The Problem

Meal planning can be time-consuming and requires dedication; and even when meal planning is done right, busy, unpredictable schedules, personal cravings, and convenience take precedence over planned meals. This often leads to purchased food going to waste, which causes significant economic and environmental losses on both a global and an individual level.

How might we improve the meal planning experience for people with busy, unpredictable schedules to reduce household food waste?

The Solution

Conserve is a meal planning application that generates plans based on the user's eating preferences. Using versatile ingredients, Conserve adds variety to people's diets while giving them the flexibility to change meals at any time based on cravings and unpredictable schedules. Additionally, Conserve is driven by user behavior and gets smarter after each use. For example, Conserve will know when the user gets a late start on cooking a meal and can provide recommendations for alternative meals with a shorter cook-time so they can keep up with their other obligations and be less inclined to eat out.

Preliminary Research

We jumpstarted our project by looking into existing research around food waste. We found that poor meal planning and shopping strategies, storing food incorrectly, overcooking, and confusion over expiration dates are the biggest contributors to food waste. These findings helped guide our user research phase.

User Interviews, Survey & Analysis

We disseminated a survey and conducted semi-structured interviews to better understand user perspectives, household food waste, and the challenges people face while meal planning and shopping.

Key Findings:

• Lack of awareness and over-shopping were identified as the leading causes of food waste in their household.
• Busy schedules, cravings, and convenience make people bend towards eating out.
• Sell by/expiration dates and labels are confusing.
• People generally stick to the same meals but are interested in trying new recipes.
• Grocery shoppers are influenced by store promotions.

Competitive Analysis

We evaluated existing products in the marketplace that focused on meal planning and food waste reduction. What we found was there wasn't an application that both effectively helps users reduce/track household food waste and meal plan quickly and efficiently, which helped us identify part of our value proposition.

Ideation & Prototype

'How might we...' Brainstorming Session

With our research, value proposition, and chatbot requirement in mind, we began ideating by asking a set of "how might we" questions to help guide us through our ideation phase.

How might we make users more aware of their expiring foods?
How might we help users create meal plans quickly and efficiently?
How might we prevent people from over-shopping?
How might we help people add variety to their diets?
how might we help people stick to their meal plan at the grocery store?

Initial Sketches

Original Design Concept

After discussing possible solutions, we decided on a chatbot assistant designed to provide users with meal recommendations, generate shopping lists, and help manage their food inventory.

User Flow

Paper Prototype

We created a paper prototype and conducted an informal usability tests to test the overall app concept, and evaluate the profile setup and manual meal planning experience. Additionally, we conducted Wizard of Oz testing to test our chatbot solution and the conversation flow using iMessage.

Findings

Finding #1

User responses were unpredictable.
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Solution

We added quick reply buttons to ensure the chatbot understood the user’s intent and eliminate the need for users to spend time crafting responses.

Finding #2

If the chatbot didn't respond immediately, the users were unsure if the chatbot understood their request.

Solution

Send a message or display a typing awareness indicator to inform users that their response is being processed.

Ideation & Prototyping

Rethinking Our Design Solution

A year and a half later, I independently revisited this project and noticed problems with the original design:

• The chatbot overcomplicates the solution
• Some UI issues: cluttered bottom navigation, font/background colors do not meet accessibility guidelines (WCAG), and inconsistencies with spacing between elements.

With this in mind, I created design principles for the new solution:

• Adaptable - the design should adjust to the user's lifestyle.
• Convenient - the design should require minimal effort and time from the user to operate.
• Sustainable - the design should be focused on preserving resources and reducing waste.

Prototyping

After reviewing our user research, "how might we" questions, and the new design principles, I started thinking of ways to improve our original design and created wireframes to test and iterate on these concepts.

Evaluation

Findings

I tested the designs with 5 participants who currently meal plan or have tried meal planning. Here are some of the key problems and solutions I found:

Finding #1

During the "change meal" flow, users had trouble remembering which meal they were changing.

Solution

Show the meal image and name at the top of the screen.

Finding #2

Users need more control over the meal plan start date.

Solution

Give users the option to choose the meal plan start date and the ability to change it later.

Finding #3

Users need the flexibility to choose which days they want to meal plan for, as well as the ability to incorporate leftovers.

Solution

Allow users to select which days they want to meal plan and which days they want leftovers.
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