calorie goals on nutritional apps like MyFitnessPal.
Design Process
Research
Problem Statement
User Survey
Survey Findings
Journey Mapping
User Pain Points
Define
Feature List
User Persona
Competitive Analysis
Design
Wireframing
Prototype
Test & Iterate
Final prototype
Next Step
Reflections &
Learnings
Research
Problem Statement
User Survey
Survey Finding Summary
To better understand diet users’ struggle with delivery apps like UberEats, We created a typeform survey targeted at 30 fitness enthusiasts and health conscious eater who follow a regular health diet.
80%
of these users preferred to cook at home or subscribed to a diet meal plans in order to follow their diet.
Among them, these are the three main information 94% of diet users would require to follow their diet.
How can we improve Uber Eats’s ordering experience for fitness and health diet users?
Sample questions and responses from survey
77%
of those diet eaters have avoided ordering takeout for lack of calorie count and distraction of unhealthy options.
97%
of them express an interest in seeing calorie count and macro listings in delivery apps.
More Research
Journey Mapping
Pain Points & Opportunity
To better understand our target user’s current experience with UberEats, we created a journey map based on our interview data.
This allowed us to identified key user pain points and areas of improvements.
We identified these key user pain points. Once we articulated these problems, it was relatively intuitive to develop solutions for each of them.
Diet user care about specific dishes more than restaurants
They get easily distracted by unhealthy options
It is hard to find dishes that meet their specific health requirements, for example, for users who are on a Keto diet or a low sodium diet.
Users had to manually look up calorie counts and macro info.
Based on our previous research, we narrowed down our target user to a more specific persona. This will guide us through upcoming design decisions and help us recruit the exact user group for our testing.
User Persona
Define
Feature List
Competitive Analysis
We developed a preliminary list of features/solutions in response to each user pain point.
With the preliminary solutions, we can situate Uber Eats health mode against its competitors from adjacent market such as diet-focused prepared meal kits.
This helps us to identify the business incentive and potential market opportunity in developing this feature, if we were to present this to stakeholders.
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A health mode that, once turned on, filters out the unhealthy, junk food restaurants based on the user’s personal health preference and a database of user-generated health ratings for each restaurant.
Calories and macro nutrient information displayed on the dish page. These data can be pulled from a existing nutritional database such as Nutritiontix.
The ability to monitor one’s calories and nutrition intake for each order, as well as to import these data into apps like my FitnessPal.
Add a scroll of suggested health dishes on each restaurant’s info page.
A survey that helps determine the user’s personal diet preference. This feature needs further validation in first round of testing.
As a feature, UberEats Health mode is targeted at users who can afford the higher cost of a meal delivery, but want to access the higher level of convenience, on-demand dish diversity and freshness on a delivery app, compared to a pre-made meal service.
Design
Initial Wireframes
Testing round 1
Testing feedback
Mid-fid prototype
Survey page flow
Ordering flow in health mode
Check out flow
Testing round 2 feedback
Final Prototype
Final Testing Results
A 2-hr in-person user test with 20 target users who fall into our exact user type on our low-fid wireframe brought us the following feedback for our next iteration.
Based on the user responses to our wireframes, we updated the design and validated some assumptions we had about features. We decided to follow through with a key feature: a survey that helps us determine the users’ exact diet preferences. Our goal is to incorporate these features without disrupting UberEats’ existing functions and layout.
Health mode toggle should be automatically turned on after survey to encourage usage.
Ordering page nutrition info still looks like buttons
Add/minus quantity button is confused as a part of special instruction
Nutrition information feels out of place after checkout. It would be better to incorporate it into cart page.
100%
accurate task completion in final navigation testing
90%
user conversion rate in final survey with 20 target users
95
Overall customer satisfaction score (CSAT)
Final Video Prototype
Reflection
If we have more time…
Learnings
We would brainstorm more solutions and spend more time evaluating each solution based its impact vs. effort in a business context.
Consider how this feature can be expanded to target not only at fitness diet users, but also users who follow specific diet for medical reasons.
As the health filter is dependent on the user’s health rating, we would develop a more complete flow of what kind of review data we need from the users, how we can incentivize them to input these review/rating, and how these data can be applied on the back-end to create more personalized health dish suggestions.
Prototyping and testing can inform intuitive solutions and validate assumptions about a solution.
How to narrow down our target user as we explore the business potential and opportunities of our solutions, which helps us to fine tune our solutions in later iterative process.