Pan.try

Prototype link (Please submit a link to a playable prototype, not a link to your design file) Link
Describe your project (max 150 words) Pan.try was inspired by the universal college student struggle to find food that is cost-friendly, nutritious, accessible with limited means of transportation, and efficient for their often very busy schedules. College introduces many different factors to students and we wanted to give students resources to make this transition easier. With AI’s help, Pan.try aims to remedy these issues by scanning students’ grocery receipts or food items, storing them in their “Pantry,” and then analyzing their purchase history to provide recipes and local discounts/deals that are based around their past shopping habits or current food inventory. With Pan.try, we hope college students can take a shot at “try”ing out more of their “pan” skills!
Describe your research process and findings. If you conducted any surveys or interviews, please include the survey form and/or interview questions here. If you conducted secondary research by pulling from online sources, please include a link to your sources. (Max 500 words) We began with brainstorming among our team members and asking various undergraduate students we each knew for common problem spaces that college students faced. After we identified some frequent pain points among these students, we chose to narrow our focus to one that impacted college students deeply and across the board, not specific to one university – food insecurity. Because it was such a broad problem space, we created a survey link and each team member interviewed link ~2-3 students. In total, we had a sample population of over 80 respondents. Following our user research, we consolidated the findings from our survey and interviews by creating affinity maps and identified that the root problems with obtaining food for college students were in pricing, accessibility (proximity of food sources), timing (convenience & efficiency of cooking), and nutrition. Additionally, we found a large disparity between on-campus students who never cooked or rarely bought groceries and off-campus students whose main concerns were doing both of the former. Although most students indicated that price, timing, accessibility, and nutrition were their top priorities, most off-campus students actually revealed that they rely heavily on off-campus dining (readymade food) and cheap sources to get their nutrition due to busy schedules and other inconveniences hindering their motivation to cook or seek fresh produce. We narrowed down our problem space to students who could not find accessible solutions to the problems mentioned above and conducted competitive analysis as well as secondary research to better understand the food insecurity problem space within college students & existing solutions. Some platforms that we studied included TooGoodToGo, MyFitnessPal, food resources on campus, and Instacart. For secondary research, we read through articles including link, link, and link, about student eating habits and problems they faced. The last thing we did to fully understand our user and problem was create user personas based on the two types of students we defined: first, an FGLI student who paid for their own food expenses and commuted by bike, and second, a student who received funds from their parents to pay for food and rent, had a car, lived off campus, and primarily cooked. After we conducted the primary and secondary research, we began ideating on features that could well translate our product goals and user findings. We brainstormed features by the four themes that we identified and again grouped them based on how much impact we predicted the feature would have and how much effort it would require the user to take. After ideating, we then moved on to mapping our user flows for potential functions of our product, finalized screens, and started developing low-fidelity wireframes.
Describe your most important design decisions. What research findings and/or user testing results led you to make these decisions? (Max 500 words) When we began our user research, we found that 40% of the off campus students’ problems were related to acquiring or preparing food. As we researched, we found that a lot of students who go from on to off-campus living have worries about having to learn how to navigate finding food for themselves, preparing it, and balancing their schedules on top of it. Many students also expressed that they end up relying on cheap fast-food options or unhealthy quick meals that are not nutritious and do not maximize their budget. We found four major themes that students care about when it comes to getting food: price, convenience (timing), and accessibility (proximity to them, cooking knowledge). Our AI scanning tool sought to address these four main pain points by decreasing the time spent figuring out what to cook and providing quick & easy recipes based on what students already have access to. The emphasis on personalized analyses (“Purchased frequently in the past”) was a design feature choice that sought to not just push recipes and deals onto students to promote more spending but to supplement the resources they already have. One of the biggest pain points we discovered amongst our interviewees/survey respondents was that off-campus students had too many expired groceries or a lack of knowledge of what to do with their leftover ingredients. Many students who disliked cooking revealed they were discouraged by the process of having to find recipes and check if they have all the proper ingredients when it was much simpler to buy food that would make them full. The majority of respondents also expressed accessibility as a deterrence from attempting to cook at all. This inspired us to develop a feature like the scan/recipe generative feature to 1) reduce the steps required in choosing what to make from what you have because time is money and 2) maximize what students are using their money on in regards to food expenses. Lastly, many of our users expressed frustrations over not knowing about opportunities to get cheap food that are normally only discovered by word of mouth. At the core of this, knowledge is a big barrier for students in knowing where to go to get their food when they live off campus. To remedy this disparity, we chose to implement the AI analysis feature that already existed for recipe generation to recommend nearby coupons and deals at various grocery stores & food delivery systems based on user purchase habits from the past. Our app’s biggest goal is to provide as much impact and value for college students in as few steps as possible. As a team, we had many conversations about our struggles with obtaining food and even faced some of the very issues we were addressing while working until late at night on this project. We earnestly developed Pan.try with the hope that it could relieve some hungry college students of the burden that comes with thinking about their next meal.