Forecasting: built on your channel data vs statistical models on ERP data
NetStock's forecasting is statistical, running on the structured data inside an ERP, with automatic model selection per item. That's a strength when your master data is clean and your business is stable, distribution-heavy, and not especially seasonal. It's a weaker fit when you're a consumer brand with promo cycles, omnichannel demand, and product launches that don't follow the historical curve. Lumina forecasts from the data you have today: Shopify orders, Amazon velocity, retail sell-through, returns, and your promo calendar. Its models are configured to how your range is split and profiled and how your products behave, so the forecast matches your own intuition about the range, with your promotions, launches, and growth plans included and every number visible. 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, with no ERP in between
- Configured to your range: how it's split and profiled, how each line behaves, with your promotions and launches included
- Rolls up to channel, region, and SKU views without rework
- Distribution and B2B SKUs with deep, stable history
- Master data that already lives cleanly in NetSuite or SAP
- Planning teams that run forecasting as a dedicated discipline