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UberEats

UberEats is the most popular food delivery platform, with 66 million users worldwide. It controls about 29% of the food delivery market, and it generated about $8.3 billion in revenue in 2021. Its mission is to make getting food from local restaurants easy and effortless. While it has grown into a huge corporation since its launch in 2014, it faces competition from other nationwide food delivery services. Its business goal is to retain its consumers through an enjoyable yet easy experience. However, the simple process of ordering food online can become convoluted with the numerous options of food. As the market continues to expand at an estimated 15.4% annual growth rate by 2025, UberEats needs a way to tackle the paradox of choice to make the app effortless to use.

ROLE

UX/UI Designer, UX Researcher

TEAM

N/A

DELIVERABLES

Storyboard, user survey, persona, journey map, secondary research, usability test, wireframe, prototype

DURATION

Mar 2022 (3 weeks)

Goal

To retain users on Uber Eats by helping users save time on making decisions

The dilemma: Why is it hard to choose?

Making choices can be a struggle. Picture this: 

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Paradox of choice comic strip

Looks familiar? This is an example of the paradox of choice or Hick’s Law. As the number of stimuli or choices increases, the longer it takes the user to make a decision. We’re tempted to evaluate all our options before making a choice in order to maximize the value and reap the best possible outcome. While doing so, we’re limited by our time and budget and may face anxiety as a result. 

The Process

I conducted external research on the company and ran a competitive analysis to find improvement opportunities. I proceeded to survey and interview users to identify pain points. After determining users' behaviors and preferences, I ideated solutions to solve the problem. I created paper wireframes, low-fidelity prototype, and a high-fidelity prototype. I completed 2 rounds of usability test, and iterated my design.

Competitive Analysis

Since there are abundant food delivery services, I conducted a competitive analysis to compare competitors and address gaps and improvement opportunities. UberEat’s top direct competitors were Doordash and Grubhub. Meanwhile, Yelp acts as the indirect competitor. 

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Present and absent features in direct competitor apps

I compared the features, visual layout, and user flow of each platform, and noted what they all had or lacked at a glance. Since the goal mainly focuses on the beginning of the user journey, I specifically examined the strengths and weaknesses of their home, search, restaurant, and menu pages in greater detail. I found that the largest gap for UberEats, compared to its competitors, is the lack of reviews.

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Strengths and weaknesses in direct competitiors

Understanding the User

To better understand the users, I surveyed over 20 people within different age groups and interviewed 6 people on the way they interact with UberEats and other food delivery apps, their preferences, and their decision-making process. The findings supported the paradox of choice:

  • About 88% of the participants expressed that browsing for what to order took the most time when using the app. 

  • About 50% of the participants stated that it takes them typically 10-20 minutes to decide what to eat, in general.

  • About 33% of interviewees voiced that they could better decide after getting inspiration.

  • The top 2 factors that impact their decision were budget and recommendations from others.

 

"I like seeing food with pictures because it's easier to imagine

if I'm feeling it or not."

​

Although food delivery apps give users freedom to choose from a variety of food options, the surveys indicate that users need a solution that can facilitate their decision-making and save them time.

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User persona

Jesse represents the target demographic gathered from the surveys. She is a busy person who needs a quicker way to decide what to eat because too many options overwhelms her.

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User journey map for ordering food on UberEats app

Users exprience pain points when they are browsing through the UberEats app and adding dishes to the cart.

Sketching the solutions

After hearing what the users prioritize when selecting their meals in the app, I ideated a few solutions to answer HMW questions: “How might we narrow down the options?” “How might we help users make better choices?” “How might we make deciding fun instead of stressful?”

I ultimately narrowed down my ideas to 2 solutions:

  1. Uber Decks: This is a new feature that creates a visual way to search for food by swiping on cards. It reveals a selected number of dish options, specially curated for the user based on algorithms (ex. order history, favorites, shares). Visual stimulation evokes strong emotions that lead to action-taking. For instance, one study implicated that salad consumption among kids increased by 90% when their cafeteria's digital menu had a rotating image of salad. These visual card suggestions can help users become more certain in their choices and save time by looking at dishes instead of restaurants first.

