WELLfed: A Case Study
Design System Buildout
I am presenting a case study for Wellfed, a mobile app that facilitates the process of choosing the right food for a user's dog. The current health concerns have instilled a sense of isolation in many people that has caused a rise in dog adoptions in order to find companionship. This surge in newly adopted dogs coupled with a rise in health conscious food decisions by existing dog owners has emphasized a need for a better way for people to select dog food. Wellfed aims to facilitate the process of choosing the right food for your animal companion.
Who is the user and what are they looking for?
“All the dog food looks the same so I just pick something and try it. If he doesn't puke we're good.”
I began my exploration of the problem by interviewing several dog owners. My intention was to gather as much information about the process people went through to purchase food for their dogs. I conducted 7 interviews with owners of varying levels of experience and was able to gather valuable insights into the motivations behind their choices. It was clear that one emerging pattern was the immense sense of protection owners had for their dogs. Going into the interviews I had always assumed that dogs protect their owners but the conversations emphasized that humans protect their dogs just as much.
“I always check to see what the first few ingredients are.”
“I'm new to the dog world so I rely on advice from friends or reviews online.”
“I look for grain-free option because my dog is allergic to some grains like corn.”
“My dog is old so I have to pick softer food for his weak teeth.”
Synthesizing The insights
In order to develop personas for our target user I arranged the data from the interviews into key insights. I then sorted those key insights into refined categories that allowed me to form a clear picture of the the greatest needs and pain points that arise during the process of selecting dog food. I was able to distill the user data into 3 key needs that would form the basis for my user personas. I then took those 3 needs and rephrased them into statements that I would use throughout the design process to refocus design through the lens of the user.
How might we...
Easily find what ingredients a pet food contains?
Find a pet food that accommodates my dog's health issues?
Leverage reviews/recommendations to facilitate the decision making process regarding choosing a pet food?
In order to be able to view the design through a human lens I created 2 relatable personas with a similar goals but slightly different motivations. The personas, Jean and Shane, were composites of the users I interviewed in the discovery phase. Jean is a long-time dog owner whose dog, Frodo, has entered old age and she makes her dog decisions with his health as a primary concern. Shane is the secondary persona and he represents dog owners who are in need need of advice because they don't know where to start with dog care.
Crafting A Solution
I began the developing a concept of the solution by first creating user flows to ensure that the users needs were met as they moved through the process of choosing a dog food. My first iteration suggested that the process would be one continuous flow from entering the app to finding the right dog food. I reiterated the task flow after another round of user interviews.
It was made clear through those interviews that a user would purchase a food using suggestions from the app then close it until their dog tried the food. They would then open the app once again in order to classify whether the food they tried was acceptable or not. I realized that I would be working with 2 separate task flows.
Must have a "try" list
Must have a way to access the "try list" after re-opening the app
Must be able to move a food to a different list
Should have a way to leave/edit a comment about why a food was added to a list
Should have a way to update an account to take new health conditions into consideration
Low Fidelity to Mid Fidelity
With a flow to work with and users to work for I set to ideating possible solutions. At this phase I determined that pen and paper would be the most appropriate tools in order to generate as many ideas as possible. Many concepts were scrapped before I was able to create usable foundational concept.
The sketches were then rendered into medium fidelity wireframes on Sketch. The only use of color was to determine the purpose of the buttons that would be used to add a food to different lists.
Goal: The user is able to add a dog food to their "Try List" then move it to their "Love it" list in under 5 minutes with no errors.
You've tried a dog food from your "Try List" and you want to add it to your rotation. Please add a food from your "Try List" to your "Love It List."
You're looking for a food for your dog who has a grain allergy. Please add a dog food to the "Try List."
You're vet just informed you that Buddy is overweight. Please update his profile to indicate his new condition.
The initial wireframe was I developed was then turned into a clickable prototype using InVision. After the prototype was created. I conducted usability testing with 5 different potential users.
Findings and Iteration
The usability testing provided several key insights that I used to reiterate the prototype. As I watched users click through the prototype I was able to observe patterns that revealed adjustments that could be made:
starting on the user profile page was confusing to users
the text was too small on the search page
users needed some type of signifier that something had been added to the list
The project deliverable was a mid-fidelity prototype. If the development were to continue I would have conducted another round of user interviews to further explore the possibilities and scope of the note system. Could it be made public and used as a bank for crowd-sourced recommendations? I would also further refine the information compiled on the results page to more acutely serve the needs of different subsets of users.