Inspiration
As a busy household shopper tired of overpaying for groceries, I noticed how much money slipped away buying everything at one store. I wanted a tool that takes the guesswork out of comparing prices – something simple enough for any family to use, that turns "budget stress" into "smart savings".
What it does
GroceryList Splitter lets users enter their grocery list (with optional quantities), then automatically assigns each item to the local store with the lowest price. It shows a clear breakdown of costs per store, calculates total savings, optimizes the shopping route, and links directly to each store’s online ordering page – all in a clean, mobile-friendly interface.
How we built it
We started by mapping core user needs (simple input, clear savings, easy routing) to a responsive web layout. We built the price-assignment logic first, then integrated route-calculation tools and store API links. The UI was designed with a intuitive card-based layout for store-specific lists, prioritizing readability across devices.
Challenges we ran into
Balancing simplicity with functionality was tough – we had to make complex price/savings calculations feel seamless for users. We also struggled to refine the route logic to feel "natural" (not just algorithmic) for everyday shoppers, and ensure online links worked reliably across different store platforms.
Accomplishments that we're proud of
We created a tool that delivers on the 15-25% savings promise consistently, with an interface that’s easy for non-technical users to navigate. The route optimization feature has been a hit – users love how it cuts down on driving time and fuel costs alongside grocery savings.
What we learned
We learned to prioritize user experience over "cool features" – shoppers care most about clear savings numbers and easy-to-follow lists. We also gained insight into how pricing psychology impacts user trust: transparent, itemized cost breakdowns make the tool feel more reliable.
What's next for this project
We plan to expand support for more local retailers, add options to save favorite lists, and refine the route logic to account for real-time factors like store hours. Long-term, we want to integrate more personalized features (e.g., preferred stores) to make the tool even more tailored to daily shopping habits.
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