SavvyMeals
An all-in-one app that turns tight budgets into tasty meals.
4 members
8 weeks
Research overview
Our research goal was to deeply understand the grocery shopping habits and pain points of university students. We employed a mixed-methods approach, combining qualitative and quantitative techniques to gather comprehensive insights.
To frame identfied user painpoints in a way that invites creative solutions, we crafted a How might we question:
Methods
User Interview
In-depth conversations to uncover
motivation and challenges.
Key Findings
Interview: We conducted semi‑structured interviews with six university students who lives outside. The questions focused on three broad areas: Buying food, cooking meals, and Food storage. The findings revealed:
Students wanted to stick to a budget but found it tedious to keep track on offers across stores.
Many repeat the same meals because finding budget‑friendly recipes is hard.
Several throw away food because they forget what they already have at home.
Ideation
After generating several ideas, we used a MoSCoW analysis to decide where to focus. It prioritises the ideas according to how critical they are to the core value proposition and the constraints.
Prototyping and testing: Work in progress
Online surveys
Quantitative data collection to
identify trends and patterns.
Competive Analysis
Evaluation of existing solutions to
identify opportunities.
Survey: To complement the interviews with a broader context, we sent out a short online survey asking about living situations, shopping/cooking frequency, and what they prioritise when buying food.
Students shop 1–2 times/week and cook 4–6 times/week.
Cost and convenience were consistently ranked as the most important factors.
Affinity Mapping: User Needs and Feature Ideas
To synthesise our interview and survey insights, we created an affinity map. We grouped similar user needs and ideas together under four themes: Recipes, Shopping Lists, Budget, and Offers. Each theme represents a cluster of related needs or desired features expressed by participants.
Competetive analysis:
We reviewed five existing apps for price comparison, finding discounts and recipe suggestions and created feature matrix. It compares each service against the core functions identified: price comparison, budget tracking, and recipe inspiration
How might we help budget‑conscious students to eat well by effortlessly discovering affordable recipes, tracking spending, and finding the best deals in one place?
We held several brainstorming sessions where we applied the SCAMPER technique. This gave us a structured way to rethink both our pain points and the features of existing apps:
