Hey Product Hunt! 👋 I built PromoLift because I kept seeing retail teams run promotions without understanding the full category impact. Here's a real scenario the demo data illustrates: a grocery chain runs "Summer Soda Fest" featuring two soda SKUs. Soda sales spike 52.9% — looks great, right? But here's what the category-level data actually shows: Beverages overall: +34.4% lift ✅ (halo effect — non-featured beverages also lifted +8.3%) Snacks: +6.9% (slight complementary lift) Bakery: +4.0% (neutral) Dairy: −6.2% ❌ (cannibalized — people bought soda instead of milk) Frozen: −6.8% ❌ (also cannibalized) The soda promotion "worked" at the product level, but it dragged down two unrelated categories. Would you run that promotion again? Maybe — but at least now you'd know. What you can do with PromoLift today: Create promotions and associate products from your catalog Input sales data manually or via CSV See real-time category lift (featured vs non-featured breakdown) Get instant benefit/detriment signals per category Switch between promotions to compare performance Everything runs in your browser — no backend, no database, no signup. Import your data, see your lift, make better promo decisions. I'd love feedback from anyone in retail, CPG, or e-commerce who manages promotions. What data would make this more actionable for your team?

PromoLift

See which product categories your promotions actually help

See which product categories your promotions actually help