client

General Assembly UX Design course

Methods

  • User interviews
  • Field studies
  • Competitive analysis
  • Personas
  • Journey mapping
  • Lo- and hi-fidelity wireframing
  • Prototyping
  • Moderated usability testing
  • A/B testing

tools

  • Figma
  • Visily
  • Miro
  • Notably.ai

Year

2024
See prototype

Clean Plate Club

Problem

People, particularly those in the United States, have a tendency to throw away food. In fact, the average American consumer wastes about 1/3 of the groceries that they buy (between 30-40%) every year. As we all know, this is expensive; there are different estimates for the cost of food waste per person, but the approximate value of the food waste in the country as a whole is $218 billion, or 130 billion meals.

Solution

Clean Plate Club is an application that aims to reduce household food waste and save people money by letting them know what they have in their inventory and when it will expire. By having real-time data on food freshness and reminders on when to consume something, users will be more conscientious of their inventory and organized when planning their meals.

Leave no crumb behind.

i. Investigate the current state

interviews

In order to identify why people are wasting food, I had to understand how they are managing it. I intereviewed 6 people using a script with with 12 open-ended questions, focusing on values, motivations, and routines. I conducted the interviews on Notably.ai to more efficiently gather key insights and themes.
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To more accurately identify which common theme (i.e., level of organization, visibility of food) affected food waste, I ideally would have set up the interview to operationalize my findings and do a regression analysis, but there was not a large enough sample size.

Affinity Mapping

I synthesized my interview results using affinity mapping, organizing interview pieces into key themes based on my own analysis and the results of Notably.ai. I used these interview findings particularly in persona building and feature prioritization.

competitive analysis

I then looked into some of the tools that interviewees mentioned they used to meal plan, grocery shop, or otherwise keep track of their food inventory. I analyzed the tools' predominant user bases, desktop and mobile experiences, interactions, navigation, visual design, and copy.

Field Studies

I needed a sharper, more sensitive understanding of user behavior, so I conducted field studies observing how people bought and used their food. I went food shopping with some friends to learn why they choose their food  (i.e.,  intent) and observed when and how they sorted through their refrigerators and pantries to understand how they actually used that food after purchase (i.e., action). This perspective helped me bridge the real world of your refrigerator to the digital world of Clean Plate Club.

ii. Define and distill needs

prioritized user base

With a keener understanding of how people forecast, organize, and use their food, I honed in on a target audience who would most benefit from a food management solution.

I then built a persona based on this audience and used it to guide the development of the customer journey and uncover key features of the solution.

customer journey

At this point, I knew I was creating a solution that allowed people to track the food in stock, but the solution had to go beyond manual tracking and organization - people can already do this on other apps, so what is going wrong with this method? To uncover the heart of the problem, I built a journey map outlining Robin's actions and feelings throughout a week of buying, consuming, and discarding food. I was able to identify where the pain points that caused the most friction were in this process so I could design a relevant, timely solution to the user's problems.

prioritized solutions

I distilled the needs identified from the persona and journey list five core needs that address user problems while still aligning with user values. This enabled me to hone in on features that most effectively alleviated problems that lead users to wasting food.

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Summary of Research Findings

Since the target audience struggles with seeing and remembering what they have in their inventory, the solution should proactively add items to the user's inventory, show real-time data on food freshness, and notify the user of food close to expiration.

iii. Draw it out

Sketches

I drew low-fidelity sketches to map out the prioritized features. I began with core features that addressed the root problem and then supplemented with other features only when there were opportunities for utility improvements.

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Wireframes and testing

Using Figma, I turned my sketches into high-fidelity wireframes and iterated on them until I felt they were ready for usability testing. I conducted 4 usability tests in the first round.
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My previous research indicated a desire for recipe recommendations based on inventory, and I conducted additional usability testing and A/B testing to validate this  addition. I added it based on initial findings but recently removed it due to evolutions in generative AI technology. I've found that users prefer as few applications as possible to manage their needs, and if users can just use their go-to generative AI chatbot to devise and tailor recipes, they will likely not do this in another app.

Final UI Design

After sufficient testing and analysis, I refined the final screens in Figma. With the solution name being Clean Plate Club, my goal was to create a visual identity that feels cordial and welcoming yet personal, one that makes the user feel proud and excited about their savings and contribution to reducing food waste yet also like they are part of something bigger than themselves. The earthy color scheme and use of the serif font "Lato" mirrors classic kitchen cook books, and the food caricatures act as mascots to the club, celebrating the user's contributions.
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