I live within 15 minutes of 6+ major supermarkets. Checking weekly ads was tedious and store flyers only surface about 10% of what is actually on sale each week. To solve this, I created Grocery Detective (grocerydetective.com), a tool that finds local prices and weekly deals across grocery chains by zip code. It can send a weekly email digest to users for saved items. The hardest past is data normalization between stores. One chain lists an item as "Chobani, vanilla, non fat greek yogurt, 5.3oz" while another lists "Chobani, low-sugar vanilla yogurt, 0 fat dairy, 5.3 oz". It's required a mix of manual matching (with a fun, Tinder-like matching game on the backend) and indexing based on different product identifiers. Early usage showed me that creating generic items would also be needed. Users are searching for "Whole Milk" but any data normalization would not match Walmart's Great Value milk with Kroger's milk. A separate index manages this so the most frequently searched items are indexed together. The matching is still not perfect, so let me know if you have any suggestions on how to improve and automate matching. I’d love your feedback on our UI and search performance! Check it out and let and let me know what features you’d like to see next.   submitted by   /u/grocery_detective [link]   [comments]