SporkSave is an app designed to help anyone (but specifically college students) save. We observed that most unnecessary spending in college is for food, drinks, and coffee. Our app targets saving strategies to both discourage spending by eating/drinking out, and when not possible, to minimize how much is spent.

The app will passively track your location to see when you’re in a coffee shop, cafe, or lunch place and will instantly send a notification saying exactly how much money you could save by making the coffee/food yourself, buying a cheaper option on the menu, or going to a nearby place that is less expensive but similar (with directions provided by Google Maps). After buying food/coffee, there will be an option to scan your receipt to help evaluate your spending decisions and better train the algorithm to understand your spending patterns. Eventually realizing consumption patterns, the app will send reminders right before lunch about savings from bringing a lunch from home or a reminder to bring a reusable water bottle before you go out to save $2/day. In this way, both right before a meal/coffee time and entering a cafe/restaurant are “nudges” the app uses to induce better saving habits.

Before leaving the house, the app will suggest making coffee at home with suggestions similar to the order you would get at a Starbuck’s or other coffee place. At the end of the day, you would get a daily spending recap critiquing the day’s spending habits (“if you’re going to go out, save $2 by not buying a soda” or “much cheaper deli two blocks from where you ate” or “reminder that making your coffee at home would save $4/day”).

Because of the user component of scanning receipts to get the best use out of the app, SporkSave is best designed for those who are actively trying to improve spending habits. One problem we had is that we want to give users good saving tips and try to steer them towards making food/coffee at home (the cheapest option) then mitigating losses when eliminating spending is not possible, but we don’t want to seem overbearing or overly critical. The motivation for users is that the suggestions are meant to find cheaper options with no downside to them (finds better places on the same route, gives directions to nearest grocery store, suggests less expensive things on menu, etc). For users who really buy into the app, we calculate that they could save around $3000/year.

Fogg’s Behavior Model:

Motivation: an easy way to save money with no lifestyle downside to the user

Ability: a willingness to download the app and preferably scan your receipts

Nudge: before meal times, on the way to getting a meal, when one enters a cafe/restaurant (these are all decision points where spending is involved–Should I go out or eat in? Where should I go out? What will I get there?)