Forecasting: built on your channel data vs a mature statistical engine
Inventory Planner's forecasting engine is mature and well understood, and it works, especially on stable products with deep history. Where it struggles is with the things that increasingly define modern consumer brands: new launches with no history, promo cycles that distort the underlying pattern, demand shifting between Shopify and Amazon, and the noise of selling on TikTok Shop one quarter and not the next. Handling those means configuring your way around the engine. Lumina forecasts from the data you have today: Shopify orders, Amazon velocity, retail sell-through, returns, and your promo calendar. It picks the method that fits each product, layers in your promotions, launches, and growth plans, and shows you why the number is what it is. For scaling brands, that's the difference between a forecast you trust and a forecast you override in the spreadsheet anyway.
- Forecasts from Shopify, Amazon, and retail data directly
- Handles new SKUs, promotions, and seasonality with your knowledge layered in
- Rolls up to channel, region, and SKU views without rework
- A long-established engine with a track record on stable, deep-history SKUs
- A large existing user base, so there's plenty of documentation and community knowledge
- Familiarity: if your planner already knows it, there's no relearning