foodies

Foodies

With the onset of the COVID-19 pandemic, our local restaurants began to struggle. We were tasked to utilize the user-centered design approach to develop solutions. We developed Foodies, an application that provides curated food options to swipe through & creative meal experiences across restaurants to choose from. 

My Role

My primary role was UX Researcher and Project Manager. I developed our research strategy and materials including surveys, interviews, and a diary study. I then co-developed our initial low-fidelity prototype of our design in Figma and conducted usability testing.

The Problem

With the onset of the COVID-19 pandemic, lockdowns & precautions have caused a shift in daily routines. To protect the local restaurants & local culture during this uncertain time, we set out to discover the optimal method to foster more community engagement. Our group, Team Yummy, is looking for a new, better way to get neighboring communities to support local restaurants. We aimed to create a method that is both personal & unique.

Target Users & Stakeholders

Our target users are primarily community-based customers / people who order food from local restaurants; and secondarily restaurant owners and employees who benefit from customers ordering food from their location(s).

Primary Stakeholders: Local community of people and customers who order food from restaurants.
Secondary Stakeholders: Restaurant owners and employees who are driven and affected by their local communities.
Tertiary Stakeholders: Food suppliers (e.g., fishermen, farmers, distilleries) that provide for local restaurants whose well-being is impacted by their success.

We selected customers as our primary stakeholders because they will be the main users of our solution. Local restaurants rely on their neighboring communities, so a customer-driven idea will be our plan to address and tackle those needs as a way to help restaurants improve their business. Restaurant workers are our secondary stakeholders in that their well-being is impacted by customer behaviors and their perspectives were considered heavily in our research process, but they aren’t the ones who will be directly using our design. Food suppliers are considered our tertiary stakeholders because while they are also affected by customer behavior and restaurant success, their role isn’t as heavily correlated as with our primary and secondary stakeholders.

User Research

Below were our research questions:

1. How are people deciding where they want to eat? 
2. What factors encourage customers to visit the same restaurants more than once? What discourages them?
3. How does the neighboring community currently engage with local restaurants? 
4. What are the barriers to neighboring communities supporting local restaurants?
5. What are successful local restaurants currently doing to maintain their business? 

We used a variety of methods to triangulate our research, a survey with 74 respondents, 4 people in a 5 day diary study, 2 rounds of semi-structured interviews covering customers and restaurant operators, 4 each. We triangulated our research by incorporating methods that could help us learn from our target users, observe their behaviors, and ask them followup questions.

Survey

We initialized our research with a survey aimed at restaurant customers in order to gather data on common demographics, behaviors, and perspectives regarding their current food-ordering experiences. We chose to conduct a survey because it was a convenient way for our team to reach out to a lot of people online to gather data in large numbers, and based on initial findings from the survey, we would then be able to dive deeper into those topics in 1:1 customer interviews. We distributed the survey primarily across messaging boards (HCDE 518 slack) and Facebook groups (Seattle Foodies).

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Interviews

We then conducted a series of interviews aimed at both restaurant owners/employees and restaurant customers. We sought to conduct interviews because they would allow us to probe further into unique attitudes and behaviors that may not have previously been found in our survey results. Interviewing restaurant employees also gave us a chance to learn more about the restaurant-sided perspective instead of just the customer-sided perspective. In total, we interviewed 4 restaurant owners/employees and 4 restaurant customers over video calls.

For restaurant workers, we went with a semi-structured interview format and encouraged them to describe their circumstances based on a few guiding questions (e.g., “tell us about how your restaurant distinguishes itself from others”).

For restaurant customers, we also went with a semi-structured interview format and encouraged each of them to engage in a conversation about their food-ordering habits and circumstances (e.g., “how does your living situation affect your decision to order food?”). 

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Diary Study

Our final research method was a diary study conducted on restaurant customers. We operated this diary study across 4 participants over the course of 5 days. We chose to use a diary study because it was a convenient, time-efficient method that would allow customers to quickly reflect on their food-ordering thought process as it happened / soon after it happened (e.g. what factors led up to the decision and how they felt), and this would allow us to more deeply understand the surrounding contexts of their decision-making rather than it being a vague recollection of their memories. Whether or not a participant decided to order from a restaurant that day, we would still learn the motivations that informed that decision.

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Findings

Here are some findings about our potential user base from our research:

• Most are young professionals but also a significant portion of established professionals
• 66% of users order food from a restaurant 1 or 2 times a week
• And they typically live with their significant others
  

And, our top research findings:

• customers want optimization 
• safety
• to explore and to enjoy
• restaurants need more exposure

Personas

We then developed 3 personas from the research to help guide our design, two primary personas and one secondary persona.