  2. Reviews:  Based on the competitive analysis and user surveys, people weigh in recommendations from others for decisions. Having restaurant reviews can, thus, give guidance and help people make decisions within the app without looking on google to learn more about the restaurant.

“You respond to the image on the display like you would respond to a plate in front of you." 

Refining the design

I conducted a usability test on each lofi and hifi prototype. They were asked to complete a few tasks, such as find the restaurant Thai Villa and read what others are saying about it and explore the UberDecks feature.

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Here are the significant findings from study I (lofi):

  • 1 out of 5 participants went to the “Browse” page and could not find the new feature.

  • 2 out of 5 participants conveyed confusion when they only saw 1 card out of the deck.

  • 1 out of 5 participants did not know what “Upvoted” meant.

​

Here are the significant findings from study II (hifi):​

  • 3 out of 4 participants expressed that they would likely order something within 8 cards.

REVISIONS TO UBER DECKS

Based on feedback from participants, these were the most important changes that were made to the Uber Decks feature:​​

  • Adding Uber Decks to the browse page: Originally, the feature was only included in the home page, as majority of the participants in the survey responded that they would scroll on the home page of their app and scroll endlessly to find a restaurant. However, not all users start at the homepage to look for food, as demonstrated in the test, so I integrated the feature on the browse page as well.

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  • Including gesture indicators: Although the introduction of the feature has instructions on how to use the deck, users needed clearer indicators. I incorporated cues to nudge the users to swipe left to see the next card or right to go back to the previous card.

  • Limiting the number of cards to 10: I wanted to limit the amount of cards in the deck because having too many options would be counterintuitive. In the test, I had 18 cards for users to interact with. The highest chosen dish was the 12th card, but the majority of the participants chose a dish within 3-8 cards.

BEFORE USABILITY TEST I
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AFTER USABILITY TEST II

Limited cards to 10 to reduce information overload.

Added cues to nudge users to swipe to the next card

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REVISIONS TO REVIEWS

Based on feedback from participants, these were the most important changes that were made to the restaurant review screens:​

  • Changing the wording in filters: I altered the phrase “Most upvoted” to “Most helpful” in the filters of the reviews to help the users understand the function of liking a review better. 

  • Making the search bar more on-brand: I cleaned up the search bar in the review section to look more similar to the search bars found in the app.

BEFORE USABILITY TEST I
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AFTER USABILITY TEST II

Combined search CTA and filters to match UberEats' style

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Users can like review if they find it helpful

Final Screens
FILTER THE DECK
CUT TIME IN SEARCHING

Users can edit price range and dietary restrictions

[

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Clear visual communication to appeal users

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Search CTA helps user look for similar food to dish suggestion

SEE WHAT OTHERS SUGGEST
SORT THROUGH REVIEWS

Users can look for comments on specific dishes

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One-click button to order the same dish as reviewer

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Putting it together
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UBER 
DECKS
REVIEWS
Takeaway

Adding Uber Decks and restaurant reviews to UberEats can make people more confident in their choices, so they feel less overwhelmed by paradox of choice. Participants in the study stated that they would recommend and use Uber Decks and restaurant reviews to aid their decisions. However, the sample deck used in testing is not tailored to each participant, so more testing needs to be done after development. Time on task and conversion rates are important KPIs that can provide a better attestation to its success. If users spend less time to decide and don’t abandon their search or switch over to another app, then the goal is achieved.

Next Steps
1

More research needs to be done with a larger sample size of participants to find the best number of dish options or cards to include in the deck.​

2

Curate Uber Decks even more to the user through a more advanced algorithms, filters, or lightning round questionnaires.

Reflection

Making changes to a well-known app was difficult because there will be more critiques. However, there is always room for improvement and new ways to solve problems as people and technology evolve. One lesson that I’ve learned from this study is to design with intent and not through arbitrary means. There should always be an explanation to the smallest design details, even down to the loading page.

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I’ve also learned to focus on one problem at a time before expanding it. When I was thinking of solutions, I thought of creating a group poll feature that could aid in making group decisions. While group decisions is another interesting topic to tackle, it requires a different set of research questions and approach. The feature could be nice to have, but it didn’t fit the main problem at hand. 

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👋 Hope to hear from you soon!

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