Dishcovery helps you recognise, learn about, and cook with foods from around the world. It is a consumer app using image recognition to scan foreign ingredients and learn about their cultural and culinary contexts.
The app allows user to scan an ingredient, explore recipes by cuisine or ingredient, and save recipes for later.
Exploring the culinary terrain, we sought to understand the barriers that prevent individuals from engaging with and cooking cultural foods. Our goal was to identify these challenges and transform them into opportunities for deeper cultural connections through food.
Our need-finding mission involved face-to-face dialogues with a diverse demographic in the Bay Area—ranging from tech professionals and small business owners to artists and educators. These non-student adults, engaged in various vocations, provided a rich, nuanced understanding of the day-to-day culinary practices and the cultural significance of food in their lives.
In our need-finding phase, we engaged with a diverse array of personas (anonymised) to gain a comprehensive understanding of various cooking experiences:
We created empathy maps for each participant, such as a software engineer who misses the flavors of home and a local artist who uses food as a medium to connect with her heritage. These visual tools captured sentiments and experiences, highlighting the common thread of seeking authenticity and connection in their culinary endeavors. One such example is below.
The "How Might We" (HMW) questions are a set of prompts designed to open up the ideation space and encourage creative thinking. They reframe problems as opportunities for design. Our HMWs focused on making ingredients more approachable and self-explanatory for users. For instance:
How might we create a system where ingredients can showcase their uses and cultural significance?
To gauge whether additional context about a dish's cultural and historical background enhances its appeal.
Participants viewed images of culturally specific dishes, initially without, then with historical and cultural narratives.
How might we make unfamiliar ingredients speak for themselves?
To test if ingredient background information demystifies unfamiliar items and influences purchase decisions.
Participants were asked to rank their likelihood of purchasing certain foreign ingredients before and after being provided with comprehensive ingredient information.
After synthesizing the insights from our experience prototypes, we moved into the ideation phase. This involved an intensive brainstorming session where our team members independently proposed a total of 60 solutions, which we then compiled and analyzed for common themes. These themes were critical in guiding us toward solutions that aligned with our project’s goals and user needs.
A Grocery Shopping Companion with Image Recognition
Our initial low-fi and med-fi prototypes were aimed at testing core functionalities and gauging user interactions with the foundational concepts of our solution. This phase was crucial for exploring the user experience without the commitment to high-fidelity assets, allowing us to iterate quickly based on user feedback.
Based on our image recognition solution, the higher-level functionality of our app that we envisioned was that a user would be able to:
● Scan a foreign ingredient
● Learn about its and cultural geographical context
● Find recipes using that ingredient
● Save any recipe they encounter on the app for later use
● Explore recipes by dish, ingredient, or culture using a search function
Simple task: Locate and scan a foreign ingredient.
This task is important because it uses the central functionality of the app, which we hope would draw intrigue from users. If users are excited about the scan functionality and are encouraged to use it, this would lead to them learning more about many ingredients.
Intermediate task: Learn about the foreign ingredient.
This task is important to provide a transition between our simple and medium tasks. By learning more about the ingredient, users are encouraged to experiment with it, which was also a result affirmed by our experience prototypes.
Complex task: Cook culturally authentic dishes using that ingredient.
The fulfillment of enjoying a meal using a potentially intimidating ingredient is one of the most important results we’d like to provide for our users. Once users cook using the recipes on Dishcovery, they’ll have obtained a new experience and added a new recipe to their arsenal, hopefully encouraging them to repeat the process with a different ingredient.
Our V1 design was a collaborative effort, as none of us had extensive experience in Figma. Following the heuristic evaluation, I took the role of designer and re-designed the task flows to create V2, which is displayed in the following section. Sample screens for V1 are below, for the second task: learning about an ingredient.
The Design Evolution process involved iterative improvements based on heuristic evaluations and user feedback, aimed at enhancing task flow efficiency and user experience. Here is some feedback we received which led to a redesign and eventually V2.
Design Challenges & Solutions:
Design Challenges & Solutions:
This iteration of the design followed even more user research and heuristic evaluation. In brief, the V3 followed usability tests on the working version of V2 on Expo (built in React Native) in order to pinpoint where the user experience could be enhanced. This section will list the key screens as well as bullet points of what was introduced in V3.
A strategically designed "Cooked This!" button would serve dual functions. On the front end, it enhances user engagement by allowing them to collect badges or achievements, showcasing their culinary journey. Each completed recipe adds to their 'Culinary Passport', fostering a sense of accomplishment and encouraging further exploration.
On the back end, this feature becomes an invaluable analytics tool, providing us with direct insights into recipe completion rates. This KPI (Key Performance Indicator) not only measures the app’s engagement levels but also informs the product team about the recipes' popularity and user satisfaction. It's a subtle yet powerful method to track which cuisines or dishes resonate most with our audience, allowing us to tailor our content to user preferences more accurately.
Integrate a smarter recommendation system that not only analyzes user preferences and past behavior but also seasonal trends and local ingredient availability to offer personalized recipe suggestions.
Allow users to personalize their dashboard to prioritize the content they are most interested in, such as highlighting favorite cuisines, dietary-specific recipes, or seasonal ingredients.
Partner with culinary experts from diverse backgrounds to curate and verify the authenticity of recipes, ensuring that the cultural narratives are accurately represented. This could also include a feature where users can submit their own family recipes for inclusion after a review process.
Regular accessibility audits could lead to implementing features like voice commands for hands-free cooking assistance, high-contrast mode for users with visual impairments, and simple language options for users with cognitive disabilities.
