CONSUMER PACKAGED GOODS

AI Demand Forecasting and Supply Chain Planning for CPG Brands

Consumer packaged goods brands operate in one of the most demand-complex environments in commerce — hundreds of SKUs, dozens of retail accounts, promotions every week, and new product launches that need forecasts before sales history exists. TrueGradient is built for exactly this.

See a live demo for CPG

Explore AI Demand Forecasting →

Why CPG Demand Planning Is Uniquely Hard

Retailer account complexity

Each major retail partner — Walmart, Target, Kroger, Costco, Amazon — has different ordering cadences, promotional windows, and fill-rate requirements. A single SKU needs a different forecast per account.

Promotion-driven volatility

CPG demand is promotional demand. A single trade event can lift a SKU 3–10×, cannibalize adjacent SKUs, and create a post-promo trough that breaks baseline models entirely.

New product launch cold starts

New SKU launches — reformulations, seasonal variants, brand extensions — need forecasts on day one with no sales history. Statistical models produce nothing. Planners guess.

Assortment and pack-size complexity

Multi-pack, club-size, and ecommerce-exclusive formats all need independent forecasts. One brand can have 500+ active SKU-account combinations requiring daily replenishment signals.

How TrueGradient Works for CPG

SKU × DC × Account forecasts — not aggregates

TrueGradient generates forecasts directly at the operating grain CPG planners actually use: SKU × distribution center × retail account, at week-level. No disaggregation step. No second tool. The same forecast drives your S&OP, your replenishment signals, and your account fill-rate reporting.

Promotion modeling built in, not bolted on

Promotions, pricing changes, and trade events are first-class features in the model — not manual overrides applied after the fact. TrueGradient quantifies historical lift, cannibalization across the category, and halo effects before each campaign goes live, so your demand plan reflects what's actually going to happen.

Cold-start forecasting for new product launches

Attribute-based similar-product matching lets TrueGradient produce a day-one forecast for any new SKU — based on comparable products in your assortment, category benchmarks, and channel context. Planners get a defensible forecast before the first sell-in order, not six weeks after.

Probabilistic outputs — P10 / P50 / P90

Every forecast includes a full probability distribution so your supply chain team can size safety stock against actual risk, not a point estimate. Reduce excess inventory during slow periods without increasing stockout risk during peak.