Design Requirements and Question

From this research and personas we developed a list of design requirements and revised our initial design question.

Design Requirements

• The solution should give customers some information about nearby restaurants, as Taylor is in a rush and Rachel is unwilling to travel far.
• The solution should assist customers in making more informed decisions, as Taylor doesn’t have as much time to analyze every restaurant.
• The solution should reassure customers about their food safety, as Taylor and Rachel are hesitant to trust restaurants.
• The solution should facilitate meaningful interactions beyond the food, as Rachel strives to socialize and bond with her family and friends.
• The solution should enable customers to find quality restaurant experiences that meet their expectations, as Rachel wants to enjoy herself and Taylor wants food that is worth her time and money.
• The solution should promote local restaurants to nearby customers, as Seth hopes to build community connections.
• The solution should be compatible with phones, since Taylor and Rachel primarily order food through their phones.
• The solution should incorporate inputted locations of its users, as customers prioritize locality and distance from restaurants.

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Design Question

• Original design question: How might we improve connection between local restaurants and neighboring communities when the restaurant needs more business and customers?
  

• Revised design question: How might we better inform neighboring communities about their decisions to order from local restaurants to help promote restaurants during a time of uncertainty?
  

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While we ultimately hoped to bridge a connection between restaurants and their local communities, we framed the primary users as customers since they are the ones who the restaurants will depend on — and restaurants will benefit mainly as a result of a customer-driven idea. We learned that customers don’t necessarily seek to make a connection with a restaurant but rather make smarter decisions to ensure the food is worth their time and money. We also wanted to rescope the ‘need for more business and customers’ to ‘a time of uncertainty’ in order to signal the unique conditions under which restaurants are currently operating during the COVID-19 pandemic.

Design Ideation

After our research, we created our refined design question: How might we better inform neighboring communities about their decisions to order from local restaurants to help promote restaurants during a time of uncertainty? 

We came up with a variety of ideas after completing the user research. We put all of our ideas into an affinity diagram and then refined further. We decided to go forward combining the idea of a dating-app like interface for food options as well as offering thematic, curated packages.

Once we were set with our design idea to move forward with, we refined design requirements into design goals.

Design Goals

1. Browse and order meals efficiently and conveniently  —  The design will help customers efficiently accomplish their food browsing and ordering goals and accommodate for those who are inconvenienced by time and/or location.
   

2. Curate experiences through personalization  —  The design will take into consideration customer preferences and inputs as a way to curate experiences and help all users achieve what they are all individually looking for.
   

3. Provide reliable safety information  —  The design will anticipate user-submitted feedback regarding restaurants’ safety to build towards a holistic platform where customers benefit from each other.
   

4. Promote the local restaurant community  —  The design will advance the promotion of the local restaurant community and help both customers and restaurant owners discover what’s nearby and what food experiences complement each other.

Storyboards

To move forward with the swipe-able app concept, we developed storyboards to show the main functionality.

Prototyping

Next, we then began the development phase of our design process.

User Flows

Following the storyboarding we developed user flows to flesh out more details of the expected design.

Low-Fidelity Prototype

First, we developed an expected information architecture for the prototype.

Then, we executed a low-fidelity prototype using Figma for our main user flows including setting preferences, swiping through food options, picking packages, and rating the order. Users can navigate to these different features through the menu bar.

Testing & Iteration

After creating the prototype, we conducted a usability study with 5 participants that fit both our primary and secondary personas. We had a set scenario and tasks that were given to participants following a script.

Overall, they were excited by the swiping and packages concepts. However, we could still improve the UI clarity on the menu bar, swiping, packages, and expand the rating system.

From the results of the usability study, we made some changes to our prototype. We moved the menu bar from the top to the bottom of the app for easier reach along with text descriptions. We add a more 3-dimensional tile view for the dish option, with the next option greyed out behind the current picture to better suggest swiping. We changed packages to meals and offered more options along with a specific option based on the user saves or ‘likes’. Ratings were changed to still have an overall star rating, but moved to the tagging system for other options along with space for additional comments.

Final Deliverable

Introducing Foodies, our final app solution designed using Adobe XD. Upon opening the app, a user can set their preferences and then begin swiping through dish options. Tapping on a dish allows for more details.

A user can also switch over to the option to view meals, experiences curated across multiple restaurants. The user can scroll horizontally through different categories and vertically through different options in each category. Saved items from dishes of meals automatically are categorized by type to view later. After ordering, the user can submit feedback on the overall experience, tag experience praises, rate health and safety, and leave additional comments.

View full prototype here